BRADLEY BREN CAHOON

Computer Skill Learning in the Workplace: A Comparative Case Study

(Under the direction of BRADLEY C. COURTENAY)

Twelve computer users in three organizations were interviewed in a qualitative study of how adults learn personal computer skills in the context of workplace activities. Transcripts and observational data were used as the basis for organizational case studies; a cross-case analysis identified general categories, events, and processes of individual, workgroup, and organizational learning.

Generally, individual learning began with a social situation requiring adaptation to computers. The most skillful participants progressed to adapting computer resources to work requirements. The transition from novice to experienced user, a process that a learner may enact many times, depended on asking questions, self-directed learning, learning more than one software application or computer system, and adapting computer resources to work requirements.

All participants indicated that informal learning through mutual problem solving and coaching had been more important in their skill development than formal training. Each workgroup included one or more individuals identified by peers as local experts, on whom the group relied for support, and negotiated implicit or explicit rules governing the distribution of computer work and skills. In some groups, these rules encouraged self-directed learning to reduce demands on local experts. In other workgroups, most computer tasks were delegated to local experts, with other members exhibiting little self-directed learning. These results were consistent with prior research on situated learning (Lave & Wenger, 1991).

Organizational expectations and support appeared to motivate self-directed learning and skill development. Members of bureaucratic service organizations developed less skill than members of a flatter, more profit-oriented organization. Informal learning was also influenced by conflicts between formal organizational structures and informal networks of computer users.

Recommendations for computer training include extending the duration of workshops, focusing on rehearsal of work tasks rather than enumeration of software features, training workgroups together, and involving participants in program planning. Alternatively, instructional technology labs can support self-directed learning and reduce conflicts in motivation by distancing learning goals from immediate work goals. Future research in this area could focus on quantitative assessments of transfer of training and the development of network-based systems to support collaborative learning.

COMPUTER SKILL LEARNING IN THE WORKPLACE:

A COMPARATIVE CASE STUDY

by

BRADLEY BREN CAHOON

B.A., The University of Georgia, 1983

M.A., The University of Georgia, 1985

A Dissertation Submitted to the Graduate Faculty

of the University of Georgia in Partial Fulfillment

of the

Requirements for the Degree

DOCTOR OF EDUCATION

ATHENS, GEORGIA

1995

© 1995, 1998

Bradley Bren Cahoon

All Rights Reserved

ACKNOWLEDGEMENTS

The research presented in this dissertation could not have been conducted without the support, encouragement, and cooperation of many people. I am especially grateful to the individuals and organizations who participated in the study and to the hundreds of computer training participants at the Georgia Center for Continuing Education whose experiences led me to examine this problem. Helen Mills and the other members of my department were unfailingly supportive during my research. Bradley C. Courtenay and the other members of the advisory committee–Ron Cervero, Sharan Merriam, Michael Orey, Edward G. Simpson, and Karen Watkins–improved this study greatly through their comments, criticisms, and insights. Other faculty and fellow graduate students provided valuable feedback throughout the evolution of the research. Joe Cafiero read various drafts and participated in a long-running e-mail dialogue that helped shape my thinking about the subject.

My wife, Lynn Cahoon, contributed to this study on many levels: assisting with transcriptions, proofreading, making editorial recommendations, discussing her own learning experiences, and listening patiently as I tried to explain to her and myself what I was looking for and what I found. For these reasons, and for her loving kindness, this dissertation is dedicated to her.

TABLE OF CONTENTS

Page

ACKNOWLEDGEMENTS iv

CHAPTER

1 INTRODUCTION

Context of the Problem 1

The Problem 3

Purpose of the Study 5

Significance of the Study 6

Definitions of Terms 8

2. REVIEW OF THE LITERATURE

Introduction 14

Quantitative Studies 15

Qualitative Studies 27

Organizational Studies 34

Situated Learning 40

Informal and Incidental Learning 45

3. METHODS

Introduction 50

Design of the Study 51

Population and Sampling 54

Data Collection 57

Data Analysis 60

Strengths and Limitations 68

4. FINDINGS

Case 1: Leisure Activities Department 72

Case 2: Outpatient Therapy Department 75

Case 3: Regional Publishing, Inc. 84

Cross-Case Analysis 90

5. DISCUSSION AND RECOMMENDATIONS

Summary 124

Discussion 125

Recommendations 135

REFERENCES 147

APPENDICES 156

CHAPTER I

Context of the Problem

Fifteen years ago, personal computers were a technological novelty. Now they are pervasive in organizations of all kinds and sizes, as much a part of the fabric of working life as coffee cups and telephones. Popular images of "the computer" in the mass media have shifted from monolithic mainframes attended by white-coated technicians to desktop systems that ordinary people use to work, play, and communicate. Personal computers are already so common that they are achieving a degree of invisibility. Just as electric lights, automobiles, and televisions have become unquestioned parts of day-to-day life in our culture, so personal computers are beginning to be taken for granted, almost as if they had always existed.

Many factors account for the rapid adoption of the personal computer. Perhaps the most obvious is the astonishing rate at which computers have become more cost-efficient. The performance of microprocessor and memory chips has improved exponentially since 1970, while at the same time the cost of computers has declined by half every two to three years (Brynjolfsson, 1993, p. 72). Constant innovations in design and manufacturing fuel a personal computer industry that shows every sign of continuing its explosive growth for decades to come (Cringely, 1992; Freiberger & Swaine, 1984; Ryan, 1990).

The potential for continuous improvement in price/performance ratios is inherent in integrated circuit technology, as miniaturization allows more transistors to be packed into smaller chips. Personal computer development has been further accelerated by consumer demand for more and better systems, as organizations purchase and install computers at a steadily increasing rate (Brynjolfsson, 1993). This hunger for computing power reflects global economic trends, particularly the increasing importance of information in the creation of wealth (Toffler, 1990). More than ever, the success and survival of organizations depends on their ability to obtain, process, and distribute time-critical information. For this reason, the personal computer has become a central tool of the modern workplace.

However, installing personal computers is not sufficient to achieve organizational goals. The ubiquity of the personal computer does not indicate that it has been assimilated painlessly into working life or that its presence has transformed every employee into a Tofflerian "knowledge worker." As Brynjolfsson (1993) notes in a review of the "productivity paradox" literature, "Delivered computing power in the U.S. economy has increased by more than two orders of magnitude since 1970, yet productivity, especially in the service sector, seems to have stagnated" (p. 67). He describes 17 empirical studies that report lower-than-expected returns on computer investments in services, manufacturing, and other sectors of the economy.

Brynjolfsson identifies four possible explanations for these findings: problems of measuring productivity accurately; the possibility that computerization tends to redistribute market share among firms rather than increasing total economic output; poor managerial decisions about computer acquisitions; and time lags between current investments and eventual benefits. The last of these dilemmas – the inevitable delay between an organization’s acquisition of computers and its members’ effective use of those computers – is closely linked to the complex problem of computer skill learning.

To realize the potential of personal computing, organizations have to ensure that workers actually use their computers, that they develop the levels of skill necessary for their jobs, and that they are able to adapt to ongoing innovations in hardware and software. Thus the pressures on working adults to learn about computers are increasingly urgent. So far, however, advances in this area of training and education have come much more slowly than advances in the technology itself.

The Problem

In spite of manufacturers’ claims of "user friendliness," many adults find that learning to use a personal computer is time-consuming, frustrating, and charged with anxiety (Filipczak, 1994; Howard, 1994). Unlike other technologies that have seen similarly rapid adoption, such as the telephone, the computer is not designed for one specific task. It is adaptable through programming to almost any activity, and this generality makes it more conceptually abstract. The physical design and environmental settings of personal computers rarely provide clues about their use, and the diversity of software means that skills learned on one program may not transfer to another. Considering the pressing need of organizations and individuals to meet these challenges, surprisingly little appears to be known about computer skill learning.

The majority of publications on computer skill learning (e.g., articles in newspapers and popular magazines, how-to books) are based on expert opinion or the promotion of specific products. Their proliferation provides some indirect evidence about the attitudes of adult learners; for example, the recent popularity of best-selling books with titles such as DOS for Dummies (Gookin, 1993) suggests that many book-buyers identify with the image of computer learners as "dummies" and may welcome a humorous approach to an anxiety-provoking situation, even as they align themselves with the targets of the humor. While content analysis of such works could prove an interesting study in itself, these books and articles offer little theoretical insight into the cognitive and social processes of computer skill learning.

A review of the scholarly literature reveals many empirical studies related to this subject, but so far no coherent theoretical basis for computer training appears to have emerged. One reason for this lack of theoretical support for educational practice is that research on computer skill learning is scattered across several disciplines, and scholars in one area often overlook related work published outside their own fields. In a helpful but incomplete review of the literature on computer skill acquisition, management professor Urs Gattiker observes that "limited cross-feeding and integration of research results is occurring between work in education and training, personnel psychology, and ergonomics, as well as in cognitive psychology" (Gattiker, 1992, p. 570). Gattiker’s review suffers from similar limitations, overlooking relevant studies in human-computer interaction (HCI), artificial intelligence, and anthropology.

As discussed in greater detail in Chapter II, the empirical literature on computer skill learning provides intriguing data and some powerful explanatory concepts, but often raises more questions than it answers. For example, a number of experimental studies suggest that popular training methods such as classroom instruction, computer-assisted instruction (CAI), and manuals are not consistently effective (e.g., Carroll, 1990; Carroll & Mack, 1984; Czaja et al., 1986 & 1989). Searches of several computerized databases, including ERIC, PsycINFO, Business Index, Current Contents Plus, and SocioAbstracts, found no studies that tried to assess the extent to which computer training transferred to actual work practices. One experimental study indicates that transfer between computer tasks may be much more limited than is assumed by most instructional designs (Singley & Anderson, 1989). Survey-based and ethnographic studies of workplace computer use suggest that managerial support for training tends to be minimal (Bikson, 1987; Olsten Forum for Information Management, 1993) and that workers rely more heavily on informal support from colleagues than on formal training and support for developing skills and solving problems (Bullen & Bennett, 1991).

Given the paucity of the research base, the data suggesting that computer training is limited in both availability and effectiveness, and the growing need to help adults develop computer skills, a critical problem emerges. How do adults actually construct the computer skills they use in the workplace, and how can this process be facilitated?

Purpose of the Study

The purpose of this study was to examine how adult learners develop personal computer skills in the context of workplace activities. This goal required investigating learning as adults experience it rather than under controlled experimental conditions, since what is at issue is adults’ adaptation to the practical demands and constraints of computing in organizational settings (Brown & Duguid, 1991 & 1992). The following research questions were used to explore this problem:

Significance of the Study

A better understanding of the ways adults experience computer skill learning could provide a theoretical basis for the planning, design, and delivery of improved computer instruction. Prior research suggests that cognitive and affective factors such as conflicts in motivation exert a strong influence on success or failure in skill learning (e.g., Carroll, 1990; Elliott & Dweck, 1988). Literature searches discovered only one prior study based on in-depth interviewing of adults about their subjective responses to computer skill learning (Howard, 1994). The present study identifies general categories that provide a context within which experimental research could be reassessed, synthesized, and adapted to the requirements of educational practice.

By focusing on individual histories of skill learning rather than on specific instances or techniques of training, this study points toward facilitative interventions that fall outside the scope of current computer training. For example, if informal peer interactions influence learning more strongly than classroom instruction, new organizational strategies may be necessary to shift instructional responsibilities from HRD departments or contract trainers to an informal network of "local experts" within the organization (cf. Brown & Duguid, 1991 & 1992; Lave & Wenger, 1991; Marsick & Watkins, 1990).

Current demographic and economic trends suggest that the significance of computer skill learning will increase. Large numbers of workers are being displaced through corporate downsizing; at the same time, the skill requirements for new jobs are becoming more complex and information-intensive. By 1989, more than 75 percent of the Americans who will be in the workforce in the year 2000 were already working (Miller, 1989). Younger workers cannot replace older ones each time skill requirements change; retraining and continuing education are the only cost-effective means of filling highly skilled jobs. Moreover, the pace of technological innovation is so rapid that those who already have computer skills must continuously learn new ones as organizations upgrade to new hardware and software. Facilitating computer skill learning may be the most economically important area of adult and continuing education during the next 10 to 20 years. Improvements in this area can help organizations achieve better returns on computer investments and can also empower workers to participate more productively in the workplace and exercise greater leverage in the labor market.

The potential significance of this study extends beyond current personal computer systems, if these are viewed as merely one example of technological innovation in the workplace. Other information technologies, some scarcely imaginable now, are likely to continue to transform working life. Already fax machines, pagers, modems, notebook and hand-held computers, local- and wide-area networks, and video teleconfencing are extending the concept of the "workplace" to include virtual communities whose members work together but rarely share the same physical space or time. For these early settlers of the electronic frontier, ongoing adaptation to technology is a fact of life. Moreover, such adaptation has become a defining activity of many professions (e.g., software developers, providers of information services, designers of interactive media, engineers, technology consultants, and researchers). A better understanding of computer skill learning will be valuable in easing the migration to a future in which technology is no longer part of the workplace, but in a sense has become the workplace.

Definitions of Terms

The diversity of systems, users, and organizational contexts makes computer skill learning an extremely broad topic. Below, "personal computer," "applications," "novice," "experienced user," and "computer skill" are defined for the purposes of this study.

A personal computer as considered here is a small, self-contained computing device with a video display, keyboard, and at least one disk drive, designed for use by one person. Personal computers have often been called "microcomputers," but this term fails to suggest that the unique quality of these systems is their use by individuals. This study focuses solely on desktop systems that have achieved widespread market acceptance. "Personal computer" as used here will refer either to IBM PC-compatible systems (i.e., computers using microprocessors based on the Intel 80x86 architecture) or Apple Macintosh computers. An informal review of industry publications such as InfoWorld and PC Week indicates that these two platforms account for all but a very small percentage of the personal computers in current use. Unless otherwise indicated, the terms "computer" and "personal computer" will be used synonymously.

The popularity of personal computers is largely a result of the commercial availability of personal productivity software or applications. Applications are computer programs designed as tools for word processing, desktop publishing, the creation of databases and spreadsheets, and other typical tasks. Unlike specialized "vertical" software, such as an airline reservation system or a point-of-sale system, applications are generic products that are commonly used in a wide range of situations; their functions are not defined by the specific information processing needs of a single organization. For example, skills in word processing or spreadsheet manipulation are more likely to transfer from one work setting to another than are skills in operating a corporation’s customized inventory system. McLean, Kappelman, and Thompson (1993) report survey results that indicate that working with spreadsheets, graphics, word processing, databases, desktop publishing, and electronic mail are the most common activities of personal computer users in organizations. Many empirical studies of computer skill learning have focused on word processing programs, which are the most common applications and often serve as a paradigm for personal computing in general.

Novice computer users are those whose ability to perform work-related tasks with personal computers and applications software is constrained by lack of knowledge or experience, while experienced users have achieved a level of skill that allows them to perform such tasks routinely. The distinction between novices and experienced users is central to this study; therefore, a working definition of skilled computer performance is necessary to recognize and evaluate the learning that occurs in this transition. For that reason, an extended discussion of computer skill follows, drawing on theoretical constructs from prior research on human-computer interaction to operationalize the concept in terms of specific behaviors and competencies.

Colley and Beech (1989) note that "activities are said to be skilled when the performance of them has reached a level where it appears to be effortless, where it is almost always accurate and where additional practice makes little apparent improvement" (p. 1). Skilled performance is goal-directed, uses feedback to correct errors, and is improved by practice. Colley and Beech distinguish perceptual, motor, and intellectual (i.e., cognitive) skills:

Personal computing performance requires the development of skills in all three of these categories. Computer novices must learn to filter their perceptions of the information on the display screen to identify important details; they must use motor skills such as typing and mouse operation to respond to these perceptions; and they must learn to interpret their perceptions in order to choose appropriate responses. Thus, in making the transition from computer novices to computer users, learners practice several types of skill simultaneously.

The effortlessness and accuracy of expert performance indicate that some computer skills are habitual or automatic. Examples include typing, in which the ability to locate keys becomes tacit with sufficient practice, and word processing, in which experienced users can perform complex actions such as deleting a sentence without conscious awareness of the individual steps involved. Such tacit knowledge is described as procedural, to distinguish it from conceptual or declarative knowledge; declarative knowledge is learned and expressed symbolically (for example, as facts or lists) while procedural knowledge is expressed by performing an action. Some aspects of procedural learning can be represented quantitatively, particularly the relationship between the time required to perform a task and the time that has been spent practicing it. According to Wærn (1989), who reviews quantitative studies of computer skill learning,

This function is often graphed as the well-known ‘learning curve.’

However, learning to use a computer involves much more than developing procedural skills, as is evident when a procedure fails to produce the expected results. Problem solving in such a situation requires the skillful use of declarative knowledge about the system. In the words of Wærn, this involves "learning the characteristics or nature of the problem space as well as learning how to search efficiently within it" (Wærn, 1989, p. 82). In computer performance and many other domains, experts appear to possess highly-organized knowledge about the problem space that allows them to reason their way toward solutions even when they lack sufficient information to choose among procedures (Bédard & Chi, 1992).

Cognitive scientists have attempted to account for this kind of performance by positing the existence of mental models that allow reasoning by simulation (Gentner & Stevens, 1983; Greeno, 1989). HCI researcher Donald Norman describes interaction with a computer as a cyclical process of execution and evaluation, in which the user must form an intention, decide how to execute it, act, and then evaluate the resulting state of the computer system. The ability to sustain this process depends on the user’s mental model of the system, which focuses attention on relevant aspects of the situation and allows the construction of explanations about the system’s behavior (Norman, 1986).

Research on procedural knowledge and mental models is helpful in operationalizing the concept of personal computer skill along several behavioral dimensions:

• Efficiency: In performing a task, novices are more likely to make mistakes and to perform actions unrelated to task goals, while experienced users tend toward optimal efficiency.

• Speed: Novices must think through each step of a procedure, while experienced users have automated many procedures and can execute them rapidly without awareness of individual steps.

• Attention: While novices are often distracted by irrelevant aspects of the system’s state, experienced users can focus their attention on salient details.

• Parallel processing: The efficiency of novices declines steeply when they attempt more than one task, while experienced users are often able to sustain high levels of performance on simultaneous tasks.

• Problem solving: Novices are frequently unable to recover from mistakes or deal with unfamiliar events, while experienced users demonstrate lower error rates and stronger problem-solving skills.

• Transfer: Beginners have difficulty in transferring skills to new systems and programs, while experienced users have a greater ability to interpret unfamiliar tasks in terms of similarities to previous experiences.

These differences between skilled and unskilled performance suggest both possible objectives for computer instruction and criteria for evaluating its outcomes. However, the processes through which novices become skillful users remain obscure. The studies described in Chapter II attempt to illuminate these processes with varying degrees of success.

CHAPTER II

Introduction

As yet, computer skill learning has received little attention in the literature of adult education. Rachal (1993) and others have focused on the use of computer-assisted instruction (CAI) to support adult basic education and teaching in other content areas. However, the use of computers as a medium for the delivery of instruction is tangential to the problem of learning workplace computer skills. Most relevant publications have been dated by the recent evolution of the technology (e.g., Gerver, 1984 & 1986; Heermann, 1986).

The purpose of this review is to describe and evaluate empirical research on computer skill learning, in order to clarify what is already known about the cognitive processes and social situations underlying this learning and to provide a theoretical basis for this study. With a few exceptions, all the studies cited here are data-based, have been published within the last decade, and deal with commercially-available personal computers and software. These criteria have allowed the inclusion of experimental studies, ethnographic observations, interviews with and surveys of personal computer users, verbal protocol analyses, and organizational case studies.

The first section of this chapter reviews quantitative studies of individual computer skill learning, most of which are based on experimental or quasi-experimental comparisons of various instructional treatments. However, methodological problems limit the application of many of these studies to educational practice.

The second section reviews qualitative studies employing verbal protocol analysis and phenomenological interviewing, which present a different and potentially more practical view of individual skill learning.

The third section assesses organizational studies, presenting data on the social contexts in which most adults learn to use computers. The concluding sections discuss the development of computer skills in terms of theories of situated learning and informal and incidental learning, which provide the conceptual framework for this study.

Quantitative Studies

The studies reviewed in this section used experimental methods to collect data about how adults acquire computer skills. Subjects were grouped according to personal characteristics and instructional treatments, trained, and then compared on various measures of performance. In many of these studies, the treatments were identical to methods commonly used by providers of computer training and support: classroom instruction, CAI, video, and printed manuals. These studies would seem to be of immediate relevance to educational practice, but many do not fulfill this expectation. Their findings suggest that the learning associated with these forms of instruction is insufficient to account fully for the ability to use a personal computer in daily work. While many of the studies report similar results, discrepancies in their designs make direct comparisons between them difficult. A discussion of designs and results will identify some common methodological problems.

Two studies by Sara Czaja and her colleagues are representative of many others in their design and their findings. Czaja et al. (1986) evaluated three training strategies for teaching novices to use the WordStar word processing application: computer-assisted instruction (with commercially-available tutorial software), use of a printed manual, and instructor-led lecture and drill. The subjects were 135 women with basic typing skills and at least a high school education. In an experiment lasting eight hours, all subjects were trained on the same set of WordStar operations during the morning, reviewed this training briefly after a lunch break, and then attempted to complete a series of realistic word processing tasks. Performance was evaluated on number of tasks attempted and completed, average time per task, and average number of errors per task. Computer-assisted instruction was found to be the least effective means of instruction, which the researchers attribute to the passivity enforced by programmed instruction. However, they also note that "none of the methods evaluated in this study proved to be effective in teaching people word processing. On the average, people made approximately 7-11 errors per task, which appears too high..." (Czaja et al., 1986, p. 215).

In a 1989 paper, Czaja et al. analyzed the same data in terms of age-related differences in learning. The subjects were equally divided among three age groups: 25-39, 40-54, and 55-70. No significant interaction was found between age and training method. All subjects in the computer-assisted instruction condition performed less well, regardless of age. The subjects in the older group consistently performed less well than younger subjects in number of tasks attempted, time on tasks, and time-averaged errors. The authors suggest various possible explanations for the lower performance of older learners, including age-related differences in spatial memory. However, they overlook the possibility that older learners may require longer periods of training to achieve the same skill levels as younger learners (Zandri & Charness, 1989).

The design of this experiment, involving only a few hours of training prior to two hours of testing on six complex tasks, reflects an unrealistic assessment of the inherent difficulty of personal computer performance. One could compare it to providing novice automobile drivers with a few hours of instruction and then asking them to drive unassisted to various locations. Unfortunately, the treatments in most experimental studies suffer from the same lack of duration.

Two similar studies by Gist, Rosen, and Schwoerer (1988 and 1989) tested the effectiveness of observational learning and behavioral modeling (Bandura, 1986) in the development of computer skills. In the 1988 study, older and younger groups received three hours of spreadsheet training through either a tutorial or modeling approach. The tutorial group used CAI software to complete exercises and solve problems, while the modeling group worked with the same content but saw procedures demonstrated by an actor on videotape before each exercise. Both age groups performed better under the modeling condition; the older group scored less well on a performance test regardless of training condition, a difference that may reflect the three-hour time constraint.

In their 1989 study, Gist et al. explored the effects of behavioral modeling on self-efficacy (the perception of one’s own ability to learn or perform a particular task). Participants were categorized as high, medium, or low in self-efficacy prior to participation in three hours of spreadsheet training, with instructional treatments similar to those of the 1988 study. Participants were randomly assigned to behavioral modeling and computer-assisted instruction conditions, tested at midpoint for self-efficacy, and tested at the end of training for performance and satisfaction. Again, behavioral modeling led to consistently higher performance scores for all groups. Low self-efficacy participants reported fairly high efficacy at midpoint under the modeling condition, while under the CAI condition they reported much lower efficacy. Both these experiments support the use of video in training as a means of demonstrating and situating computer skills and tend to reinforce the findings of Czaja et al. on the relative ineffectiveness of CAI.

Zandri and Charness (1989) also compared the effect of different instructional treatments on younger and older subjects, but achieved different performance results. Forty-six subjects participated in four self-paced training sessions on the multi-purpose application Sidekick. Each session lasted a maximum of three hours. Treatments included working individually and working with a partner of the same age cohort; participants in the partnered condition were required to take turns at the computer keyboard during problem-solving exercises. All received written instructions and were allowed to work through the assigned exercises at their own pace.

Older adults asked for help two to three times as often as young adults and took twice as long as younger ones to complete the training, but achieved nearly equal performance results on a post-training performance test. Initial attitudes toward computers showed little correlation with final performance, and partnered training was found to be at least as effective as individual training. This study suggests that older adults can achieve the same levels of computer skill as younger ones if they are given enough time (through self-pacing) and have the opportunity to ask questions. All participants had near-maximal scores for performance, indicating that self-paced, problem-solving activities of sufficient duration are likely to lead to stronger skill development.

In another comparison of WordStar training methods, Frese et al. (1989) drew on the work of Donald Norman and others who have studied the user’s construction of a mental model of a computer system. Frese et al. categorized training methods on two dimensions, passive-active and sequential-integrated. The passive-active dimension describes the extent to which the learner is encouraged to construct and test hypotheses about the system, while the sequential-integrated dimension describes the extent to which the training relies on rote instruction in simple procedures or on high-level explanations of how procedures are organized within the system. A combination of active and integrated instruction was hypothesized to support the development of an accurate mental model.

To test this theory, the experimenters trained 15 subjects in three groups, each with his or her own computer and experimenter. All subjects were trained by editing an example text. The "sequential" group was given passive instruction with written materials detailing exact step-by-step procedures. The "hierarchical" group received a more detailed manual and diagram that presented the organization of commands within WordStar. The "hypotheses" group received no written material; they were encouraged to hypothesize about how to fix errors in the sample text and to experiment with different solutions. The correct commands were then provided by the experimenter.

Two-hour training sessions on two days were followed by a two-hour testing session. Subjects were assessed on their ability to recall commands, time-weighed error scores, keystroke efficiency, transfer of skill to a previously-unused command, prior typewriting skill, and other measures. As predicted, the hypotheses group outperformed the sequential and hierarchical groups on all measures, though not all differences were statistically significant. The hypotheses group showed the largest degree of variance on corrected error time, keystroke efficiency, and transfer. As in the studies by Czaja et al. and Gist et al., instructional methods requiring more self-directed problem solving produced better results than programmed instruction.

A study by Charney, Reder, and Kusbit (1990) further explored the relation between self-directed, exploratory learning and achievement of computer skills. Sixty-five subjects used the same training manual to learn 12 commands for the spreadsheet application VisiCalc. One group learned through guided exploration–no problems were posed to them, but they were encouraged to try out the commands on sample spreadsheets. The other group worked with six tutorial exercises, in which both problems and step-by-step solutions were provided, and six problems that required them to attempt to discover solutions, with feedback from the experimenters. The exploration learners did not spend as much time on (self-generated) exercises and seemed to have difficulty in posing realistic problems for themselves. Problem solving was slower, but appeared more effective than exercises in which each step was provided; problem-solving instruction also produced the best scores on a performance test given two days later. The researchers employed regression analysis to determine that this outcome was not simply the effect of longer training time in the problem-solving condition, and suggest that a completely exploratory method may be relatively ineffective for computer novices who lack sufficient knowledge of the domain to set appropriate learning goals.

Quantitative studies of computer learning vary widely in the degrees to which they attempt to assess factors of prior knowledge, motivation, and learning style. While few would dispute that these variables are likely to have a strong influence on learning outcomes, quantitative designs seem ill-equipped to offer much insight into their effects.

For example, Gattiker (1990) attempted to assess how individual differences such as academic ability and gender affect the acquisition of workplace computer skills. The subjects of the study were university students enrolled in a management course on end-user computing. Thus, in spite of a large number of subjects (n=347) and a fairly complex use of multiple regression analyses, the results of the study have more bearing on performance in computer classes than in the workplace. The study found that previous enrollment in a survey course in computer science was of limited benefit to subjects with below-average academic ability (as indicated by GPA) in their performance in the subsequent computer course. However, female students in this group seemed to show more ability to transfer knowledge from the earlier class to successful performance in the management class. The researcher found that performance of lower-ability students was significantly correlated to the amount of time they spent on lab practice–certainly not a surprising result. Gattiker’s findings in this study are too inconclusive to have a strong bearing on training practice.

In a similar effort to understand motivational factors, Webster and Martocchio (1993) examined the effects of task labeling (as work or play) and trainee age on learning outcomes. The 68 subjects were university employees enrolled in an institutionally-sponsored class on the mail-merging feature of WordPerfect 5.0. Participants were randomly assigned to work or play treatments and completed pre-training surveys designed to assess computer anxiety, computer attitudes, confidence, motivation, computer experience, and pretraining WordPerfect knowledge. Subjects in each treatment heard lectures and completed practice exercises on the same features of the software. In the play treatment, the instructor relied on a script using language that had previously been tested for its associations with play, while in the work treatment the researcher used work-related language to describe and explain the same training. The investigators hypothesized that the play treatment would produce more positive learning outcomes and that this effect would vary with the age of the participants. At the end of training, participants completed a questionnaire to assess post-training motivation and a ten-item objective test on the mail-merge operations.

The play treatment was found to be somewhat more effective for younger participants, but older participants showed no significant difference between treatments. As in most other studies, younger participants tested significantly higher on training outcomes than older ones. The researchers showed praiseworthy caution by controlling for training expectations, computer experience, and previous WordPerfect knowledge as covariants in their analysis. However, the use of a ten-item multiple-choice test as a measure of performance provides little indication of the participants’ ability to use the mail-merge procedure in practice. The researchers did not report the duration of the training activities (one can infer that training lasted less than one day), nor did they describe the opportunities participants had to practice with the WordPerfect application during training. This study provides little useful data about an important variable in computer learning: the effect of task labeling, or perceived goals, on motivation and performance (cf. Elliott & Dweck, 1988).

Bostrom, Olfman, and Sein (1990), as part of a series of computer training studies, attempted to assess the influence of learning style on training outcomes. Bostrom et al. distinguished two basic categories of training: exploration-oriented, emphasizing trial and error, learner control, and realistic tasks, and instruction-oriented, emphasizing programmed activities, instructor control, and enumeration of software features. To assess the interaction of these forms of training with learning styles, Bostrom et al. conducted four experiments in which subjects learned computer software tasks under varying instructional conditions. Prior to training, all subjects completed the Kolb Learning Style Inventory (Kolb, 1976) and were categorized in terms of the basic learning style dimensions abstract/concrete and active/reflective. The authors acknowledged that the disputed validity of this instrument limits the generalizability of their results, but reported a consistent pattern of findings across the four experiments: "In general, abstract learners performed better than concrete learners. In most cases, active learners performed somewhat better than reflective learners" (Bostrom et al., 1990, p. 113). The lack of significance in all but one of the four studies is attributed to varying degrees of experimental control, but the researchers also note that differences in preferred learning style do not prevent individuals from learning under other conditions: "A person’s learning preference does not preclude or negate what he or she learns" (p. 114). One implication of this is that, while some people may be predisposed to learn computer skills because of a learning style suited to abstract concepts and active experimentation, training methods can be adapted to the needs of concrete and reflective learners as well–for example, through the use of analogies to provide concrete references for computer structures and functions.

The same distinction between exploration-oriented and instruction-oriented training informs a 1993 study by Davis and Bostrom dealing with the interaction between training method and computer interface design. The experiment compared the effects of both training methods on learning to perform a set of basic file and directory tasks on IBM-compatible and Macintosh computers. Findings supported those of other experiments that indicate that the mouse-based graphical user interface (GUI) supports faster learning and performance than a command-based interface. The visual display of files and directories as icons that can be moved with the mouse appears to allow novices to construct a more accurate mental model of the computer system in a shorter period of time. Subjects learning to work with files and directories by typing verbal DOS commands had significantly lower and more variable performance scores. The type of interface used had a much stronger effect on learning outcome than training method, reflected in the low variability of performance scores under the GUI condition. Given the increasing popularity of the GUI as a standard on both Macintosh and IBM-compatible personal computers, the findings of this study are encouraging. However, the failure to find significance for differences in training method suggests once again the low effectiveness of formal training methods and the limited value of quantitative findings as guidelines for educational practice.

Some of the methodological problems of these studies are apparent. In his review of the computer skill acquisition literature, Gattiker (1992) notes that most experimental studies have failed to assess adequately subjects’ prior knowledge, perceptual speed, or motor abilities. Further, most research has been conducted with students in university settings (e.g., Gattiker’s own 1990 article), and thus does not support inferences about workplace learning: "Specifically, these propositions should be tested in the context of continuous education efforts undertaken to advance skills held by employees" (p. 565). Webster and Martocchio (1993) conducted the only study reviewed here that met this criterion, but its performance measures were unrelated to actual work tasks.

A second design flaw of most experimental studies of computer instruction has been their short duration. Total training time is usually in the range of two to four hours. Gattiker argues that this is inadequate:

Gattiker also notes that adults who have not been formally schooled for many years can be overwhelmed by long, continuous training sessions, such as a full-day experiment; intermittent training of the same total duration may be more effective, particularly for those with low initial knowledge or skill.

A third common design problem in experimental studies is their lack of consistent measurements of performance (learning outcomes). To some extent, this is an inevitable consequence of the variety of hardware and software used in the studies. However, it is an inherent limitation of experimental designs that performance must be assessed under controlled conditions that have little in common with the workplace situations in which most computer novices are required to develop their new skills.

The quasi-experimental methods discussed above are not the only possible approach to rigorous quantitative measurement of computer skill learning. Recent advances in brain research suggest that the computer itself, through imaging technologies such as positron emission tomography (PET), can reveal surprising relationships between learning and brain activity. Studies by Richard Haier and colleagues (Goldsmith, 1994; Haier et al., 1992a; Haier et al., 1992b) used PET scans to measure glucose metabolic rate (GMR) in the brains of subjects playing the computer game Tetris, an activity that requires eye-hand coordination and visual attention skills similar to those used in other computer tasks. Subjects were scanned after an initial session learning the game and then again after several weeks of practice. While average game performance increased sevenfold, GMR declined; more skillful performance was strongly correlated with lower levels of energy use. Haier et al. attribute the brain’s increased efficiency to the development of optimal cognitive strategies, which, once automatized, lead to the use of fewer extraneous brain areas and an overall decrease in the glucose used by the brain. The authors acknowledge that Tetris requires attention and speed, but "may not be an adequate probe of working memory" (Haier, 1992b, p. 425), which appears to play a critical role in many cognitive skills. These results appear to be consistent with other research on computer skill learning that emphasizes increased efficiency as a result of automatic processing (e.g., Singley & Anderson, 1989). However, the use of PET scans to study brain activity during learning is still in its earliest stages and seems to have no direct application to educational practice at this time.

Quantitative methods are attractive to many researchers interested in computers; the objects of study can also serve as instruments for data collection, statistical analysis, and even visualization of brain activity. However, the value of this work for trainers and educators depends on the researchers’ ability to explain the instructional implications of their data. Most quantitative studies have not taken a sufficiently broad view of the problem of computer skill development to provide useful insights about the experiences of typical adult learners.

Qualitative Studies

Many of the strongest factors influencing computer skill learning, such as motivations, expectations, goals, self-efficacy, and prior knowledge, do not lend themselves to quantitative measurement or statistical analysis. Data about these mental states may be more appropriately collected and analyzed through qualitative methods such as observation, interviews, and case studies (Bogdan & Biklen, 1992; Merriam, 1991). Qualitative data are human expressions of meaning such as speech and other actions; their form is generally verbal rather than numerical (Dey, 1993). In many respects, qualitative research provides a more integrated view of the process of computer skill learning than does quantitative research. This section reviews qualitative studies employing verbal protocol analysis and phenomenological interviewing.

Although it differs from most qualitative methods in its reliance on experimental conditions, verbal protocol analysis (Ericsson & Simon, 1984) is a common strategy in research on computer learning that has produced rich qualitative data. Learners are presented with various computer tasks and are encouraged to ‘think aloud’ about their actions, strategies, and problems; the sessions are recorded on audio- or videotapes, which serve as data sources. Analyses of recordings focus on reconstructing the learners’ cognitive processes rather than on measuring their performance (although simple frequency counts of actions or behaviors can provide a means of triangulating data from verbal reports). The crucial difference between protocol analyses and other experimental approaches is that learners’ subjective reports about their computer experiences are accepted as valid and valuable information.

Robert (1989) is representative of verbal protocol studies of computer learning. Robert was impressed by the tendency of Macintosh users to prefer to learn through unassisted exploration rather than by referring to manuals. In his experiment, subjects who had some previous computer experience but no Macintosh experience worked on their own with the computer for two hours without access to manuals or other assistance. Throughout, the subjects were encouraged to verbalize their thoughts and problem-solving strategies. In analyzing videotapes of these sessions, Robert observed subjects using strategies of trial-and-error, experimentation, repetition, analogy, and induction. They encountered numerous problems in the course of exploration: getting lost, being overwhelmed with information, being naive about the repercussions of their actions, misinterpreting system cues, becoming snarled in tangles of errors, and getting sidetracked. Robert concluded that exploratory learning is facilitated or hindered by the user’s prior knowledge of the task domain, the complexity of the computer system, and the quality of its interface design.

Studies of subjects with prior computer experience are helpful in assessing the levels of understanding achieved by typical personal computer users. Briggs (1990) and Santhanam and Wiedenbeck (1993) used verbal-protocol designs similar to Robert’s to assess the knowledge and skill of people who used personal computers on a regular basis but who had no special computer expertise. Both studies found that users who are competent in basic word processing often exhibit gaps in their comprehension of computer systems.

Briggs (1990) notes that many people teach themselves to use word processing applications but questions the success of these self-directed learning efforts. She argues that such learners tend to acquire procedural skills in word processing without adequate mental models of their computer systems. To test this hypothesis, Briggs studied the ability of users of varying experience to teach themselves a new word processing application on an unfamiliar computer. In addition to audiotaping the subjects’ questions and comments, she collected quantitative data in the form of recorded keystroke counts during two document-editing tasks.

Briggs found that few subjects were able to make use of their previous word processing experience to ask for relevant information; those who had used more than one word processing application were most successful in verbalizing questions that helped them accomplish the tasks. Often users lacked sufficient explicit awareness of system events to monitor and improve their own performance: "Users have a tendency to act before they think" (Briggs, 1990, p. 396). This study suggests that purely self-directed learning is not sufficient as a means of becoming a competent user, a finding consistent with the results reported by Charney, Reder, and Kusbit (1990).

Santhanam and Wiedenbeck (1993) were interested in the word processing performance of users who were neither novices nor experts. They studied 14 discretionary users–"lawyers, managers, professors, and university officials" (p. 205)–who had experience editing substantial documents. Subjects used their preferred computer system and software to perform a set of tasks identified as "routine" and "non-routine" by the experimenters. These subjects were compared to a smaller number of experts (secretaries and technicians who used the software daily) and novices (no experience with the software) on the same tasks. All subjects were videotaped and were guided to verbalize their thoughts as they performed the tasks. The performance of the novice and expert subjects provided triangulation for the data-coding categories used with the discretionary users.

The discretionary users were remarkably homogenous in their performance. They tended to display expert-like behavior on routine tasks, although they often used sub-optimal methods of accomplishing them, preferring to rely on a small set of familiar skills rather than attempting to learn new skills. On non-routine tasks, their behavior was strongly novice-like and showed that their conceptual knowledge of the systems and commands was shallow. These users appeared to have achieved a steady state of knowledge and showed little motivation to learn abstract concepts that would support expert-level reasoning about system behaviors. This study points toward a "plateauing" effect in the development of computer skills.

These findings are largely consistent with the influential work of John M. Carroll (Carroll, 1990), whose central thesis is that adults want to accomplish meaningful tasks and use prior knowledge about these tasks to try to make sense out of computer systems. Thus learners are vulnerable to a motivational double-bind; their eagerness to accomplish work-related goals often interferes with their development of a more coherent understanding of the computer system.

Carroll (1990) supports this view with data from a series of studies originally reported in Carroll and Mack (1984) and other articles. In the 1984 study, the subjects were ten temporary workers with extensive experience in routine office activities but no prior computer or word processing experience. They were asked to imagine a scenario in which a word processing system had just been introduced to their office and they were to learn it in order to train colleagues, working with the printed manuals and tutorials provided with the system. Each subject spent four half-days teaching herself to use the system and was then tested on a simple transfer task requiring her to type, revise, and print a one-page letter. Throughout, subjects were encouraged to think aloud, with experimenters intervening occasionally to prompt them to verbalize their thoughts. The self-training sessions were recorded on videotape, which was the primary data source.

The conditions of this experiment closely parallel the circumstances in which many workers first encounter personal computers. The researchers’ goal was to identify and categorize critical incidents in the learning process as the basis for generalizations about typical experiences of computer novices. In this study and others, Carroll and his colleagues describe patterns of behavior that will be familiar to anyone who has attempted a similar learning task. Learners consistently "jumped the gun" by plunging into tasks before they had read instructions. Their half-hearted efforts to coordinate their actions with step-by-step tutorial exercises were often thwarted by errors that left the computer system in a state out of synchronization with the training materials. These episodes often created tangles of errors in which the original deviations from the training sequence were forgotten or unrecoverable. Errors were also caused by inappropriate analogies drawn from prior knowledge (e.g., of typewriters). Even more striking was the tendency of learners to diverge completely from programmed instruction to explore system features on their own, often referring to several manuals simultaneously in an effort to construct an instructional agenda around personal goals.

Carroll (1990) argues that classical instructional design methods based on the decomposition of knowledge into basic concepts and principles (e.g., Gagne, Briggs, & Wagner, 1988) are ineffective in supporting the learning needs of adult computer novices. As an alternative, he proposes a "minimalist" design method that emphasizes less reading, more realistic tasks, and anticipation and exploitation of learner errors. He supports the effectiveness of such instruction with data from various experiments testing "minimal manuals," "task scenarios," and a "training wheels" interface in which advanced features of an application are blocked to prevent novices from becoming entangled in errors before they have mastered basic procedures.

Carroll’s work is especially important in its recognition that the need to gain computer skills is situated within a context of social incentives and constraints. This approach to the problem of computer training acknowledges that human relationships, rather than hardware and software, drive the process of learning.

Phenomenological studies of computer skill learning are relatively rare, but their findings have been similar to those of protocol analyses. Boland (1985), in a review of his interview-based studies of system design, argues that surveys and other quantitative methods are less effective than a hermeneutic approach that treats "the design and use of information systems [as] the text that we must try to understand" (p. 194). Boland emphasizes that all phases of computer use are interpretive activities that should be understood as dialectical processes of sense-making, in which users, programmers, and researchers are engaged in the social construction of meaning.

This philosophical orientation, which is more characteristic of most qualitative research in education than the comparatively rigid procedures of protocol analysis, is also evident in Howard’s 1994 study of adult computer users. Based on in-depth interviews with eight computer users, this study attempts to identify common themes in adults’ first encounters with personal computers. Not surprisingly, Howard’s subjects reported experiences similiar to those of Carroll’s: their motivational conflicts, anxieties, humiliations, and gradual adaptation are poignantly described in their own words and as interpreted by the researcher. Howard outlines several stages in this process: initial excitement about the potential benefits of computing; frustration caused by unexpected complexities; and accommodation to the practical requirements of computer use.

Howard’s study demonstrates both the depth and the dangers of the phenomenological method. His primary data are drawn from only four interviews, with an additional four interviews serving as data for triangulation. This sampling procedure seems insufficient to support useful generalizations, especially since the study does not build on earlier data-based research. Howard moves quickly from his limited data to broad assertions about the reproduction of cultural values. His analysis of recurrent subjective experiences of computer skill learning prefaces a highly-charged discussion of the ways in which the mediation of experience by technology reinforces values of "efficiency, accuracy, and progress" (p. 36) at the cost of more humane values of reflection and contemplation. While the philosophical arguments presented are challenging and valuable in themselves, their relationship to the interview data is tenuous and unpersuasive. As a result, the study is satisfying neither as an empirical study nor as an essay of opinion. However, it does demonstrate that interviews can produce data about the emotional and interpersonal conflicts inherent in computer skill learning.

Organizational Studies

A fundamental weakness of most of the research reviewed to this point is that the initial encounter between an adult learner and a personal computer usually occurs not in a laboratory but in the workplace. Most adults are motivated to learn about computers–willingly or not–by the expectations of managers and colleagues. No account of computer learning that fails to consider the obstacles and opportunities created by its organizational context can serve as an adequate guide for the practice of adult educators.

From the perspective of sociology, the acquisition of computer skills by individuals is an element of larger processes of organizational learning, through which

Computerization offers new possibilities for explicitly recording and transmitting organizational knowledge and even for capturing the decision-making skills of high-performing workers in expert system programs (Harmon & Sawyer, 1990). However, the inclusion of particular personal computers and applications in organizational routines can also lead to "competency traps," in which familiarity and habit block the adoption of more mature technologies. Levitt and March (1988) indicate that such learning can lead "an organization, industry, or society to persist in using a set of procedures or technologies that may be far from optimal" (p. 323). Examples include the standard QWERTY keyboard, originally created to slow down workers who were exceeding the mechanical limits of early typewriters; while alternative layouts offer potentially higher levels of keyboarding speed, the inefficiencies of the QWERTY design are apparently now too deeply embedded in educational and business practices to eliminate. The popularity of relatively primitive software such as MS-DOS threatens to produce similar effects. However, the price-performance ratios of computer systems improve so rapidly that fixation on any single standard seems unlikely to last.

One implication of the rapid evolution of personal computers is that their successful use in organizations depends on how workers respond to the stress created by continuous pressure to learn. Bikson (1987) summarizes the results of various RAND Corporation studies on organizational adaptation to computer-mediated work. These findings indicate that workers tend to respond positively to the initial introduction of computers in the workplace, in spite of the fact that few organizations take any interim measures to manage workload while users are learning a new system. Bikson emphasizes, however, that the short-term stress of introducing computers is less significant than the subsequent, ongoing increase in demands on cognitive resources:

Bikson points out that only about one-third of the managers surveyed believed that their organizations had a continuing role in facilitating users’ adaptation to electronic information tools, although more than 70 percent believed that moderate to major changes in the use of these tools would occur in their groups over the next two to three years. The implication is that employees are often left on their own to learn about new computer systems. Bikson suggests that workers’ learning can be enhanced by informal knowledge sharing within workgroups and by training that promotes the development of cognitive models of computer systems rather than rote performance, thus supporting problem solving, generalization, and adaptation to next-generation tools.

The issue of computer skill learning is complicated by debate about the effects of computerization on the social environment of work. Some writers contend that computers lower the cognitive demands of work, fragmenting jobs and reducing the quality of working life. Braverman (1974) framed the terms of what has come to be called the "deskilling debate," arguing that automation serves to increase managerial control by lowering skill requirements, making it possible to hire less educated and experienced workers and thus reduce labor costs. However, it is not clear that such effects are inevitable consequences of computerization.

Kraut (1987) observes that research on the deskilling issue has produced a range of contradictory results and attributes this to several causes. First, case studies have often focused on organizations using technology at "different epochs and stages of maturity" (p. 14). For example, studies of centralized, minicomputer-based word processing centers cannot be compared directly to studies of individuals using word processing applications on personal computers. Second, "researchers have ignored important level-of-analysis distinctions about the units of work that are being skilled or deskilled" (p. 17). Often the deskilling of a particular task is accompanied by the reorganization of tasks within a job; spellchecking may reduce the lexical skills once required of secretaries, but the availability of laser printers and multiple fonts demands learning new typographical skills. Third, the introduction of computers can have the effect of redistributing tasks across job categories, so that skill needs are shifted within organizations: "In universities, professors do much of their own typing with word processing equipment and personal computers, transferring some of the most onerous of data entry tasks from secretaries to professionals while at the same time giving the professionals more control over the form and content of their writing" (p. 19). Such transfers of skill requirements would seem to have generally positive effects on job quality–provided that resources are available to support learning.

Citing early social analyses of the telephone, Kraut argues that attempts to predict and evaluate the effects of technological change on the workplace have been notably unsuccessful. Our limited understanding of how personal computers affect the quality of working life may encourage overly-simplistic interpretations of the social impact of the technology. Similarly, Rule and Attewell (1989) argue that "computing has become a kind of projective device for social scientists and other social critics" (p. 131). In a survey of 184 private sector organizations in and near New York City, they found the majority of computing activities to be straightforward conversions of conventional processes such as payroll, invoices/billing, accounts receivable and payable, word processing, order entry, general ledger, financial statements, mailing lists and labels, and so on. At each site, computers were adapted to existing organizational functions and goals, which remained largely unchanged.

However, some researchers have observed more radical effects on organizations. In her case study of several corporations adapting to new technology, Zuboff (1988) observed the emergence of new patterns of collaborative work, in which learning computer skills coincided with learning new forms of organizational behavior. She concluded that the introduction of computers into an organization can serve to transform the culture of work by creating

The ability of computers to create a new kind of work environment is particularly evident in organizations using groupware applications. These programs are designed to support workgroup collaboration, typically including functions such as electronic mail, document exchange, scheduling, and time logging. Bullen and Bennett (1991) interviewed 223 people in 25 organizations using groupware, ranging from large corporations to small businesses. Their findings provide interesting insights about the role of organizational activities and values in the individual’s acquisition of personal computer skills. Some features of the groupware applications were quickly and generally adopted, while no one bothered to learn other features:

When organizational training efforts focused on the procedural mechanics of groupware applications, users tended to learn only the most basic skills and to employ the tools in unimaginative ways. In some cases, where managerial expectations for improved performance were high but groupware introduction involved no re-examination of current work processes, the pressure of having to learn a new tool had a negative effect on productivity. Where trainers presented groupware in terms of its ability to accomplish the organization’s unique work tasks or to make workflow more efficient, people made better use of the applications.

Successful adoption of groupware and other personal computer applications seems to depend less on formal training than on advocates in management who champion their use and on departmental "gurus" to whom co-workers can turn as learning resources. This finding is consistent with other studies that suggest that one-on-one problem solving episodes are the most popular form of computer learning in organizations. Adult learners tend to prefer to ask another computer user a question rather than rely on manuals or on-line help, perhaps because such exchanges situate new knowledge in the context of shared activities:

Two key points emerge from the literature on computer learning in organizations. First, training and learning are not equivalent. As shown by the experimental studies of computer instruction reviewed above, people do not generally achieve significant levels of practical skill solely through formal training, if they are fortunate enough to receive any. Most personal computer learning occurs in the workplace in the course of day-to-day activities. Second, such learning is usually a communal activity, in which computer knowledge is developed and shared within workgroups. Such sharing serves not only to accomplish organizational goals but to construct the social identities of the participants. These points are elaborated in the conclusion of this chapter, which discusses theories of situated learning and of informal and incidental learning as a conceptual framework for the study of computer skill learning.

Situated Learning

To support practice effectively, educational theories should explain and predict learning in ways that can guide the planning, design, and delivery of instruction. Good theories of computer skill learning must explain both successful and unsuccessful instruction. For example, Carroll (1990) presents evidence that some manuals and CAI tutorials can actually impede adults’ progress in gaining practical computer skills, while studies such as those of Czaja et al. (1986 & 1989) suggest that short-term classroom training can be equally ineffective. Yet people do learn to use personal computers and succeed in getting meaningful work done. These findings can be understood in terms of an emerging body of theory, often called situated learning, that claims that knowledge is inextricably involved with the social circumstances of its use (Lave & Wenger, 1991).

Situated learning has roots in a variety of social scientific research traditions, including cognitive anthropology, activity psychology, and critical theory (Chaiklin, 1993). It is not a single, unified learning theory, nor are the most prominent researchers in this movement in unequivocal agreement about its goals, methods, or principles.

The person most strongly identified with situated learning is the anthropologist and educational researcher Jean Lave, whose central concern has been to move the study of cognition and learning out of laboratories and classrooms into settings of everyday activity. Some of her early work focused on the methods of calculation used by adults in grocery shopping, food preparation, and other ordinary situations; in these studies, she found that adults rely on procedures that exploit the physical materials at hand rather than on the arithmetic algorithms they were taught in school (Lave, 1988; Lave, Murtaugh, and de la Rocha, 1984). With Etienne Wenger, she has elaborated the concept of situated learning into a theory of "legitimate peripheral participation" that emphasizes the relationship between learning and participation within social and historical "communities of practice" (Lave & Wenger, 1991). In a recent article, Lave articulates a set of premises that indicate the basic approach of situated learning theorists:

Lave insists that situated learning theory itself, like the practices it describes, should be seen as the shared construct of a community rather than as a reified body of knowledge.

John Seely Brown, Allan Collins, Paul Duguid and others have collaborated on a series of papers that apply concepts of situated learning to a variety of domains: the culture of traditional schooling (Brown, Collins, & Duguid, 1989); the use of "cognitive apprenticeships" to teach reading, writing, and mathematics (Collins, Brown, & Newman, 1990); the development of intelligent tutoring systems (Brown, 1990); organizational learning (Brown & Duguid, 1991); computer skill learning and system design (Brown & Duguid, 1992); and educational technology (Brown & Duguid, 1993). These articles will provide the primary sources for the following discussion of situated learning.

Situated learning can be described in terms of three premises: its rejection of the idea of general transfer of knowledge; its insistence that cognition is socially distributed rather than solely an attribute of individual minds; and its social and historical analysis of communities of practice.

The general transfer of knowledge is implicitly assumed by almost all forms of institutionalized education. In this view, knowledge can be abstracted from the situations in which it is used, presented to students in a generalized, symbolic form, and subsequently applied by them to tasks outside the instructional setting. This belief informs most of the methods and tools of schooling, including lectures, textbooks, and examinations. Unfortunately, there is little empirical evidence supporting general transfer. Singley and Anderson (1989) review research in this area, beginning with the studies of Thorndike (1906), and find no basis in the psychological literature or in their own experiments to support claims that generalized knowledge can be transferred to situations that do not share identical elements with the situations of its acquisition. Instead, knowledge tends to be highly use-specific. Singley and Anderson offer the "extreme example" of someone who has been told the rules of chess:

If computer knowledge and skills are inseparable from the situations in which they are applied, the frequent failure of computer training to improve performance in other settings is more comprehensible. Having rehearsed a procedure or heard about a concept in a classroom does not guarantee that one will be able to use it appropriately in practice.

Another element of situated learning theory is its location of cognition within material and social environments rather than inside peoples’ heads. This view appears to oppose mainstream cognitive psychology and artificial intelligence, which attribute problem-solving performance to processes occurring within individual agents. That such processes occur is not disputed; however, ethnographic studies in settings as diverse as aircraft carrier navigation (Hutchins, 1993), industrial production (Darrah, 1992), copy machine repair (Orr, 1990) and tailoring (Lave & Wenger, 1991) suggest that people rely more heavily on interactions with co-workers, tools, and materials to do their jobs than on the application of knowledge from memory. Situated learning theory holds that locating cognitive skill solely within individual minds ignores the way people communicate with each other and use their physical environments to distribute the load of memory search and problem solving. Tools and workplaces provide resources that reduce demands on participants’ memories and logical abilities; communication with other workers frames problems, narrowing the search for solutions.

The significance of this view for research on computer skill learning is primarily methodological. It suggests that rather than relying on laboratory experiments or surveys, researchers are more likely to understand how people learn to work with computers through interviews, fieldwork, and document analysis. These methods allow the collection of better data about the social contexts of computer use and may shed light on the ways learning occurs in the process of work.

A third element of situated learning theory is its social and historical analysis of communities of practice. If the knowledge required for work is seen as constructed by groups rather than belonging to individuals, it becomes important to understand how the organizational context of an activity has evolved historically. Work practices occur within larger cultural and economic processes that shape the behavior and understandings of participants, often in ways of which they may be unaware. These processes influence learning by shaping perceptions of who can legitimately participate in which activities, how conflicts of interest between "newcomers" and "old-timers" should be resolved or repressed, and what kinds of social identities participants will adopt (Lave & Wenger, 1991).

In the context of computer skill learning, these issues are closely tied to processes of organizational innovation. An understanding of how people learn to work with computers seems to be inseparable from the changes that computers create in organizational structure and behavior (Zuboff, 1988). The implementation of new information tools carries with it new expectations for productivity (Bikson, 1987) and the possibilities of deskilling and redistribution of skills (Kraut, 1987). In turn, organizational innovation has to be understood in the context of global economic changes that make computerization a matter of competitive survival (Toffler, 1990).

These elements of situated learning theory may account for aspects of computer skill learning that have otherwise received little attention. In its emphasis on everyday practice, situated learning has similarities to a number of theories of adult learning, such as Schön’s concept of the "reflective practitioner" (Schön, 1983). Another theory that deals more directly with the communication of knowledge through social interactions is informal and incidental learning (Marsick & Watkins, 1990).

Informal and Incidental Learning

Informal and incidental learning theory, like situated learning, is based on the premises that training and learning are not equivalent and that most learning occurs in the course of work practices. It addresses learning at several levels: individual, workgroup, organizational, and professional. Framed as a theory of human resource development, it is developed around cases and situations familiar to trainers in many kinds of organizations and is thus more adaptable to applications in adult and continuing education than most research on situated learning. Its basis in action science (Argyris, Putnam, & Smith, 1985) provides a framework for organizational interventions that encourage people to reflect on their attitudes, beliefs, and practices. The categories of informal and incidental learning are useful in analyzing the kinds of computer skill learning that occur without formal training.

Informal learning occurs primarily outside institutionally-sponsored instruction. It is goal-oriented and intentional; it can be planned, but is often spur-of-moment. It includes self-directed learning, as in the case of someone who "fools around" with a new computer program, perhaps dipping into books or on-line help to construct an ad hoc curriculum, trying things out and learning along the way. Such learning is motivated by real-world tasks and agendas (Carroll, 1990). Alternatively, an informal learning episode might involve networking within a workgroup or organization, identifying people who are expert users of a particular program in order to solicit their help in resolving a problem (Bullen & Bennett, 1991).

Perhaps the most common informal computer learning situation is one-on-one coaching or mentoring by a co-worker. An employee may give a new worker an orientation to the organization’s electronic mail system through an impromptu tutorial session. Such spontaneous training episodes may communicate only the most rudimentary knowledge and skills, but they do so in the same setting in which those skills will be practiced (i.e., at a specific office computer). They may also initiate interpersonal relationships that can support future instruction and problem solving.

In contrast, incidental learning is unintentional, a by-product of another activity. Often learners are not aware that they are constructing knowledge during these incidents. Through force of repetition or observation, they can absorb ideas about computers that they might not be able to verbalize unless encouraged to reflect on their attitudes and actions. Incidental computer skill learning includes learning through errors or problem-solving episodes. For example, in the process of producing an annual report, a computer user may teach herself how to add bullets to text or how to create a chart from a spreadsheet, even though she began the task with no explicit intention of learning these skills. Computer users seem to "pick up" a variety of skills in this way, often as the result of situations that place new demands on their knowledge of computers and software.

Incidental learning also includes the assumptions, beliefs, and attributions about computers that people unintentionally communicate to one another. For example, by listening to conversations and observing the behavior of colleagues, computer novices may come to believe that having a particular type of personal computer is a sign of social status; that women, minority members, or older people cannot learn computer skills as readily as stereotypical "white guys in ties"; or that all computer experts use technical jargon to conceal their own lack of understanding and to control less knowledgeable users. As these examples show, incidental learning can be fraught with errors; however, whether or not they are valid, such concepts are easily communicated in social interactions and are likely to influence the learner’s subsequent motivation and behavior.

Incidental learning episodes, over an extended period of time, appear to constitute a socialization process through which people construct personal identities as computer users. In addition to learning how to operate equipment and software, becoming a computer user involves learning to see oneself in certain relationships to computers, other users, and organizational environments. One goal of computer skill learning is adaptation to experiences within a community of practice:

Categories like "novice," "user," and "expert" are more valuable as indexes of social identity than as measurements of skill. Little research has been done on how people construct identities as computer users in response to participation in work practices. If theories of situated learning are accurate, a longitudinal study might find evidence of ongoing changes in perceptions, beliefs, attitudes, and goals during the course of new users’ adaptation to the requirements of computer-based work. Brown and Duguid (1992) discuss the related issue of the difficulties experts can face in acknowledging their need to resume the role of novice in response to changes in technology.

One side effect of the introduction of personal computers in workplaces may be a reduction of status barriers between novices and experts. Brown and Duguid (1992) suggest that

To summarize, theories of situated learning and of informal and incidental learning appear to be consistent with many of the findings of experimental, survey-based, and ethnographic research on computer skill learning. This body of research identifies several variables as critical factors in the development of workplace computer skills:

• Practice effects. The factors that best predict the quality of skill performance are the recency and duration of prior performance. Skills that are constantly rehearsed tend to become automatic and error-free.

• Self-direction. Even when presented with structured training materials, adults learning new computer skills tend to be self-directed in their attempts to apply the skills to work-related problems immediately.

• Specific transfer via mental models. The success of such self-directed learning efforts appears to depend heavily on the transfer of specific knowledge from prior experience with similar systems. Successful transfer can occur when the learner already possesses a mental model that is strongly analogous to the new situation.

• Limited general transfer. Transfer of general, verbal knowledge (such as a lecture or a computer manual) to practical tasks tends to be poor.

• Preference for informal learning. Adults rely heavily on informal interactions with other members of their workgroups for the development of computer skills.

• Socialization. In addition to mastering operations and procedures, adult learners experience a socialization process through which they develop new identities in relation to computers and their organizational setting.

In the following chapter, this conceptual framework provides the basis for the design of an interview-based study exploring how computer users interpret their learning experiences and how interactions with their workgroups and organizations influence their learning.

CHAPTER III

Introduction

The purpose of this study, as outlined in Chapter I, was to examine how adult learners develop personal computer skills in the context of workplace activities, in order to understand how educators, colleagues, and organizations can facilitate this learning. Chapter II discussed potentially valuable constructs from prior research and identified methodological difficulties that limit the applicability of earlier empirical studies to educational practice. One conclusion drawn from the review of the literature was that computer skill learning is studied more appropriately within contexts of organizational behavior than under artificially-controlled conditions. These findings about computer skills were shown to be consistent with theories of situated learning and informal and incidental learning, which provide a conceptual framework for this study.

This chapter describes the methodology and procedures used to address the following research questions:

Design of the Study

This research used interview transcripts and on-site observations as data sources for a comparative case study of computer users in three organizations. This section discusses the rationale for applying a qualitative case study design to the research questions.

Traditionally, as their name suggests, computers have been associated with quantitative methods, so it is not surprising that many studies of computer skill learning have relied on techniques such as statistical analysis of computer-recorded keystroke data (e.g., Card, Moran, & Newell, 1983), expert systems programmed to simulate human learning behaviors (e.g., Anderson, 1989), and quasi-experimental comparisons of instructional treatments (e.g., Czaja et al., 1986 & 1989). These methods have been effective in testing hypotheses about well-defined problems, such as the relationship between duration of practice and efficiency of performance. However, they are ill-suited to the discovery of new concepts or theories or to the study of subjective states and processes such as goals, intentions, understandings, attitudes, beliefs, or emotions. Educational research problems centering on discovery or on subjective states lend themselves more readily to qualitative approaches such as interviewing, observation, and document analysis (Bogdan & Biklen, 1992; Merriam, 1991).

Some of the most influential research on computer skill learning has employed verbal protocol analysis, a quasi-experimental design in which participants are encouraged to think aloud while performing computer tasks (e.g., Carroll, 1990). This method has been used with considerable success to collect verbal data about routine word processing activities (Santhanam & Wiedenbeck, 1993) and adaptation to unfamiliar systems (Briggs, 1991). While these experiments demonstrate the value of verbal data for the study of computer skill learning, their generalizability is limited by their laboratory settings. Given evidence that most skill learning is situation-specific (e.g., Singley & Anderson, 1989; Chaiklin & Lave, 1993), findings based on laboratory protocols cannot be assumed to apply directly to the day-to-day experiences of computer users in offices and other work settings. Therefore, this study employed in-depth interviews, conducted at the participants’ places of work, to elicit contextually-appropriate accounts of practical learning.

Talking to people is perhaps the most obvious means of learning about their perceptions and understandings. Discourse between speakers has a methodological face validity because each of us relies on it daily to understand and predict the behavior of others. As a formal research technique, however, interviewing requires explicit decisions about procedures for sampling, collecting and analyzing data, and assessing validity.

The interviewing strategies used in this study were influenced by psychological research on the use of narratives and explanations in discourse (e.g., Antaki, 1988; Edwards & Potter, 1992; Gergen, 1988; Potter & Wetherell, 1987; Mishler, 1986a and 1986b). These strategies contrast with survey-style interview methods that emphasize problems of standardization: "how to ask all respondents the same question and how to analyze their responses with standardized coding systems" (Mishler, 1986a, p. 233). Survey-style interviewing tends to suppress narrative and explanatory ‘digressions’ in order to produce a homogenous body of data that can be subjected to statistical manipulation.

Discourse-analytic methods reflect a more phenomenological view. Rather than attempting to produce a general, ‘objective’ account based on aggregations of standardized responses, such strategies emphasize that any discourse between speakers acts to construct a negotiated social reality (Edwards & Potter, 1992). This view of interviewing is consistent with the theoretical perspectives of situated learning and informal and incidental learning, which emphasize the importance of interpersonal relationships in the creation and exchange of knowledge.

In a discussion of research on information systems, Boland (1985) argues that phenomenological or hermeneutic methods can produce more useful data than quantitative approaches because interpretation is the defining activity of computer deployment and use:

A primary concern of this study was the influence of workplace relationships and other organizational factors on individual skill learning. Relevant interview data could be provided only by computer users working together within an organization. To support generalizations across organizational types, it was necessary to collect such data within several organizations of differing missions, sizes, and computer resources. Thus, while the central problem of the study was to clarify how individuals learn computer skills, the research was structured as a comparative case study of three organizations. This design allowed within-case analyses of individual skill learning at each organization as well as a cross-case analysis that develops a general interpretation of computer skill learning.

An additional rationale for an interview-based design is its value as a contribution to the knowledge base. A review of the literature discovered only one similar research design, a study of first-time adult computer users based on phenomenological interviews (Howard, 1994). Howard’s study, while it moves too hastily from the interpretation of empirical data to philosophical speculation, is a useful demonstration of the value of this under-utilized approach. By presenting and analyzing additional interview data about learning in organizational settings, the present study may facilitate efforts to synthesize prior findings and support computer training practice.

Population and Sampling

The most basic decision in an interview-based study is the selection of participants (Johnson, 1990). In qualitative research, this process has different goals than the probabilistic sampling methods employed in quantitative research:

Accordingly, informants are chosen on the basis of their "theoretical qualifications ... in terms of such things as status, role, position, expertise, category or subgroup membership, dimensions, and even knowledge" (Johnson, 1990, p. 38).

The population of interest in this study includes adults who use personal computers routinely in their work but who are not academically trained computer professionals. ‘Routinely in their work’ in this context means that a user’s computer tasks are recurrent and necessary to achieve basic functions of the user’s job. Individuals who have received or are pursuing degrees in computer-specific disciplines (e.g., computer science, electrical engineering, management information systems, instructional technology) were excluded on the grounds that such people’s experiences are not representative of the majority of personal computer users in the workforce. The selection of participants was intended to include a sufficiently broad range of individuals, organizational types, and computer installations to warrant generalizations about this population.

To collect data about diverse organizational situations, the sample had to include both public- and private-sector organizations of varying sizes and computer resources. My work in computer training at the University of Georgia Center for Continuing Education helped me make initial contacts and establish the credibility of the research. Three organizations agreed to participate in the study: a non-teaching department of the university; a privately-owned hospital; and the corporate office for a chain of regional newspapers.

In the case of the university department, access was facilitated by my previous contacts with the staff as advisor to a student sports club. I sent an invitational letter (Appendix 1) to ‘Mel Daniels,’ the facilities manager for ‘Leisure Activities,’ who identified other potential participants during a follow-up telephone conversation. ‘Elizabeth Burton,’ a secretary at ‘County Hospital,’ received the same letter and then identified two other interview participants when we talked on the telephone. Elizabeth was familiar with my department at the Georgia Center through her informal activities as a coordinator of computer workshops for hospital staff; however, I had no direct participation in this training nor any contact with the interview participants at the hospital prior to this study. Access to ‘Regional Publishing, Inc.’ was facilitated by my department head, Dr. Helen Mills, through her membership in a civic group with the president of that organization. The president identified ‘John Gilliam,’ RPI’s controller and computer systems administrator, as an appropriate contact person. Again, the invitational letter was followed by a phone conversation in which John and I discussed the selection of other interview participants.

In both the letter and the telephone contacts, I described the research problem and emphasized my desire to talk to computer users who held different positions within the organization, who represented various levels of computer experience, and who had opportunities to interact with one another in the course of their computer work. I worked with each contact person to select potential participants who met these criteria and who could make themselves available for a 30-60 minute interview.

At Leisure Activities, I interviewed four of the department’s six staff members (as a result of audiotaping problems, only three of these interviews provided transcript data). At RPI, I interviewed four people out of a staff of nine. The hospital’s department of ‘Outpatient Therapy’ has a staff of about 40 people, most of whom do not use computers. I interviewed three computer users in that department and two other hospital employees: a secretary in another department who had once been a temporary clerical worker in Outpatient Therapy, and the director of internal auditing. In all three cases, I interviewed about half of the computer users in each workgroup, including managers, professionals, and support staff. A total of 12 people of different job requirements, educational backgrounds, ages, and genders participated in the interviews. Participants ranged in computer skill from near-novices to an experienced network administrator. Background data about the participants are presented in Tables 2, 3, and 4 of Chapter IV.

In the cases of Leisure Activities and Outpatient Therapy, the first round of interviews was followed by a second set of additional interviews. Discussions with members of the advisory committee early in the data collection process made clear the need to ensure that all the cases paralleled each other in terms of the number of individuals interviewed and the representation of different organizational positions (i.e., support staff, professionals, and supervisors). In the case of one organization (the hospital) individuals outside the department who had relevant information were also interviewed. These second rounds of interviews reinforced the parallelism of the cases and also allowed further observations of the workplace environments. A second round of interviews at RPI was unnecessary, since these criteria were satisfied in the first set of interviews.

Personal computers used in these organizations included networked and non-networked DOS, Windows, and Macintosh computers running a variety of standard word processing, spreadsheet, database, and desktop-publishing applications. Currently these are the personal computers and types of applications most widely used in the United States.

Data Collection

Interviews were conducted on-site over a four-month period. All but two were conducted in participants’ offices or work areas so that they had access to their computers during the interviews and so that I could observe their work environments. In the other two interviews, another room in the department was used for greater privacy, but I was still able to observe the participants’ work areas.

At the beginning of each interview, participants were asked to sign a consent form approved by the University’s Institutional Research Board. This form described procedures for protecting the anonymity of their responses. Participants were advised that they could terminate the interviews at any time or withdraw their interviews from the study at a later date. They also received instructions on how to contact me for further information or copies of the findings.

The interviews included two stages. First I filled out a survey-style data sheet (Appendix 2), collecting basic information about the participant and the organization. The second stage was an in-depth, audiotaped interview lasting 30-90 minutes, using a simple interview guide to elicit stories, explanations, and statements about experiences of computer skill learning.

The interview guide (Figure 1) served primarily as a memory aid. The questions were derived from a pilot study, from informal conversations with many computer users, from the research questions for this study, and from recommendations by the advisory committee. Participants were invited to talk about events that they perceived as important in their computer skill learning, about their strategies for coping with computer problems, and about the positive and negative effects of their organizational settings on their learning. The structure of the interview guide did not determine the content or sequence of all questions and responses during the interviews. Alternative lines of questioning were explored if potentially relevant issues surfaced. For example, in the case of County Hospital, participants’ comments about the MIS department led to extensive discussion about user-support issues not anticipated in the interview guide. Throughout the interviews, I avoided the use of jargon or other language that might direct responses and used restatement and rephrased questions to prompt for elaboration and to confirm understandings (Merriam, 1991).

As soon as possible after each round, the interviews were transcribed by me or by an assistant. I reviewed printed transcripts and checked them against the audiotapes to verify or correct questionable readings. Pseudonyms were substituted for personal and organizational names throughout the transcripts, and some other references that might allow identification of individuals were also edited. The 12 resulting text files (totaling about 42,000 words) were the core data for the study.

Observations conducted on-site at the workplaces provided an additional data source to triangulate interview data. The form in Figure 2 was used to record observations after each site visit. These notes served as memory prompts while writing the "thick" descriptive passages prefacing each of the three case analyses in Chapter IV (cf. Geertz, 1973).

A walk-through tour of each organization early in the interview process revealed material details of office design, distribution of computer resources, and patterns of computer activity. By interviewing most participants at their desks, it was also possible to observe details of their personal work environments. Several participants responded to questions by using their computers to demonstrate or display the software and files being discussed. Such observations provided useful validity checks for participants’ statements about their skills and attitudes.

How are personal computers used in the organization?

Who was using computers during the visit?

Describe any incidents of computer use that involved more than one person.

Describe the overall computer installation of the site.

Describe the participant’s work space and computer system.

Describe any use of the computer during the interview.

Describe any reference materials in the work area.

Describe any characteristics of the participant that influence computer use (e.g., a disability).

Data Analysis

Unlike quantitative methods, procedures for the analysis of qualitative data cannot be completely specified prior to data collection, since the form of the data is unpredictable. As a result, qualitative studies do not usually meet one of the most common standards of research reliability: the ability to be replicated. However, advocates of qualitative methodologies contend that much quantitative research emphasizes reliability at the cost of construct validity, resulting in the production of elegantly-tested findings that have little or no practical relevance (Edwards & Potter, 1992; Mishler, 1986b; Potter & Wetherell, 1987). One of the primary goals of this and other qualitative studies is to achieve valid results by using methods that respect the socially constructive nature of discourse and practice.

Traditional standards of scientific inquiry and scholarly publication require that the processes and findings of research be presented in such a way that an informed audience can judge its value. For the qualitative researcher, these standards impose an obligation to document as clearly as possible how data were collected and analyzed and how specific interpretations are warranted (Kirk & Miller, 1986). This section identifies presuppositions that shaped the research and its findings, outlines the procedures used to carry out within-case and cross-case analyses, and describes the measures taken to assess the validity of the findings.

In an interview, both the researcher and the participant contribute to the construction of meaning. In spite of all efforts at objectivity, the data collected can be heavily influenced by the questions asked and by the participant’s perception of the researcher’s motives and expectations in asking those questions (Mishler, 1986b). Thus the agenda and concepts that guided the research effort must be stated explicitly, so that readers of the study can assess their possible influence on what data was collected and how it was analyzed.

Chapter I describes the context of the research problem, states the purpose of the study, and defines several critical concepts: ‘personal computer,’ ‘applications,’ ‘novice,’ ‘experienced user,’ and ‘computer skill.’ These premises and concepts were accepted as given. The questions in the interview guide (Figure 1) reflect the assumption that certain events and experiences are central to computer skill learning, e.g., ‘getting started,’ ‘coping with problems,’ and ‘learning within the organization.’ The phrasing of these questions presupposed that participants would tend to describe their computer experiences in the form of stories and explanations. Just such stories and explanations comprise the bulk of the data.

The initial stages of data analysis were concurrent with data collection. As interviews at each organization were completed, the tapes were transcribed and the printed data read repeatedly and annotated. A tentative analysis of each case was made before conducting interviews in the next organization, which allowed emerging themes to be tested across the cases.

The first set of interviews, conducted at the university’s Leisure Activities department, provided an opportunity to test analytic strategies and to receive feedback from two members of the advisory committee. Following the strategy proposed in the prospectus for this study, excerpts from the interviews were analyzed in terms of structuralist theories of narrative (Barthes, 1982; Chatman, 1978; Ducrot & Todorov, 1979). The analysis described each excerpt’s internal structure (how narrative elements such as characters, actions, happenings, and settings were combined and organized) and pragmatic function (how the narrative expressed the narrator’s beliefs, attributions, goals, and intentions). Discussions of this analysis with the advisory committee members produced a list of common themes that was useful in analyzing data from the other cases.

This initial effort persuaded me that structuralist analysis would not be applicable for the data in this study. Designed for the detailed explication of dense, written narratives, these methods cannot be imposed on the looser structure of speech without distorting the data. While structuralist procedures were useful in identifying passages of talk as narrative or explanatory units, I decided to concentrate on the identification of recurring themes, concepts, and experiences by making constant comparisons between and within the interview texts (Dey, 1993; Glaser & Strauss, 1967).

After completing and transcribing interviews for the second case, County Hospital, new themes were identified and others were modified. Some of the categories of learning experience described by the Leisure Activities participants also applied to the data for the second case. The desire to see if these categories would recur in a smaller, more profit-driven organization led to the selection of Regional Publishing, Inc., as the last of the three cases.

With all 12 transcripts in hand, the final within-case and cross-case analyses were prepared on a Macintosh computer using the applications Microsoft Word and FileMaker Pro. The within-case analyses were conducted in the same sequence as the original site visits. For each case, the transcripts were reviewed and selected excerpts from the interviews were copied from the Word text files into FileMaker Pro database records. Each database record included fields containing the following information: a code that identified each record; the participant’s name; a category; researcher comments; and the text of the excerpt. Figure 3 shows the database record for an excerpt from one of the County Hospital interviews.

Alexandra

Becoming a Novice

Alexandra was thrown into computer use when she started a previous job. None of the staff received any formal training or support. "As we needed it, we'd try to figure out how to use it."

I took a job as an administrative assistant and they sat me down in front of it and they said, "Here is your computer." I didn't even know how to turn it on. I was very lucky to be hired for the job. Basically, you know, someone showed me how to get around and then I took it from there. Sat with the books and pretty much taught myself -- used help a lot.

As each record was entered into the database, it was assigned to a category. The category descriptors were phrases that served to link records about related forms of experience. Throughout the within-case and cross-case analyses, the list of categories was iteratively reviewed and revised in order to create new categories only when necessary to accommodate the data and to combine related categories whenever their contents could be subsumed under a more inclusive classification. The comments field was used to summarize the excerpt and explain its category assignment. These comments provided data for an ongoing audit of the analysis, making it possible to review the evolution of the categories and the reasons for various interpretations.

Once the data for a case were placed in the database, it became possible to find and sort the records by participant or by category. In writing the within-case analyses, Word and FileMaker Pro were used simultaneously, allowing the copying of data into the research report and the ongoing revision of the category list. The Find, Replace, and Index features of FileMaker Pro simplified the process of modifying category descriptors and redistributing records among the categories.

After the within-case analyses were completed, the database contained a total of 113 records. The first step in the cross-case analysis was to create a list of the category descriptors in Microsoft Word. The Search feature of FileMaker Pro was used to determine how many records had been assigned to each category, and this information was used to sort the list of descriptors according to the frequency of records in each category. This reordering helped to focus attention on categories that contained only one or two records. These categories were subsumed into more inclusive categories, the descriptors of which were revised to reflect these additions. At this point, the database records were grouped into 19 categories.

Using the Cut and Paste features of Word, the list of category descriptors was rearranged several times to group together related forms of experience. This list was compared to the three research questions and sorted again according to different social dimensions of computer skill learning (i.e., as an individual experience, as an interpersonal experience within workgroups, and as a corporate experience in organizations). This list was used as an outline to write a draft of the interpretation of computer skill learning presented as the final section of Chapter IV. Discussions with members of the advisory committee led to further clarifications, revisions, and reorganizations of the cross-case analysis.

This study explored how adults experience computer skill learning and how their experiences are influenced by workplace relationships and other organizational factors, relying on verbal and observational data. The validity of such a study is inherently problematic, since it is an interpretation of subjective and intersubjective experiences that are by nature difficult to measure and replicate. The credibility of the study depends on the adequacy with which the design and presentation of the research address questions such as the following:

All of the participants appeared to be open, candid, and thoughtful in their comments. However, the research situation is likely to have influenced what they said. Inevitably, the process of gaining access to volunteers involved a degree of self-selection that may have biased responses. The participants’ attitudes about computer skill learning and the degree of trust and confidence they felt during the interviews also influenced the information they provided (Jones, 1985). The accuracy of interview statements depends on the extent to which participants tended to distort past events, echo received opinions, or conceal limitations of their knowledge.

The research methods provided three means of assessing the claims of interview participants. First, I relied on restatement, requests for elaboration, hypothetical questions, and silence to encourage participants to clarify their statements. These tactics provided ample opportunity to confirm my understanding of participants’ intended meanings. Second, at least three members of each workgroup were interviewed separately, providing multiple perspectives on individuals, relationships, and shared experiences. Third, observations provided data about individual behavior, interactions between people, the material environment, and other aspects of each workplace situation.

The validity of the transcription process was strengthened by transcribing all but three of the interviews myself shortly after recording them. I corrected the other interview transcripts (prepared by an assistant) while listening to the tapes. Throughout data analysis, the recordings were consulted whenever necessary to check the accuracy of transcriptions, and the transcripts were revised when necessary.

The validity of the research findings as an interpretation of the transcript and observational data is supported by the triangulation of multiple data sources. A high level of triangulation is the greatest advantage of the comparative case study design. Each interview participant told me how he or she had learned to use computers, and comparisons of their personal experiences revealed common features. Each subsequent interview provided opportunities to test and revise my understanding of the similarities between and differences among the previous interviews. In the same way, the three organizational cases triangulated one another. Cross-case comparisons and contrasts helped to indicate the extent to which each workplace shaped the learning experiences of the people there.

Critiques by members of the advisory committee raised important questions about my interpretations and encouraged me to reflect on and modify their organization and presentation. Participants in the study were also given an opportunity to react to the findings. During the revision of the research report, I prepared a brief summary of the cross-case analysis (Appendix 3) and mailed it to the 12 interview participants along with letters thanking them for their help and encouraging them to telephone me to share any thoughts about the results of the study. Follow-up conversations with some of the participants indicated that they felt the findings to be consistent with their experiences. These discussions did not explore specific categories in detail, but they did tend to confirm the overall findings and provided useful data about developments in the organizations that had occurred since the interviews.

In the end, each reader must make his or her own judgment about the validity of the study. Transcript data are presented throughout the case study analyses, so that the argument is advanced as much as possible in the words of the interview participants themselves. The description of analytic procedures provided in this chapter is intended to allow a reader to trace the development of the analysis and to evaluate the logical relationship between the experiences described by the interview participants and the general categories I synthesized from them.

Potter and Wetherell (1987) outline several validity criteria for analyses of discourse that readers may wish to apply to this study. An obvious one is coherence. How well does the analysis account for the data? How does it compare to alternative accounts? Another criterion is the ability of the analysis to generate new explanations and to account for phenomena beyond the scope of the study. Ongoing discussion with other researchers is important in testing the validity of this study and in raising new questions for related research.

Strengths and Limitations

Computer skill learning is a complex subject that has attracted researchers in a variety of fields. It has been approached as a form of cognitive processing, an objective for training, a problem in personnel management, a requirement for computer system design, and an expression of organizational culture. Each of these perspectives lends interest and value to this study.

However, the scope of the present research is deliberately narrow, focusing on current hardware and software as they are used by adults in organizational settings. The rapid advance of computer systems will turn this study into a historical curiosity in a few years as technologies like digital video, internetworking, handheld computing, speech and handwriting recognition, intelligent software agents, and virtual reality transform what it means to learn to use a computer. At the same time, the framing of the problem in terms of workplace experiences excludes some forms of computer skill learning that may be highly significant in other areas of human experience. For example, the use of computers at home for entertainment, communication, and education has been ignored. So has the computer skill learning of children, although this learning differs from the experiences of adults in ways that invite future research.

This study draws on a variety of personal experiences: my own computer skill learning; my practice as an adult educator working in computer training; my doctoral studies; and my activities in software design and development. As Chapter II indicates, my thinking and expectations about this topic draw heavily on prior research and theory. While I do not believe it possible to approach any problem as a tabula rasa, it should be acknowledged that my preconceptions have influenced my interpretation of the data provided by participants in the study. My reactions to the data were also shaped by feelings of identification with and empathy for the interview participants. For example, I felt a strong sympathy for the workers at County Hospital who described their struggles to learn computer skills in an unsupportive environment. Their accounts of the indifference and incompetence of the hospital’s computer support professionals surprised and sometimes angered me. This emotional response forced me to scrutinize the data about these organizational conflicts with great care and to conduct additional interviews to assess the accuracy of these reports.

The methods of this study were determined by the research problem. The advantages of interview transcripts and observations as sources of valid data about computer skill learning seem to me to far outweigh the reliability of quantitative methods. Like any other methods, however, interviewing and observation confer no monopoly on truth or objectivity. Many alternative designs are possible, both quantitative and qualitative, that might produce more or better data about the experience of learning to work with a personal computer. Clearly, some aspects of this experience can never be described adequately on the basis of interview data, because they could not be verbalized accurately by computer users–for example, their mental models of computer systems, the processes by which they develop motor and pattern-recognition skills, the influence of computer learning on their values and beliefs, or the relative degrees of transfer between different training methods and work tasks. Some of these possibilities for further research are discussed in Chapter V.

My ambitions for this study were circumscribed by the limitations of its methods. I have attempted only to produce an analysis that is consistent with the data and that can support the practice of computer skill learning and teaching in organizations.

CHAPTER IV

The selection of participants in this study was designed to include a range of organizational types, computer systems, and individuals, with the goal of examining how adults learn computer skills in the context of workplace activities. In trying to develop an analysis sufficiently general to guide educational practice in diverse settings, it was necessary to include both public- and private-sector organizations of varying sizes and computer resources and to interview individuals of different skill levels, job requirements, educational backgrounds, ages, and genders. To support comparisons between the organizations and to collect data about informal and incidental learning, it was necessary to conduct interviews with groups of individuals working together in departments of similar sizes.

Three organizations participated in the study: a non-teaching department at a state university; a privately-owned hospital; and the corporate office for a chain of regional newspapers (see Table 1). As detailed in Chapter III, participants in each case were selected through a telephone conversation with a contact person during which the research goals and sampling criteria were discussed and persons were identified who met the criteria and who were available for interviews. About half the personal computer users in each department or workgroup were interviewed. A total of 12 people participated in the interviews, ranging in skill from near-novices to experienced network administrators and including managers, professionals, and support staff. In each organization, interview participants were co-workers who could discuss shared experiences. Throughout, pseudonyms are used for all personal and organizational names. Personal computers in these organizations included networked and non-networked DOS, Windows, and Macintosh systems running a variety of standard word processing, spreadsheet, database, and desktop-publishing applications.

The first three sections of this chapter draw on observational and interview data to provide a snapshot of the activities, facilities, personnel, and culture of each organizational case and to describe the individual participants. The fourth section is a cross-case analysis, using excerpts from all 12 interviews to show how the computer experiences of the participants exemplify general categories of individual, workgroup, and organizational learning.

Case 1: Leisure Activities Department

The Department of Leisure Activities manages facilities and programs for student sports and recreational clubs at a large state university. The department is housed in a suite of recently-renovated offices in Miller Hall, an elegant but dilapidated building in the middle of the campus. The suite is comfortable and well-lit, if somewhat cluttered with sports equipment and office furniture. Exposed brick walls and potted plants help create a relaxed atmosphere. Of the six full-time staff, some have private offices, while others share an open reception area. Casually-dressed staff and students move through the suite constantly, and all the office doors are open; there is considerable activity, but little evidence of stress or tension. Sometime next year the department will relocate to the Leisure Center, a huge state-of-the-art sports complex currently under construction.

The department uses 14 networked Macintosh computers, primarily for desktop publishing of flyers and signs, word processing, and budget management. These computers range from old black-and-white Mac Plus and SE models to new Quadras. One older IBM system sat on a table, disconnected. Most of the computer use I observed was by student workers, though all interview participants had computers on their desks.

Because of my work as advisor to a sports club, I have had several opportunities to observe the office setting and interact with the staff. Most knew me at the time of the interviews and seemed comfortable talking to me. Table 2 summarizes background information about the three participants.

Mel Daniels, the facility coordinator, oversees the scheduling, maintenance, and staffing of the gyms, pools, and intramural fields. His comfortable office has a window and an array of cellular phones. During the interview, Mel played with a golf putter and gestured with it to emphasize some points. He was self-deprecating about his computer skills, which are limited to basic word processing and desktop publishing. His brand-new Macintosh Quadra sat under a heavy plastic dust-cover.

Mel’s attitude about the information processing required by his work is one of humorous resignation:

Anne Boole, an accounting assistant, has a work area at the back of the department’s open entry area, behind the receptionist’s desk. Both of her computers were running: a new Quadra and a Mac Classic used for e-mail and older database software that won’t work on the Quadra. Anne is a proficient user of Word, PageMaker, and other applications. Her interview was hindered slightly by occasional interruptions as other staff members asked her questions. At one point she stopped to help a university inventory-control person locate certain new computers for bar-coding. Anne spoke confidently and with evident enjoyment about her role as the department’s informal computer expert.

Beth Kirk’s office is next to Mel’s and is identical in design. Her Quadra was running a popular screen-saver program showing animated fish. In my previous contacts with Beth I had observed her efficiency and humor in running meetings of student sports clubs. Unlike Mel and Beth, her descriptions of her computer experiences were vague, possibly because she is still in the early stages of skill development and relies on assistance from others in the workgroup for much of her computer work.

Computers are important in the daily routine of Leisure Activities, but their use is limited to fairly simple word processing and desktop publishing. The department’s local-area network is used only for printing and occasional file-sharing, with no connectivity to the campus-wide network. After initial delays in acquiring computers, the department now enjoys excellent resources and support. Hardware installation and configuration are provided by the university’s computer services group, who have worked effectively with Leisure Activities since the department acquired its first computer in 1988. The department’s exclusive use of the Macintosh appears to have simplified learning–all the interviewees praised the Mac’s ease of use–but it may also have insulated the staff from learning more than the basic operations required by their jobs.

Case 2: Outpatient Therapy Department

County Hospital is the largest of three hospitals serving a small Southern city. A for-profit enterprise, it employs some 1,500 people and provides a comprehensive range of in- and outpatient health care services. The hospital is one of the largest buildings in the city; its surrounding complex of parking decks, office buildings, and treatment centers covers several blocks and is the site of constant construction. Inside, the corridors and reception areas bustle with tense-looking staff, relatives, and patients. The building’s modernistic design and hotel-like decor do not conceal fully the undercurrent of urgency and pain that pervades a busy hospital.

To reach Outpatient Therapy, one must follow signs and take an elevator to the fourth floor. The atmosphere is quieter within the department, where a reception desk and offices separate a small waiting room from the therapists’ work areas. There is little movement around the department except for the occasional passage of a patient or nurse. The all-woman support staff is in conventional office wear–dresses, skirts, discreet jewelry and make-up. Busy at their desks, they shuffle through folders and notebooks and stare at computer monitors, often while talking on the phone. Though Outpatient Therapy employs about 40 people, most of these work in patient care; only the support staff uses personal computers.

My first set of interviews at the hospital made it clear that computer skill development in Outpatient Therapy could only be understood in the larger context of the deployment of personal computers and software throughout the hospital. Liz Burton, the department’s local expert, is a secretary whose frustration with the hospital’s lack of user support has led her to coordinate computer workshops for staff with the local university on a volunteer basis. Her situation is even more unusual in that her unofficial leadership has been recognized and supported by the hospital administration, which at the time of the interviews had just created a new position to compensate her for her training-related work.

To collect data about Liz’s role in training other computer users in her department and throughout the hospital, I interviewed Liz, a former co-worker, and the hospital’s director of internal auditing, then made a second visit to interview Liz’s supervisor and another co-worker who shares an office with her. These interviews yielded information about the participants’ individual experiences as well as the organizational factors that shape computer skill development throughout the hospital. Table 3 summarizes background information about the five interview participants.

Liz Burton shares a small office with Samantha Newhart, occupying a corner crowded with filing cabinets and an IBM computer. A thin, intense woman, she takes fierce pride in her role as a local computer expert. Her eyes showed some of the strain of routine 60-hour work weeks. In addition to the secretarial and transcription work of her Outpatient Therapy job, for the last year she has scheduled and coordinated computer workshops for staff throughout the hospital, a self-imposed task that grew out of her participation in an unofficial computer users group. At the time of the interview, the hospital had just recognized her efforts by creating an additional half-time position so that her training work could be compensated out of the MIS departmental budget.

This arrangement is ironic, since Liz’s relationship with MIS has been bitterly adversarial. Questions about her own computer experiences inevitably led her to describe problems with MIS that have impeded computer skill development throughout the hospital. Data from the other hospital interviews and from observations tended to confirm that hospital staff work in a ‘user-hostile’ computer environment, their learning obstructed by a lack of communication about hardware and software upgrades, incompatible versions of applications, hard-to-use system configurations, and little or no training.

In spite of these problems, Liz sees the situation at the hospital as improving. After a year of unpaid work, the establishment of her official post as training coordinator has given her additional authority to coerce managers into releasing staff for training and to ensure that staff meet the skill prerequisites for the workshops they attend. The installation of a hospital-wide local area network (LAN) appears to be driving the administration’s current commitment to computer training. Liz realizes that she has gotten herself into much more work than she anticipated:

Samantha Newhart, who shares an office with Liz, is a relatively new employee, having worked at the hospital about six months at the time of her interview. Most of her work hours are spent transcribing the therapists’ progress notes. She began her career as a transcriptionist working on typewriters: "We did everything in duplicates, and you scraped–if you had a carbon, you had to scrape it with a razor." Later she operated a Lanier dedicated word processor, then switched to a personal computer and WordPerfect, which she much prefers: "The personal computer to me is much easier, and it’s a lot freer, you can do a lot more with it," especially in terms of copying and moving text between documents and managing file storage efficiently.

Samantha and Liz rely heavily on each other for WordPerfect support:

Samantha is the only clerical worker among all the interview subjects who owns a home computer, which she uses sometimes as a resource for learning to solve problems encountered at work:

Like Samantha, Alexandra Hugo is still adjusting to the organizational culture of County Hospital. Employed as a secretary in a different department for about a year, Alexandra described her most positive experience in learning computer skills as "being shown by other people. I think that having a live person is definitely the most important thing." In particular she mentioned Liz Burton, who had supervised her when she first came to the hospital and on whom she had relied for help with computer problems: "I was faking my ability at the time," she said with a laugh.

In spite of this self-deprecation, Alexandra’s computer skills appeared to be broader than those of most of the hospital secretaries. Her lack of confidence about them may be related to her age. At 31, she was the second youngest of all the interview participants, and described experiences typical of her age cohort, which saw the advent of the first personal computers in schools but not their acceptance into academic culture:

Alexandra’s comments tended to confirm the inadequacy of user support at the hospital: "There’s no support network or backup–I mean I think there’s supposed to be, but there really isn’t." However, she has benefited from an informal relationship with one MIS staff member:

Alexandra’s instruction in how to fix her printer was the only example reported in the five hospital interviews of MIS staff tutoring or training a user.

Edie Arness, the office coordinator for Outpatient Therapy, is Liz Burton’s immediate supervisor. Overseeing patient scheduling, records, billing, and telephone support, Edie uses personal computers much less than the secretaries, though she is a frequent user of the hospital’s minicomputer-based staffing system. (This time-logging program, using dumb terminals connected to an IBM AS/400, is not currently accessible through the hospital’s personal computer LANs.)

She is somewhat skeptical about the value of training all of the department’s staff for the transition to the LAN:

Edie was able to confirm details of Liz’s experiences with the users group, and provided additional information about her new half-time position:

Ted Warner, the director of internal auditing, provided more information about the administration’s perspective on computer use at County Hospital. Located in an attractively-renovated house a block away from the main hospital, Ted’s spacious office is well-lit and furnished with handsome carpeting, bookcases, and armchairs. On his large desk is a state-of-the-art personal computer system, including a dockable notebook computer that he can remove to take home or on business trips. Well-dressed but casual, Ted showed a keen interest in and understanding of the evolution of personal computing at the hospital, in which he has played a key role.

His personal status as a ‘power user’ and his close relationship with MIS were evident when our meeting was interrupted by the arrival of an MIS technician to whom Ted loaned his CD-ROM drive. The MIS staffer, a younger man with a loosened tie and rolled-up shirt-sleeves, was planning to use the drive to "play around with" an evaluation copy of Visual Basic, a popular tool for the development of customized Windows applications.

When he accepted the internal audit position at County Hospital in 1983, Ted had an immediate impact on the organization’s personal computing practices.

These fiscal controls marked the beginning of an overall change in computing at the hospital. In 1983, personal computers were not considered an important concern for MIS, and users were forced to rely almost entirely on one another for help and instruction. Ted talked about this cultural shift when asked if he ever provides informal computer support:

Ted was candid in acknowledging that the expanded MIS staff is still not providing adequate support for software users.

Though Ted alleges a lack of staff time, an equally plausible explanation for the weakness of user support is its low priority for MIS and the hospital administration. However, that attitude seems to be changing. As networks spread throughout the organization, it is increasingly evident that the costs of neglecting the learning needs of staff are insupportable:

"Now that we are putting in networks house-wide, you really can’t do it any longer," Ted said. "If you’re going to have 20 or 30 people tied in on a network, they have to know what they are doing."

For now, Ted’s answer is to support Liz in her coordination of workshops, but as Edie implied, this may not be a long-term situation:

Ted Warner’s long-range view and the secretaries’ accounts of their day-to-day experiences combine to create a picture of a large, steeply-hierarchical organization struggling to come to terms with the impact of personal computing. MIS’s failure to support the learning needs of computer users, which could pass for benign neglect in the pioneering days of 1983, has led to a chaotic, stressful situation. To develop the computer skills they need to meet their job requirements, Liz and the "low level people" she champions have been forced to act at the margins of the formal organizational structure through the users group and Liz’s work with the university.

Until recently, Liz saw her actions as inherently in conflict with the agenda of MIS and pursued her training goals with something resembling the passion and paranoia of a rebel leader in a guerrilla war. It is uncertain whether her official recognition marks an evolution of the hospital’s organizational culture, opening the way for greater empowerment of computer users, or whether it is simply an effort to return control of computer training to the beleaguered MIS department.

Case 3: Regional Publishing, Inc.

The corporate headquarters of Regional Publishing, Inc. (RPI) is a modest one-story building in the heart of the downtown business district, a short drive from County Hospital. Inside, the entryway and corridors are thickly carpeted and paneled in dark wood. A visitor waiting for an appointment can entertain himself by studying tropical fish in a backlit aquarium or a plaque proclaiming RPI’s mission, which announces an unswerving commitment to freedom of the press, community service, and the market economy. A glance up and down the corridors reveals serious-looking professionals working in their offices, but also discovers evidence of a recent move: a half-empty conference room furnished with flipcharts, stacked folding chairs, and paper-filled cardboard boxes.

The nine people who work in this quiet office are mostly new employees. As part of a reorganization that involved significant changes in the size and composition of the management team, RPI corporate headquarters was relocated here from another state seven months prior to the date of the interviews. The small group that remains uses a Novell local area network, 486 computers, and a few DOS and Windows applications to direct the financial operations of 35 regional newspapers in three states. Scattered over a forty-county region, these subsidiaries are independently-managed ‘cash cows’ under RPI’s fiscal husbandry, simultaneously the clients of RPI’s accounting services and the sources of its revenue.

At RPI, the only commodity more precious than information is time. The four interviews conducted here were brief, but sufficient to provide a strong contrast to Leisure Activities and County Hospital. In this organization, computer skills are concentrated in the professional rather than the support staff. Table 4 summarizes background information about the interview participants.

Wanda Poe’s work area is behind the reception window at the entrance to the building and is equipped with a IBM-compatible computer, a copier, and a fax machine. As administrative assistant to the president of RPI, the bulk of her work is telephone support and helping to manage the flow of information between the corporate office and the newspapers. Our interview was interrupted briefly when a Federal Express courier delivered an envelope to her; later I learned that each newspaper submits a disk copy of its monthly budget spreadsheet to the corporate office this way.

Though Wanda has been working with personal computers since the early 1980’s, she remains somewhat insecure about her ability to solve computer problems on her own, a situation she attributes to her age.

Eventually, once the turmoil of RPI’s recent move subsides, Wanda hopes to receive additional training, the lack of which she considers the most negative aspect of her current computer work.

Diana Oldham, director of human resource development, was typical of the three young professionals I talked with at RPI: purposeful, conscious of the value of her time, and sufficiently skilled to use four or five different applications in her daily work. Her small but well-appointed office was crowded with bookshelves and filing cabinets, and her tall, leather-covered chair seemed too large for the space behind her desk. An Alpha Four database was visible on the monitor of her 486 computer.

Already a skillful user of WordPerfect and Lotus 1-2-3, Diana is making the transition to Ami Pro and Quattro Pro with the help of her co-workers and software manuals. She expressed confidence about her ability to learn these new applications but also was concerned about the time such learning took away from her work.

Diana’s HRD activities do not include computer training. Any training that occurs at the subsidiary newspapers is organized locally, and there was no indication of any formal computer training procedure for the corporate office.

Next door to Diana, staff accountant Barry Acuff has an almost identical office furnished with glossy new executive furniture and a 486 computer. At the time of the interview he was waiting for a technician from a local computer store to arrive with a replacement for his monitor. Affable and confident, he had some difficulty describing his learning experiences in any detail, giving the impression that computer use is so habitual for him that it requires an effort to recall how he developed his skills.

Like Diana, Barry had been at RPI about half a year at the time of the interview but seemed to be making the transition to the organization’s favored applications more easily. He described using a variety of specialized software to work with financial data. The youngest of the 12 interview subjects, Barry had taken two computer classes in his accounting degree program but had little hands-on experience before entering the workforce. He talked about his pleasure in discovering ways to do his job faster and better, often as the result of "experimenting" with his computer.

The RPI staff’s flexibility and creativity in using their personal computers was a sharp contrast to the attitudes prevalent at County Hospital, where most users appeared to rely on a static set of skills to perform routine tasks. John Gilliam, the controller at RPI, was the best example of the way its business practices and organizational culture support a higher level of computer skill learning.

John’s office is larger than Diana’s or Barry’s, but equally crowded. On the walls, mounted fish and family photographs hint at a life away from RPI. Stacks of papers cover the big desk; on top of some of them sits a notebook computer running Quattro Pro. Behind the desk, a 486 is running a DOS application, and during the interview John occasionally taps its keyboard to feed it a new set of data. Older personal computers litter the room, stacked in the corners like boxes, some with repair work orders taped to their cases.

Of the 12 interview subjects, John had the strongest computer skills and also the most formal computer training. At 33, John is a member of the same age cohort as Alexandra Hugo, and like her just missed the introduction of personal computers into college curricula. His two programming classes required him to prepare FORTRAN and COBOL assignments on punched cards to be processed by machine room technicians. His course in systems analysis was also mainframe-based. Since these three courses did not involve any use of personal computers and did not lead to a degree in a computer-specific discipline, John falls within the sampling criteria for this study. However, it is important to note that his academic computer experiences were more extensive and sophisticated than those of any of the other participants.

The automation of accounting processes at RPI began shortly after John Gilliam accepted a position with the firm.

This ambitious project required John to develop a variety of new computer skills, particularly in the use of Lotus 1-2-3. Eventually, he established a system of spreadsheets that allowed each regional paper’s monthly income statement to be linked directly to the general ledger. The success of this effort encouraged John to take on other projects, learning to use new applications when the old ones had been stretched to their limits:

At RPI, the stakes of computer use are high. Finding more efficient solutions to business problems is not an intellectual exercise, but a corporate imperative. In this bottom-line environment, software can supplant workers. During John’s tenure, RPI has become a leaner and more productive organization, and computer skills have become a condition of employment. The reorganization that preceded RPI’s relocation seemed to have been driven at least in part by concerns about the ability of the old staff to accept ongoing skill development as part of their responsibilities.

Asked to account for the difference between the two groups, John ruled out age as a factor, citing instead "general professional attitude, and ... educational background." The similarities in Diana’s and Barry’s attitudes toward computer skill learning and productivity are not coincidental:

In summary, computer skill learning at RPI is shaped by the organization’s small size, flat structure, and profit orientation. Personal computer applications have become essential to tracking the newspapers’ financial performance, so RPI has stripped away old procedures, employees, and organizational units to reorganize around the information systems developed by John Gilliam. Its new staff understands ongoing computer learning to be a condition of continued employment and consequently is highly motivated to develop new skills and to computerize routine tasks.

The experiences of the people interviewed in all three cases demonstrate that most computer skill learning is driven by the need to adapt to organizational situations. Job requirements, work practices, material resources, relationships with peers and supervisors, information system policies, and organizational culture all appear to influence who learns which computer skills. In themselves, the data from the three cases are neither surprising nor inconsistent with prior research. However, viewed across the cases, these data support new insights about the processes through which people, workgroups, and organizations develop computer skills and about the relationship between organizational situations and personal learning experiences. The final section of this chapter presents a categorical analysis of these processes and relationships.

Cross-Case Analysis

This study examined how adult learners develop personal computer skills in the context of workplace activities, guided by three research questions:

These questions invite analysis of computer skill learning at three levels, as a process that affects the individual, the workgroup, and the organization. Within each of these categories, common properties or characteristics can be identified. By shifting the focus of analysis among the categories, it is possible to view the interview data in new ways and to develop a general interpretation of computer skill learning that can be applied in various contexts. These categories and their associated properties are outlined below in Figure 1.

Separating these three levels is helpful because it allows a detailed analysis of events, processes, and relationships. However, this separation does violence to the situated quality of computer skill learning in the workplace. As the following sections show, personal learning experiences are organized by interactions within workgroups, which are in turn shaped by organizational factors. Following the analyses of the categories, a concluding section reintegrates these levels by comparing the three organizational cases and demonstrating how each organization presented a unique set of constraints and opportunities that shaped its members’ skill development.

In response to the question, "How did you get started using personal computers?", each interview participant described a different series of personal experiences. For every learner, the passage from novice to skillful user is a story of unique problems, opportunities, and accomplishments. However, a pattern of events can be abstracted from these narratives which describes a typical process of individual adaptation to computers within an organizational environment.

This composite ‘getting started’ narrative begins with an organizational situation that calls for the learner’s adaptation to computers and culminates in his or her ability to adapt computers to work requirements. This neat progression from a reactive to a proactive role is not realized in every case. Not all the computer learners interviewed had achieved the same levels of skill. The interview data and other research (e.g., Briggs, 1990; Santhanam & Wiedenbeck, 1993) suggest that many people who work with computers attain a limited set of skills and may never move beyond this plateau. Furthermore, the narrative describes a pattern of events that can be reenacted many times in the history of one person’s computer use as he or she encounters new systems, software, or work requirements. Therefore it should not be viewed as a ‘stage model’ describing an invariant, irreversible process, but rather as a story representative of the way the interview participants experienced computer skill learning. This composite narrative integrates constructs identified elsewhere in the literature, but its unique contribution is to organize these events in a series that helps explain the sequential development of specific skills within the context of workplace activities.

In describing their transformation from novices (working to close the gap between their skills and the requirements of their jobs) into experienced users (able to perform routine computer work with little difficulty), the interview participants tended to talk about experiences corresponding to the following sequence:

None of the interview participants mentioned a purely self-directed initiation into personal computing. Instead, each described a process of adaptation to some social context that either demanded computer skills or presented an opportunity for their development. These social contexts allowed the participants to perceive themselves as computer novices with respect to specific organizational expectations or opportunities.

Of the 12 participants, none was young enough to have worked extensively with personal computers during secondary or post-secondary education (ages ranged from 31 to 49). Only three reported that they had first encountered personal computers in school (Beth Kirk, Edie Arness, and Barry Acuff). In the case of John Gilliam, three college classes using mainframe computers helped develop programming skills that he was able to exploit later when he learned personal computer applications. It should also be noted that, while a few of the participants reported participating in computer training workshops, most regarded these training experiences as marginal to their skill development. Almost all of the interview participants reported having their first consequential encounters with computers in a workplace.

Some participants described learning computer skills while adapting to the requirements of a new job:

Equally common were participants who were forced to adapt when their organizations installed personal computers. In several instances, participants use similar language to convey a lack of involvement in computer decisions made by a faceless "they":

Some people reported a slightly different pattern of adaptation. Rather than being "thrown into" job situations which required the hasty development of skills, these individuals gained access to computers that were under-utilized and used the opportunity to "pick up" computer skills without immediate work pressures:

This experience of exploring available computers out of personal interest rather than in reaction to immediate job demands was evident in most of the participants who were recognized later by their peers and supervisors as local experts.

Almost all the interview participants talked about asking for help from co-workers who were using similar systems. New computer users or users who were learning unfamiliar applications were especially dependent on their co-workers. For some of the participants this style of learning was stressful or humiliating, while others accepted it as normal:

Some participants described their frustration in work environments in which there was no one to whom they could turn with questions.

Asking questions was especially important for new computer users who were trying to adapt as quickly as possible. However, more experienced users also reported relying on asking questions as the fastest and most efficient way to solve common problems:

As discussed below, the efficiency of asking and answering questions appeared to depend on informal negotiations within the workgroups that prevented inequitable demands on the time of more experienced users. Sometimes the information needs of computer novices conflicted with the ability or willingness of co-workers to assist them. For many of the participants, these workgroup conflicts appeared to motivate self-directed learning.

Participants reported a variety of self-directed learning strategies, including trial and error, manual reading, and exploration. Most appeared to agree with Mel, who described self-directed learning as the most critical component of individual skill development:

Mel’s co-worker and computer mentor Anne made an almost identical statement, suggesting an informal consensus within their workgroup about its members’ responsibility to learn independently:

Though a number of the participants commented on the difficulty of reading software manuals, many acknowledged them as a useful (or at any rate unavoidable) resource for self-directed learning:

Often self-directed learning episodes resulted from unexpected tasks or problems that forced the participants to develop new skills or to try to interpret poorly-understood aspects of an application or computer system. Sometimes these experiences were the results of being delegated an unusual task:

Two participants spoke of making mistakes and losing data as traumatic events, still vividly remembered long afterward. These episodes may have forced them to develop a deeper understanding of their computer systems, as seems to have been the case when Beth Kirk realized that an application had crashed because a font had not been installed properly. In other instances, losing files led to specific changes in computer work habits (e.g., Samantha adopted new procedure for making back-ups after a defective disk prevented her from printing a transcript).

While all appeared to accept the necessity of self-directed learning, participants varied widely in their motivation to pursue it. Some seemed to have difficulty imagining circumstances that would lead them to try to learn a new computer skill, while others approached computer use as a continuous process of self-directed learning. One explanation for this might be the different degrees of autonomy and creativity implicit in their job requirements. For example, a transcriptionist at County Hospital could not imagine a need to learn new skills unless the absence of a co-worker required a redistribution of routine tasks:

This attitude contrasts with that of the director of internal auditing for the hospital, for whom self-directed computer learning had become a career strategy:

The obstacles, opportunities, and potential rewards presented by the participants’ organizational positions appeared to account for much of their self-directed learning.

For all the participants who had achieved computer skills beyond the minimal level required by their work, a key experience was learning to use more than one application or computer system. Often this expansion of skills was an unavoidable response to the ongoing upgrades of hardware and software that characterize the personal computer industry. Sometimes this experience involved switching from an old to a new version of the same application:

Somewhat more difficult is switching from one application to another. Even if the programs share many identical functions, the transition can be confusing and time-consuming.

Other participants described such transitions in terms of their awareness of a need to break old habits:

As in the event of becoming a novice, learning a new application or computer system was almost always an adaptation to an organizational situation. While few of the participants at Leisure Activities or County Hospital were making such skill transitions at the time of the interviews, such experiences were common at RPI, where most of the staff were still adjusting to unfamiliar software:

This enforced learning was not always perceived positively because of its effects on workflow and productivity.

However, this resistance was offset to some extent when the learner believed that the new application or system presented significant advantages over the old one:

Where the new application is significantly superior to the old one, users’ response can be enthusiastic even when they are adapting to many unfamiliar features and procedures. For example, users at RPI seem to have shifted easily from WordPerfect 5.1 for DOS to Ami Pro for Windows, even though these two word processing programs have completely different interfaces (i.e., Ami Pro uses a mouse for text selection and the operation of pull-down menus, while in WordPerfect 5.1 the same procedures are performed with function key commands).

Switching from one type of computer hardware to another can be a particularly harrowing change, but it also seems to be a powerful learning experience. For example, the transition from a dedicated word processing system to WordPerfect on a PC gave Samantha an opportunity to appreciate the similarities and differences between the two systems:

Participants who had considerable experience in adapting to new applications or systems showed greater confidence in their ability to learn new skills as necessary in the future. They were able to estimate the effort needed for learning a new application and manage their time accordingly:

For John Gilliam, the most skillful user in the study and the one who had worked with the widest range of hardware and software, the superficial differences between systems were less significant than the underlying logic revealed by their similarities:

Confidence in the ability to master new computer skills and conceptual understanding of principles common to all computer systems were clear signs of a progression beyond the novice stage. A strong sense of self-efficacy and experience with a range of systems and software were common characteristics of all of the participants who were identified as local experts by their workgroups.

For the most skillful participants in this study, the transition from novice to experienced user can be said to have reached a climax when they became more proactive than reactive in their computer use. Rather than learning new skills only in response to external situations, these participants were able to shape their computing environments to fit the requirements of their work, adapting the tools at hand to their own needs and those of their organizations.

Even users who are still close to the novice stage begin to discover more efficient ways to do routine work:

Several participants mentioned such discoveries, which seem to depend on a willingness to ‘play around’ and an awareness of the potential power of applications:

Adapting computer systems to the needs of the workgroup can be a simple process, as when Alexandra created word-processor versions of office forms. It can also be a complex, long-term effort that reshapes an entire organization, as in John Gilliam’s development of the general-ledger and sales-tracking systems for RPI. John’s projects required a high level of skill with specific applications (Lotus 1-2-3 and Alpha Four) and the ability to draw analogies between examples in the manuals and the needs of RPI.

For John, these concepts seemed to have an almost visual quality that allowed him to "see how everything comes together." Browsing through the manual, he studied examples of similar programs and then translated the elements of an actual business situation at RPI (salespeople, clients, transactions, bills) into a set of usable database structures. None of the other participants in the study described comparable applications of abstract reasoning to computer tasks. In this episode, John’s behavior was more like that of a systems analyst than a typical computer user.

However it is expressed, the ability to use the computer to enhance productivity in creative ways indicates a high level of skill. Such a user is now likely to be able to answer questions and solve problems for others in the workgroup, and may be recognized by his or her peers as a local expert.

The process of personal skill development, as described by the interview participants and synthesized in the composite narrative above, does not occur in isolation. At each stage of his or her progression from novice to experienced user, the learner is adapting to situations that arise during day-to-day interactions within a workgroup. This section shifts the focus of analysis from the personal to the interpersonal level to consider some of the workgroup roles, goals, constraints, and behaviors that comprise the context of personal skill development.

In this study, a workgroup is considered to be any group of people within an organization whose job responsibilities involve daily interaction, usually sharing the same physical space and resources. Workgroups may be more or less stratified, but in practice personal relationships within a group tend to be informal. In this study, the departments of Leisure Activities and Outpatient Therapy are workgroups, as is the corporate headquarters of RPI.

All the participants named other members of their workgroups to whom they turned routinely for help with computer tasks. Consistently, participants identified the same individuals as local experts:

In some workgroups, the local expert role is shared by several people, particularly if the distribution of skills and job requirements in the group is fairly homogenous; for example, Barry at RPI, while not as skillful as John, was cited by Diana and Wanda as a resource for problem solving. Ted Warner at County Hospital appears to have acted as a local expert until he became director of internal auditing, which distanced him from daily contact with a peer workgroup.

Certain knowledge critical to job performance can be communicated to novices only by allowing them to work closely with experienced members of the workgroup. New employees depend on situation-specific knowledge to perform even the most basic computer tasks:

While local experts are important in educating novices and solving complex problems, they are not the sole sources of information. Usually expertise is distributed widely through a group, reflecting the distribution of tasks. Potentially, every member of the workgroup is a resource for all the others:

Knowledge sharing within workgroups occurs primarily through solving problems together and through tutoring.

As described above, individuals within the workgroups relied heavily on asking questions to solve problems and develop skills. Asking and answering questions was the most common method by which the participants in this study solved computer problems.

Sometimes asking questions was not appropriate because of the time costs to other members of the workgroup; on the other hand, not asking a question could be equally expensive.

The processes by which the workgroups managed these conflicts are discussed in more detail below.

Answering questions face-to-face or on the telephone is the most common means of solving immediate problems, but the exchange of printed material is also important.

Distributing these printed resources to all the members of the workgroup saves time by providing an alternative to interrupting another member’s work with a question.

One-on-one tutoring by a local expert is a particularly valuable but time-intensive activity that usually occurs only when a new member joins the workgroup or when tasks are reassigned within the group. A typical tutoring episode involves the local expert and the trainee working together at the computer which will be used for the target task:

Either explicitly or implicitly, the members of the workgroups negotiated informal rules for sharing computer knowledge and work. These rules tended to encourage novices to try to enhance their skills by solving problems on their own before turning to a co-worker for assistance. For example, Leisure Activities was forced to re-examine Anne’s role when other members of the department received their own computers:

The workgroups responded to these conflicts of interests in various ways, depending on the weight they gave to differences in status and authority. Participants in groups that emphasized values of "teamwork" and "collegiality" (such as Leisure Activities) seem to grant local experts considerable authority to encourage or coerce colleagues to take responsibility for their own computer skill development:

At the opposite extreme was Outpatient Therapy, where supervisors and professionals delegate almost all computer work to clerical staff, with the result that computer skill remains concentrated in a few people who lack the political or cultural leverage to change the distribution of knowledge:

Edie described an incident that suggests how this process of delegation may impede the skill development of other members of the workgroup:

Through decisions and episodes like these, workgroups manage the distribution of computer skills necessary to perform their functions. All the interview participants described more interactions with colleagues than formal training experiences when asked about their most important experiences in learning computer skills.

Interpersonal behaviors like identifying local experts, solving problems together, tutoring, and deciding who will do what all arise naturally from the shared goals and constraints of a workgroup as its members use available computer resources to perform the tasks required by their jobs. From the perspective of individual learners, these informal interactions appear to account for most computer skill development. In addition to the ability to use applications and systems, this personal learning involves the acceptance of social roles, attitudes, and expectations that frame the learner’s understanding of computer work.

These socialization aspects of computer skill learning involve factors extending beyond the workgroup to the organizational level. Just as personal experiences of computer learning are embedded within workgroup interactions, so the role negotiation and shared beliefs of workgroups are embedded within the context of organizational factors.

The design of this study produced much more data about individual and workgroup learning than about organizational factors. The data collected did not include the extended on-site observations and internal documents that would support a full-scale treatment of organizational learning. However, the activities of each workgroup occurred within a context of organizational goals, resources, and conflicts, and some useful data about these factors emerged that reflect spontaneous, unplanned activity as well as managerial decisions.

Obviously, the most basic criterion for learning to use a computer is having access to one. While a few of the participants in the study owned personal computers, most did not, and all described their initial encounters and other important learning experiences as occurring within organizational settings. Thus it is important to consider the processes through which each organization determined what computer systems to acquire and whom to involve in the decision-making process.

At Leisure Activities, computer acquisitions followed typical university procedures in which proposals were submitted as part of an annual budget process. According to Mel Daniels, the university was somewhat slow in providing computers, but eventually supplied all the systems requested by the department:

The members of Leisure Activities asked for Macintosh systems as a result of informal networking with peers from other universities. Their choice was not based solely on the system’s reputation for ease of use, but also on the prospect of receiving assistance from colleagues in their academic discipline:

As Leisure Activities plans its future acquisitions, Beth Kirk has not hesitated to rely on the expertise of the support staff for decision-making:

This active involvement of computer users in selecting their own computer systems was not observed in the other two organizational cases. At County Hospital, the selection of hardware and software has remained firmly under the control of upper management and MIS since the arrival of Ted Warner:

This standardization process also included the selection of specific applications such as WordPerfect and Lotus 1-2-3. Later, as the hospital began its migration to Windows and local areas networks, new applications were selected by MIS. According to Ted Warner, the long-range goal is to allow users to access applications only from a central file server: "... We’re hoping to get as much as possible on the application server to take some of the upgrade load, and some security issues, and centralize them in the MIS department." At this point, individual users will have even less control than they do now over the software available to them.

Computer acquisition at RPI is carried out on a smaller scale and with a more personal touch, since John Gilliam serves all the functions of an MIS department. RPI’s standardization on the DOS/Windows environment seems to have evolved from its need to maintain compatibility with its first computer, the IBM AT John Gilliam found "sitting in the corner" when he arrived.

The staff at RPI rely on a standard set of applications chosen by John for their compatibility with the general-ledger and sales-tracking systems he designed. However, his policies for acquiring software are sufficiently flexible to allow Diana Oldham to continue to use Lotus 1-2-3 and WordPerfect as she makes the transition to Quattro Pro and Ami Pro. Perhaps because of its smaller staff, larger proportion of professionals, and flatter structure, RPI seems to be willing and able to acquire a wider range of software than the other organizations and to provide a limited degree of support for the preferences of individual staff members.

Though these data are too sketchy to support generalizations about organizational policies for computer acquisitions, they do show wide variations in the extent to which computer users were allowed to participate in such decisions in these three cases. User satisfaction with available computers seemed to be greatest at Leisure Activities, where users were directly involved in system selection; at County Hospital, where users had no involvement, satisfaction was much lower. Interestingly, neither of these groups showed high overall levels of computer skill compared to RPI, where user involvement in decision-making was limited but where daily work practices relied more heavily on creative computer use. Apparently, the levels of computer skill achieved within these organizations depended more strongly on job requirements and managerial expectations than on user involvement in computer acquisitions. The implications of the ‘plateauing’ of computer skill observed in the Leisure Activities and Outpatient Therapy cases are explored more extensively in Chapter V.

Given computer systems and applications, regardless of their level of involvement in the acquisition process, users must make do with the tools at hand. The distribution of the skills needed to perform computer tasks, as shown above, occurs largely at the level of workgroup interactions. Yet these interactions are insufficient to account for the way entire organizations adapt to the challenge of unfamiliar computer systems. Means must exist or be created to allow the necessary skills and information to reach all the affected workgroups.

The local experts interviewed sometimes had questions themselves that no one within their workgroups could answer. As a result, they tended to establish informal support relationships with people outside the immediate environment. Some of the participants talked about sharing information with computer users in different workgroups. Often these knowledge-sharing relationships involved many people and were stable over long periods of time. Existing independently of the formal structures of the organizations, these informal networks of computer users appeared to have evolved through word of mouth and shared experiences:

Sometimes these contacts extend to friends working in other organizations, or even friends or family members of co-workers.

An informal network of computer users was most strongly developed in the case of County Hospital, where it had taken on quasi-formal status in a computer users group. Widespread dependence on the informal network for problem solving seems to be the result of the failure of formal channels to provide needed computer information and support. Participants claimed that computer professionals at the hospital were incompetent or unresponsive to user needs and that some managers failed to pass down information about changes in computer resources.

While most of the data about problems with computer support at the hospital came from Liz Burton, other participants tended to confirm her views. A particularly startling example was the way Samantha Newhart’s computer had been configured for transcription. She showed me how the margins of her WordPerfect documents were too wide to allow lines of text to display fully on the screen. Rather than wrapping automatically, lines extended off the right edge of the screen for about 25 characters before wrapping. MIS was unable or unwilling to solve this problem or even to explain it to her:

In trying to resolve this problem, Samantha’s first recourse was to her office-mate. Liz was unable to elicit a helpful response from MIS in spite of her working relationship with that department. Given such inadequate support, it is not surprising that computer users at the hospital are compelled to rely on an informal network for help and information.

These needs became so pressing that a few individuals organized a users group, in effect creating a formal structure for informal knowledge sharing:

Initially, the hospital administration resisted the formation of the users group.

Eventually a few administrators (led by Ted Warner) recognized that the users group reflected legitimate learning needs of the hospital employees. The gradual accommodation of the users group by the administration provides an example of organizational learning through the negotiation of formal and informal interests.

The case of County Hospital illustrates the gap that can exist between formal and informal interests within an organization. In the context of the formal structure of the hospital, personal computing appears to be perceived in terms of costs and benefits (e.g., of acquisition and productivity), job requirements, and departmental authority (e.g., MIS). From the standpoint of users, computing is perceived in terms of day-to-day practices, especially computer problems that they are expected to solve with or without formal support. The disparity of these views has been a source of frustration and anger for both the staff and the administration.

Recent efforts to reduce this gap and address the needs expressed by computer users seem to have hinged on the efforts of Ted Warner. As an administrator with extensive experience as a computer user, Ted was in a position to understand the interests of both groups. He was well aware of the inadequacy of the hospital’s training policies:

However, Ted’s initial efforts to participate in the users group were not well received. Concerned about the costs of a proposal to use telephone support services, he tried to steer the group toward his own style of self-directed learning, unintentionally reinforcing the perception that the administration was indifferent to the problems of workers:

The first sign of progress in resolving these conflicts was the decision to let Liz Burton and other members of the users group participate in the planning of computer workshops.

Eventually, Liz became the official computer training coordinator for the hospital. Through her active participation in the informal network of users, she has been able to organize more and better computer workshops. These efforts appeared to be gaining momentum as the hospital completed the installation of its network. However, as noted earlier, Liz’s position is a temporary one. It is unclear what channels will remain for negotiation between the informal network of users and the formal structure if she is replaced, as planned, by an MIS professional.

The case of County Hospital is a unique instance, and it is by no means clear that the events surrounding the users group are in any way typical. It is not unusual in profit-driven organizations for formal goals to take precedence over the needs of individual computer users. This was evident in the case of RPI, where personal computers have provided leverage for aggressive downsizing:

Formal organizational interests in this context take on Darwinian overtones, as the company uses information technology to transform itself into a more competitive entity. In such situations, the economic survival of the firm is advanced at the cost of its employees.

Breaking down the data into the categories of personal experiences, workgroup interactions, and organizational factors has allowed each of these areas to be examined in detail. However, this artificial separation tends to obscure the interdependency of these categories and the global sense of what it means to learn to use personal computers in the context of workplace activities.

Unlike mainframe and minicomputer systems that support many simultaneous users, a DOS-compatible or Macintosh computer is designed for use by one person. The monitor, keyboard, and mouse provide affordances for a single user’s eyes and hands. The very phrase ‘personal computer’ implies independent use. Empowerment of the individual is a central theme in personal computer marketing, as magazine and television advertisements pitch products to manage one’s time and money, gain advantage over less savvy competitors, and unleash hidden powers of creativity.

However, the findings of this study tend to undermine this alluring image of the computer user as an independent, empowered loner. Instead, they indicate that individual computer skill learning is shaped at every stage by workgroup and organizational factors.

Computer skill is a complex set of motor, perceptual, and cognitive abilities that are developed over time through personal experiences. However, few of these experiences occur in social isolation. Each interview participant became a computer user when he or she encountered a unique organizational demand or opportunity. Each discovered different resources within his or her workgroup for getting answers to questions or trying to learn on his or her own. The need to ask questions, which was common to all the participants, could only be satisfied within the context of daily interactions with other people working with identical computer systems. Similarly, the tendency to try to solve problems independently through self-directed learning was a response to the stated or tacit expectations of others within the workgroup. In some cases, these expectations coerced reluctant learners to reduce their dependence on more skillful colleagues, while in other situations they encouraged delegation of computer tasks to a few people and thus an abdication of responsibility for further learning by the rest of the group.

Even those participants with the most proactive attitudes toward computer use and the greatest range of experience with varying systems and applications did not pursue computer skill learning in isolation. Instead, their status as local experts within their workgroups seemed to have been instrumental in their continued skill development. Faced with the expectations of coworkers for answers and solutions, local experts responded by continuing to learn and, in some cases, actively supporting the skill development of their colleagues through informal tutoring, distribution of printed information, or organization of training opportunities. Thus, regardless of the participants’ skill levels, workgroup interactions formed the context of almost all of their personal computer activity.

While most personal experiences of computer skill learning are bounded by the context of workgroup interactions, these interactions in turn are bounded by organizational factors. For each of the participants, organizational expectations, in the form of job descriptions and responsibilities, created the initial situation that motivated his or her first serious efforts at computer skill learning. In each case, organizational policies and procedures for computer acquisitions determined what types of computers and software workers would use. At the same time, factors of organizational culture influenced how workgroups distributed computer responsibilities and to what extent knowledge could be shared across departmental lines. The quality of formal computer support affected the degree to which users relied on informal networking for help in solving problems. In short, all of the participants’ learning experiences reflected the opportunities and constraints presented by the missions, resources, and cultures of their organizations.

Taken as a whole, the findings of this study indicate that the mass-market image of the solitary computer user rapt in silent contemplation of a screen is less representative than a bustling office scene in which work is interrupted constantly by dialogue: questions, responses, commiserations, and digressions. Becoming a skillful computer user is not a purely personal, cognitive achievement. Instead, it is a process of adaptation to the social opportunities and constraints presented by unique "communities of practice" (cf. Lave & Wenger, 1991). In turn, the computer productivity of organizations appears to be dependent on the extent to which their cultures allows members to share their knowledge with each other.

The implications of these findings are discussed in Chapter V.

CHAPTER V

Summary

This study examined how adults learn personal computer skills in the context of workplace activities. Twelve computer users in three organizations were interviewed about their computer skill learning experiences. Data from the interview transcripts and from on-site observations were used as the basis for a qualitative case study of learning in each organization. A cross-case analysis of the data provided the basis for a general interpretation of computer skill in terms of personal experiences, workgroup interactions, and organizational factors.

One of the unique results of this study is a composite narrative describing a typical sequence of workplace experiences through which individuals develop varying levels of personal computer skill. In general, individual skill learning begins with a social situation requiring adaptation to computers and may culminate in the ability to adapt computers to personal requirements. It is only within the context of specific social situations that people are likely to perceive themselves as computer novices in comparison to others with whom they share organizational resources and responsibilities. The transition from novice to experienced user, a process that may be enacted many times in the history of one’s computer use, depends both on self-directed learning and on informal knowledge sharing within workgroups through practices such as asking and answering questions and tutoring by local experts. While many individuals maintain a reactive stance toward computing, learning new skills only in response to organizational pressures, others achieve a more proactive ability to adapt a variety of hardware and software resources to tasks and to discover more productive ways to do their jobs.

The success of informal interactions in enhancing the overall computer knowledge and skill of workgroups appears to be influenced by organizational factors such as the delegation of work, user participation in computer-related decision-making, and the degree of conflict between formal organizational structures and informal networks of computer users. The variation in skill development shown by the participants within the different cases suggests that individual computer skill learning is strongly shaped by its organizational environment.

Discussion

The purpose of this section is to relate this study to some of the research reviewed in Chapter II and to speculate about its theoretical implications. First, data from the category of personal experience are compared to earlier research on self-directed learning and the role of experience in skill transfer. Next, findings on workgroup interactions are interpreted in terms of situated learning theory. In the final part of this section, the data on organizational factors are re-examined in light of the ‘productivity paradox’ described in Chapter I.

In addition to informal knowledge sharing, successful adaptation to the requirements of computer work and to the culture of a computerized workplace seem to require self-directed learning. Shared problem solving and tutoring within workgroups can be effective but are potentially inefficient. Excessive demands by inexperienced users for support can interfere with the ability of co-workers to manage their time effectively. As a result, the workgroups in this study tended to encourage their computer users to solve problems on their own whenever possible. These workgroup expectations create an "organizing circumstance" (Spear & Mocker, 1984) for self-directed learning. Rather than being purely self-regulated, such learning is initiated in response to an external demand and occurs under conditions over which the learner has relatively little control.

In the early stages of computer skill development, success in independent problem solving seemed to be important in reducing the participants’ anxiety and dependence on other users. The levels of skill participants achieved through self-directed learning appeared to be proportionate to the frequency and duration of their independent computer work, their persistence in problem solving, and the reinforcement of these behaviors by the workgroup. In groups in which all computer work was delegated to a few people, other members showed little evidence of self-directed learning.

Trial and error, the use of manuals, and exploration seemed to be less productive for novices than for experienced users. Some participants found the information in manuals hard to understand or apply to practical tasks, and their efforts to explore the features of their computer systems sometimes entangled them in errors. These results tended to confirm the findings of Briggs (1990), Carroll (1990), Charney, Reder, and Kusbit (1990), and Singley and Anderson (1989), which indicate that self-directed learning requires some prior experience to be effective (see the discussion below on the role of experience in transfer). Participants seemed to be most successful in self-directed learning if they could fall back on asking questions or being coached when necessary. Attempts to learn complex skills independently without any informal support from co-workers tended to be frustrating and unproductive.

A somewhat unexpected finding of this study was the apparently limited motivation of computer users to improve their skills beyond the levels necessary to meet minimal job requirements. Most of the participants in the study were not using their computer systems very effectively, in that they were not fully exploiting the systems’ potential to streamline or simplify their work practices. This lack of self-directed learning deserves closer consideration.

While some of the participants were working with older hardware and software, most had access to fairly current personal computers with adequate speed, memory, and applications. All three organizations were either already using or in the process of moving to Windows or Macintosh software, and the statements of participants tended to confirm experimental results indicating that such mouse-and-menu-driven software is easier to learn than command-based programs (e.g., Davis & Bostrom, 1993).

In spite of their access to good computing resources, most users in the study appeared to have reached plateaus in skill learning and performance. Most were proficient in a narrow range of tasks but reported having to resort to novice-like behavior when faced with an unfamiliar task, a pattern of behavior observed in an earlier experimental study (Santhanam & Wiedenbeck, 1993). This plateauing effect was most apparent in the Leisure Activities and County Hospital cases. With the exception of individuals identified by their peers as local experts, almost all the participants in these cases had minimal skill levels and did not appear to understand much about their computers (for example, few of these participants made statements demonstrating an understanding of file systems or of the interaction between disk memory and RAM). At RPI, where a small team of professionals was responsible for processing large amounts of financial data collected from subsidiaries, computer users were more likely to develop new skills in order to improve work processes.

The concluding section of the cross-case analysis suggests some possible explanations for this plateauing effect. At County Hospital, where workers had little control over their jobs or their tools, their skills remained fairly static and rarely achieved a level allowing them to be proactive in modifying their work procedures. At RPI, where job requirements were more flexible, employees relied on self-directed learning to discover ways to do their work better. The critical difference in these organizations appears to be the extent to which they emphasize standardized routines versus unpredictable outcomes. At County Hospital, most work is repetitive and procedural, while at RPI the emphasis is on achieving specific goals by whatever means the individual judges best. In these cases, self-directed learning of computer skills seemed to be shaped directly by organizational values.

Theories of situated learning, as summarized in Chapter II, argue that verbal knowledge as presented in traditional school instruction tends to transfer poorly to practical use. This view was partially supported by the present study, since some participants reported problems applying printed materials or lectures to actual tasks. However, other participants reported making effective use of printed materials for problem solving. The critical issue seems not to be whether such transfer can occur, but how factors of personal experience affect the degree of transfer.

Verbal knowledge is transferred to computer performance whenever someone uses a computer manual to solve a software problem. In such an episode, the transfer is an intentional (that is, self-directed) activity initiated in response to specific situational demands. The learner is motivated by his or her awareness of the expectations and judgments of other people to focus attention on a particular goal or problem. Often the computer user searches the manual for a bit of missing information that will be applied within a context of well-rehearsed procedures. Possible solutions are tested for their relevance to the task at hand until the problem is solved. Thus the abstract information in the manual is transferred to performance in a specific workplace situation through a cyclical process of execution and evaluation (cf. Norman, 1986). It is this hands-on experience, and the subsequent memory of it, that supports later use of the new skill.

The most skillful participants in this study showed cumulative effects in their development of expertise. The individuals who had extensive experience in using different applications and systems showed the greatest ability to transfer their experience to new situations. For example, participants who had already learned to use one or more word processing applications could learn another word processing application far more quickly than novices. This finding is consistent with the experimental studies of Singley and Anderson (1989) on skill transfer in text editing. Since all text editing involves the manipulation of "identical elements" (i.e., characters, words, sentences, and paragraphs), transfer between experiences with different word processing applications can be strong even when the details of procedures differ between applications (e.g., pull-down menus are used instead of function keys).

In the case of John Gilliam, the most sophisticated computer user in the sample, the ability to recognize identical elements was strengthened by a conceptual understanding of general principles of information processing and systems analysis. His ability to draw analogies between textbook examples and the unique database needs of RPI shows a type of abstract reasoning not described by the other participants. This instance is another example of verbal knowledge being transferred to performance within the context of a specific problem-solving situation.

A broad base of computer experiences appears to develop an awareness of the underlying similarities between different software and hardware systems that supports future learning. The benefits of experience are emotional as well as cognitive. Users who have learned new systems in the past seem to have greater confidence in their ability to do so in the future (cf. Gist et al., 1989, for a study of the relationship between self-efficacy and performance in computer use). The assurance that they will be able to learn new skills as needed appears to reduce users’ anxiety and allow them to make realistic estimates about the time they will need to commit to the learning required for future tasks.

Few of the participants in this study claimed that formal training had played a central role in the development of their computer skills, though most had attended such training. This result might have been predicted from experimental studies suggesting that conventional computer training produces relatively low gains in performance (e.g., Czaja et al., 1986 & 1989; Gist et al., 1988 & 1989). All of the participants described experiences of informal knowledge sharing as critical to their learning.

In most cases, the participants started learning about computers because they needed to function as members of a workgroup. All three workgroups shared computer knowledge through informal tutoring and mutual problem solving, and these activities seemed to be the preferred resources for individual skill learning. The situations of the workgroups also determined when an individual was likely to learn a new application or system and what resources he or she had available to apply to personal or organizational goals. Thus workgroup interactions and organizational factors appear to define most of the goals, opportunities, and constraints for individual computer skill learning in the workplace.

Both novices and experienced users in the study relied heavily on informal knowledge sharing with co-workers, claiming that asking and answering questions about computer problems were faster than alternative problem-solving methods. Certain individuals in each organization were recognized by all of their peers as local experts and were valued as resources for help and tutoring. These findings parallel those of Bullen and Bennett (1991) and are consistent with other research on learning in workplace environments (e.g., Brown & Duguid, 1991 & 1992). They appear to support a key concept of situated learning theory: that knowledge is not solely a property of individual cognition but instead is distributed within workgroups.

The theory of legitimate peripheral participation advanced by Lave and Wenger (1991) also helps to explain the patterns of informal knowledge sharing reported by the participants in this study. Typical of many work communities, legitimate peripheral participation is the process by which new-comers are integrated into the productive activities of the group. On-the-job learning through observation of and tutoring by ‘old-timers’ is legitimized by the culture of the organization. Novices are assigned peripheral positions and tasks that allow them to see complex work being done while sheltering them from the consequences of their lack of skill. Over time, novices become full participants. Their acceptance as peers doing equal work includes a process of socialization in which they accept the goals and practices of the group, including the responsibility to help educate future novices.

The situation at County Hospital can be interpreted as an example of the effects on individual and organizational learning when informal learning and peripheral tasks are not considered legitimate activities for novices. Several participants described their feelings of anxiety and frustration when they began new jobs lacking crucial computer skills, only to find that the culture of the hospital made no provision for a period of training or assimilation. Their efforts to receive informal help from co-workers were sometimes thwarted by low levels of computer skill within the workgroup. MIS policies at the hospital prevented participation by either novices or experienced users in decision-making about computer systems. Possibly as a result of these factors, most of the participants showed little inclination to learn new computer skills or to attempt to improve their computer practices. Only with the active involvement of Elizabeth and the users group in computer training did this situation begin to improve.

These findings about self-directed learning, skill transfer, and informal knowledge sharing suggest possible explanations for the frequent failure of organizational investments in computing to return commensurate gains in productivity – the well-known ‘productivity paradox’ (Brynjolfsson, 1993). The learning abilities of adults and the capabilities of personal computers seem to be less determinative of productivity gains than the extent to which organizations support users’ needs for self-directed learning, experience with a variety of applications and systems, informal knowledge sharing, and participation in the design of work processes.

For decades, some researchers on human-computer interaction have argued that user participation is fundamental to the design and deployment of effective computer systems (e.g., Bødker, 1991; Ehn, 1988; Winograd & Flores, 1986). Nonetheless, such participation seems to be the exception rather than the rule. Judging from the comments of the participants in this study, most computer users are forced to adapt to technology chosen and installed by people external to their workgroups, often delivered without warning or explanation. By limiting responsibilities for computer decisions to an internal MIS unit or team of consultants that is isolated from the actual work practices of users, organizations fail to exploit the situation-specific expertise of workgroups and often alienate the people whose activities the computer systems will ostensibly enhance.

Advocates of strategies for organizational change such as total quality management (TQM) and business process reengineering (BPR) often point to personal computers, and especially to the deployment of local area networks, as a means of creating flatter, leaner organizations that can respond faster and more effectively to competitive pressures. Central to these strategies is the idea of giving employees more decision-making power and broader task responsibilities. However, as Clement (1994) points out, fashionable talk of "empowerment" often confounds two distinct uses of the term, each with different implications for organizational computing. Most commonly, "empowerment" is taken to mean functional empowerment, in which computers are seen primarily as tools extending the ability of individuals to process and act on information. Prevalent in the managerial literature, the concept of functional empowerment tends to be "oriented to improving performance in the interest of organizational goals that are assumed to be shared unproblematically by all participants" (Clement, 1994, p. 54).

This concept of empowerment fails to address the relation between organizational and individual goals. Workers at the lower levels of organizations are not likely to feel "empowered" by managerial efforts to give them greater responsibilities without a corresponding degree of participation in determining what these responsibilities should be and how they can best be carried out. An alternative concept of empowerment, democratic empowerment, addresses such political concerns directly by emphasizing "the rights and abilities of people to participate as equals in decisions about affairs that affect them" (Clement, 1994, p. 54). Clement presents several case studies illustrating that functional empowerment through computerization inevitably raises issues of democratic empowerment, as informal networks of users attempt to renegotiate aspects of system and organizational design, often leading to direct conflicts with management and computer support staff. In some cases, these conflicts were resolved through mediation, but often only after work stoppages compelled management to negotiate. In most organizations, such conflicts probably never reach the level of collective action, but instead remain submerged, with corrosive effects on morale, corporate identity, and productivity.

These conflicts would appear to be the crux of the productivity paradox. The fundamental role of informal social networks in organizational learning implies that organizations are most likely to see continuous gains in computing productivity when their internal communities of users participate in decision-making about system specifications, training, and support. The educational implications of user empowerment in organizational computing are considered in the following recommendations.

Recommendations

The findings of this study might appear to denigrate the importance and effectiveness of computer training. It is true that most participants in the study did not feel that training had contributed greatly to their practical computer skills, and several of them described being bored or frustrated in workshops or in trying to read instructional materials. However, most of the participants said they wanted to participate in more training, and lack of training was cited frequently as a negative aspect of computing in their organizations. Clearly, adult computer users want and need more educational opportunities. A better understanding of how computer skills are developed and shared in workplace practices can help providers of training and continuing education design more effective instruction.

Most computer training is conducted in instructor-led workshops, usually in a computer laboratory. Generally such workshops focus on a specific piece of software such as a word processing or spreadsheet application. Participants listen to lectures about the capabilities of the application and perform exercises that allow them to experience the use of key features. Often a projection system allows the group to see the screen of the instructor’s computer as he or she explains the organization of menus and commands and demonstrates procedures. Such training may extend over weeks (as in the case of a continuing education evening class) but more typically lasts three to six hours.

This popular form of training can be an extremely efficient approach to introducing groups of workers to new computer applications. However, learner satisfaction and subsequent transfer to work practices seem to depend on how well the training reflects the needs and abilities of the participants.

Often such classes are planned and taught by computer professionals who find it difficult to empathize with less experienced users or to explain applications from perspectives of practical use. This situation transfers to the classroom the communication problems that many participants in this study described in their encounters with computer professionals, who baffled users with technical jargon and concepts that had little apparent relevance to the practical outcomes of the discussion. When pressed into service as instructors, ‘techies’ may devote more class time to lecturing than to guiding the participants through hands-on activities, and their curricula tend to focus on exhaustive presentation of software features rather than performance of typical tasks. Such training bears little relation to the way computers are used in workplaces and seems unlikely to lead to significant gains in performance.

These problems might be avoided or minimized through better planning and instructor preparation. In identifying instructors, program planners should recognize that technical expertise can be an obstacle as well as an asset. Far more important are the abilities to appreciate the goals and feelings of inexperienced computer users, to listen patiently and responsively, and to use participants’ efforts and errors as opportunities to explain underlying concepts. As the findings of this study suggest, being able to understand the context of individuals’ computer use and to relate instruction to that context is what makes co-workers and local experts the most powerful resources for informal learning. Thus it is hardly surprising that effective computer trainers, whatever their backgrounds or relationship to their audiences, seem to develop learner-centered instructional strategies consistent with standard theories of adult education practice (e.g., Knowles, 1990).

The greatest weakness of most computer training seems to be its lack of duration. A failure to control for this variable was cited as a methodological problem in several of the quasi-experimental studies reviewed in Chapter II. The importance of training duration is well documented in other research and is often depicted in the classic ‘learning curve’ graph, which shows an exponential relationship between the amount of time spent practicing a skill and the speed and accuracy with which it can be performed. In general, for complex skills such as the use of personal computer applications, the initial period of steep gains in performance seems to be several hours longer than the three to six hours typical of most training workshops (cf. Card, Moran, & Newell, 1983, for a detailed discussion of power-law effects in computer skill learning).

The brevity typical of most computer training may help to account for its limited effectiveness for the interview participants. Eleven of the twelve reported receiving some computer training, but all of them perceived their informal learning experiences as more important to their overall skill development. However, most of the participants’ computer training had been limited to a few half-day or one-day workshops, often separated by long intervals. The individuals identified as local experts tended to have taken more short courses and more sustained classes. For example, the most skillful user interviewed, John Gilliam, had also participated in the most training: three quarters of college computer classes. While a self-selection effect seems to be operative here, in which the most motivated computer users chose to participate in more training, the interview data do tend to support a relationship between total duration of training and subsequent performance.

For greatest effectiveness, therefore, computer training should extend over several days. In situations where it is impractical to allot more than one day to training, care should be taken to minimize lecturing and allow as much hands-on practice as possible. Comprehensive coverage of software features seems to be less important than sustained activity with the most frequently-used features.

The findings of this study suggest that participants may enjoy training more and perceive it as more useful when workgroups are able to participate in planning educational goals and activities and to train together. Training a workgroup as a unit appears to increase the likelihood that the skills introduced in a class will be reinforced and rehearsed in later informal knowledge sharing, while allowing workers to participate in curriculum development can help ensure that laboratory activities are strongly parallel to the work tasks for which the software is to be employed. This is why Elizabeth and the users group at County Hospital rejected generic ‘beginning’ and ‘advanced’ computer workshops designed without reference to their work practices and asked that they be allowed to specify the skills taught in each class.

As shown by the example of County Hospital, organizing and scheduling training becomes more politically complex when participants insist on involvement. Rather than relying on directives from management as their sole source of information about learners’ skills and work practices, educators must find ways to legitimize the participation of trainees in planning.  Cervero and Wilson (1994) provide a realistic guide to responsible program planning in the face of conflicting organizational interests.

Classroom computer training often lacks duration because a workgroup simply cannot stay away from the office for long. In fact, participants in mandated training often express resentment about their lack of control over telephone coverage and other aspects of routine workflow during the time committed to training. An alternative is the establishment of a learning lab, a resource center where individuals can schedule sessions to work independently with technology-based instruction (cf. DeJoy & Mills, 1989; Mills & DeJoy, 1987). This study lends some support to this strategy, since all of the participants described self-directed learning as central to their development of computer skills.

Self-directed learning on the job differs in significant ways from more structured independent learning with instructional technology. Several of the studies reviewed in Chapter II indicate that computer-assisted instruction (CAI) may produce lower performance gains than classroom training. Carroll (1990) describes the many problems learners can experience in working with programmed instruction, where deviations from a rigid sequence can produce confusing errors. However, CAI and related technologies have improved since those studies were conducted. The commercial market for self-directed training materials has become larger and more competitive as the personal computer industry has grown, with the result that more inexpensive and useful products are now available. For example, CD-ROM allows the development of content-dense multimedia programs combining text, graphics, audio, animation, and video through which users can choose their own instructional paths. Multimedia software can also use artificial intelligence techniques such as user modeling to respond to a learner’s interactions (cf. Burns, Parlett, & Redfield, 1991, for a review of intelligent tutoring systems).

The possibilities for self-directed learning through multimedia are enlarged by the internetworking protocols of the World-Wide Web, which allow learners to use a graphical hypertext interface to search for information distributed across the global Internet (Krol, 1994). Other Internet resources such as mailing lists (listservs) and Usenet news groups show strong parallels to the forms of informal teaching and learning observed in workplaces. In these electronic forums, people working in different organizations ask and answer questions freely, the only common bond among them being the shared experience of computer use and the certainty that "... Given the rapidly changing technology ... at some time and in some way, anyone can be both a novice and an expert" (Brown & Duguid, 1992, p. 173). By making such resources available to employees, organizations open the possibility of developing an almost unimaginable range of knowledge and skills in response to immediate situational demands.

The use of a learning lab may offer advantages over making training available on employees’ workplace computers. Carroll (1990) describes how motivational conflicts can hinder computer skill learning, creating a double-bind in which the desire to solve an immediate work problem increases anxiety and prevents the spontaneous exploration that is crucial to expanding computer knowledge. A learning lab can provide a temporary sanctuary from the environmental demands that limit most workplace learning to hurried questions and answers. It can also make available a wider variety of materials and provide staff support for selecting among them and using them successfully. At the University of Georgia Center for Continuing Education, the typical pattern of learning lab use involves consultation with lab staff to identify appropriate resources and then alternation among materials in various media (CAI, interactive video, audiotape, and videotape), throughout which lab staff answer questions, help solve problems, and provide encouragement. The freedom and self-direction of this approach to computer skill development appear to be extremely motivating for many lab users.

Organizations establishing learning labs need to ensure that policies and procedures for lab use are widely communicated. Success depends largely on the willingness of managers to release staff for learning lab sessions. Organizations must also recognize that learning labs require an ongoing budgetary commitment to upgrade hardware, software, and training materials as computer use in the organization changes. The high costs associated with instructional technology are likely to limit the use of learning labs to large organizations with well-defined training needs.

Classroom computer training and learning labs fall within the range of educational options familiar to most specialists in training and continuing education. However, the results of this study suggest that the activities of educators are peripheral to a great deal of organizational learning. The "learning-in-working" (Brown & Duguid, 1991) that occurs informally within workgroups can never be replaced by formal training, simply because only active members of the workgroup can match instruction to the situations in which knowledge and skill must be applied. Such knowledge cannot be codified in organizational charts, procedures manuals, or expert system software because it cannot be abstracted from the day-to-day interactions of people working in evolving communities of practice (Lave & Wenger, 1991). Once the shared discourse of a community is translated into written or coded form, it is inevitably incomplete, dated, and brittle.

Rather than denying or resisting their inability to control all organizational learning, educators should consider how their efforts can enhance the performance of communities of practice. Human resource development staff can serve as advocates for local experts, relying on users’ knowledge of organizational computing practices to plan and conduct classroom training. HRD staff may also be able to play a role in reducing the perceived conflicts of interest between the formal organizational structure and the informal network of users by sponsoring internal users groups, e-mail, and electronic bulletin boards to provide organization-wide forums for the distribution of practical computer knowledge. Ultimately, all these strategies point toward the cultivation of an organizational culture that can respond fluidly to technological change.

A great deal remains to be learned about computer skill learning in the workplace. The work of Howard (1994) and the present study demonstrate the utility of interviewing as a qualitative research strategy, but both of these studies suffer from the lack of a longitudinal dimension. While the interview participants in this study were able to describe the history of their own learning, and in some cases the history of computer use within their workgroups, these reports cannot be given the same weight as data collected over a longer period of time. Nor did the interviews provide enough information to draw many conclusions about the events of organizational history that had shaped the learning of each workgroup. A valuable alternative strategy for qualitative research is indicated by Zuboff (1988), whose sustained ethnographic study of several high-tech work environments succeeds in conveying the sudden shifts and gradual processes through which organizational cultures change in response to technological innovations. Only studies on this scale are likely to elucidate the organizational factors that influence individual and workgroup learning.

The participants in this study tended to give more weight to their informal learning experiences than to the formal computer training they had received. Why did they express these feelings, and is their perception of the low value of most formal training warranted? More quantitative research is needed to evaluate the effectiveness of different forms of computer training. While many subjective and intersubjective aspects of computer skill learning are not readily quantified, some aspects of the performance of computer tasks can be measured with great accuracy. Many studies demonstrate that the statistical analysis of recorded keystroke data can provide strong quantitative models of computer use (e.g., Card, Moran, & Newell, 1983).

The literature on computer skill learning does not yet include studies that use rigorous quantitative techniques to assess pre- and post-training performance. By recording keystrokes, commands, menu selections, and other user actions during normal computer work, and then comparing logs of user actions before, during, and after training, the relationship between training activities and subsequent transfer to performance could be reliably measured. While such research could not address directly the interpersonal aspects of learning described in this study, it could be used to confirm or disconfirm some of its findings and to assess the effectiveness of different forms of instruction. The software developed to carry out such studies could also be adapted to create instruments for evaluating computer skills.

Another area of research in computer skill learning that could explore the implications of this study is the use of artificial intelligence methods to create computer models of skill learning. Card, Moran, and Newell (1983) and Singley and Anderson (1989) describe rule-based expert system software that attempts to simulate the way humans learn and apply procedural skills. However, by isolating knowledge within the ‘black box’ of a single expert system, these computer models fail to reflect the ways in which human skills are distributed among members of a workgroup. An alternative research strategy would be to create model ‘societies’ of programmed ‘agents’ that can exchange information and procedures and work collaboratively to reach shared goals (cf. Bond & Gasser, 1988; Minsky, 1985). In addition to their theoretical interest, such distributed systems would contribute to the development of ‘intelligent’ performance support software that could learn from, teach, and work for humans in networked computing environments.

This study has not addressed the relationship between computer skill learning and the increasing prevalence of local- and wide-area networks. Electronic mail, on-line discussion forums, group support systems, teleconferencing, and telecommuting are all technologies that are already commonplace in many organizations and which have direct effects on the ability of computer users to share knowledge with each other. So far, there has been little or no research on the role of these network resources in computer skill learning. To indicate just one possible area for future study, the archives of Usenet news groups preserve many gigabytes of text describing years of computer problems, discussions, and solutions by thousands of participants. New research methods will have to be developed to analyze this astonishingly rich data source.

As computer networks continue to spread beyond academic and business environments to connect people’s homes, the ability to learn to use these systems will take on new dimensions of political and social importance. Economic divisions within society threaten to expand with the growth of an information underclass, effectively excluded from many forms of work and participation in public life by its lack of computer skills. Over the course of the next decade, the contradictions of user empowerment now being played out within organizations will be experienced on a national scale in the United States and other industrialized countries, and researchers will face the daunting but inescapable challenge of trying to understand and influence these events. Research on computer skill learning provides an important resource for the design of the information systems required by the ongoing globalization of computer networks.

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APPENDIX 1

[Date]

[Address]

Dear [Participant],

I’m writing to ask your help in identifying members of your organization who would be willing to participate in a dissertation research study about computer skill learning in the workplace.

I would like to talk with personal computer users at any level of experience, from beginners to experts. I am especially interested in interviewing small groups of computer users who work together and sometimes assist each other with computer tasks and problems. I will meet each participant at his or her office for an informal 60-90 minute interview, possibly followed by a second, shorter interview to be scheduled at the participant’s convenience. I will ask about personal experiences that have been important in their computer learning–how they got started, what positive and negative experiences have influenced their learning, and how they cope with computer problems. Interviewees will also be invited to join a focus group to be held at a later date at the Georgia Center, but are not obligated to attend this.

In transcripts of the interviews and in any published reports of this research, I will use pseudonyms for participants’ names and the names of all individuals and organizations, so personal and organizational confidentiality will be protected. Participants will be free to withdraw from the research at any time and to have their data removed from the study.

If you would provide me with the names and telephone numbers of 2-4 people who might be willing to give some of their time for this study, I would be very grateful. These interviews will produce information about computer training needs that may be useful to your organization, and I will be more than happy to share my findings and to provide informal consultation about ways to help your staff improve their personal computing skills.

Please contact me at the number below if I can answer any questions.

Sincerely,

Brad Cahoon

Coordinator for Technology Instruction

University of Georgia Center for Continuing Education

(706) 542-7428

APPENDIX 2

APPENDIX 3

How do people learn to use personal computers in the workplace? To try to answer this question, I asked 12 interview participants in three organizations to tell me about their personal experiences, experiences in their workgroups, and experiences of their organizations.

In response to the question, "How did you get started using personal computers?", each interview participant told a different story. For everyone, the passage from computer novice to skillful user involves unique personal problems, opportunities, and accomplishments. However, there are some common themes. In talking about learning to use computers, the interview participants tended to talk about certain kinds of experiences:

• Becoming a computer novice in response to external circumstances

• Asking other computer users for help

• Learning independently through trial and error

• Learning more than one application or computer system

• Learning to adapt computer resources to personal demands.

Of the 12 participants, only three reported that they had first encountered personal computers in school. Almost all of the interview participants had their first serious encounters with computers at work.

Some participants learned computer skills when they got started at a new job. Several others learned when their organizations installed personal computers. A few people got access to computers that were not being used and managed to pick up some computer skills without immediate work pressures.

At first, a new computer user depends heavily on co-workers for help. More experienced users can answer questions as well as ask them. Asking or answering questions is often the most efficient way to solve a problem, but co-workers can’t or won’t help in every situation. Using a computer also requires self-directed learning.

People in a workgroup tend to have informal rules for sharing knowledge. Often, experienced users encourage beginners to try to solve computer problems on their own before asking for help.

Several participants talked about the difficulty of reading software manuals, but most acknowledged them as a good resource for self-directed learning. Sometimes unexpected tasks or problems led to learning. For example, being asked by a supervisor to prepare a special document might cause someone to learn unfamiliar features of their word processing program.

Some participants described vivid memories of losing important computer files. These disasters can help new users learn more about how their computers work and can also help develop better work habits (for example, making back-ups).

Figuring out problems independently seems to be important in reducing people’s anxiety and dependence on other computer users. How much people learn on their own depends on how often and how long they work on their computers, how persistent they are in solving problems, and whether or not they are satisfied with the results of their work.

Many computer users reach a plateau in their computer skills. They learn enough about one program to meet the day-to-day requirements of their work, but run into trouble if they need to do something unfamiliar. A common experience in reaching higher levels of skill is learning to use more than one program or computer system. This might involve switching from an old to a new version of the same software (for example, from WordPerfect 5.1 to WordPerfect 6.0). Switching from one application to another can be more confusing (for example, switching from the DOS version of WordPerfect to WordPerfect for Windows).

Generally people learn a new application or computer system because of changes in their organization. Often people are reluctant to learn new programs, but they are more likely to try when they believe that the new program has significant advantages over the old one. For example, some of the interview participants were excited about learning Windows programs, even though these programs were very different from the DOS programs they had been using, because they felt that Windows was easier to use.

People who have learned new systems in the past have greater confidence in their ability to do so in the future. Knowing that they can learn new skills reduces their anxiety and allows them to make realistic estimates about the time they will need to learn new skills. This confidence is one of the differences between beginners and experienced computer users.

The most experienced computer users are able to adapt the computer resources at hand to solve problems and simplify routine tasks. Several participants mentioned discovering new and useful features of their software by ‘fooling around’ or exploring. Some solved problems for their workgroups by creating computer versions of commonly-used forms or setting up macros to automate repetitive work. Using the computer creatively shows a high level of skill. These experienced users are often able to answer questions and solve problems for co-workers and are recognized as ‘local experts’ in their workgroups.

A workgroup is any group of people within an organization whose job responsibilities involve daily interaction, usually sharing the same space and resources. Relationships within a workgroup tend to be informal. In most cases, the need to function as a member of a workgroup causes people to begin learning about computers.

In each of the workgroups studied in this research, certain people were identified by their colleagues as local experts who helped others with computer problems. It’s not unusual for local experts to be women in clerical positions who do a lot of computer work. In some workgroups, several people share this role.

The importance of local experts is rarely mentioned in manuals, training policies, or job descriptions, but they are essential to every organization. No matter how skillful or resourceful a new employee may be, there are some things that he or she can learn only from experienced staff members who know how the workgroup gets things done.

People share computer knowledge within their workgroups mainly by asking and answering questions and through coaching. For most users, asking a colleague for help with a computer problem is faster than looking for a solution in a manual, but this efficiency must be balanced against the time lost by the person providing the help.

Workgroups respond to this problem in various ways. Some give local experts a great deal of informal authority to decide who will do what computer work within the group. For example, a secretary might encourage her supervisor to learn basic word processing himself. At the opposite extreme are workgroups in which supervisors delegate all computer work to the clerical staff, so that only a few people in the group ever develop any computer skills.

Local experts may have questions themselves that no one in their workgroups can answer. They tend to establish informal support relationships with people outside the immediate environment, such as friends in other departments, in other organizations, or even friends or family members of co-workers.

Answering questions face-to-face or on the phone is the most common way for people to share knowledge in their workgroups, but printed materials are also important. An local expert may get tired of explaining a particular procedure and circulate a memo describing it, or an employee who attended a training session may photocopy handouts to share with colleagues.

One-on-one coaching by a local expert is a valuable but time-consuming activity that usually occurs only when a new member joins the workgroup or when tasks are reassigned within the group. A typical coaching experience involves a local expert and a learner sitting down together at the learner’s computer and practicing basic tasks . Many people get their first exposure to computers this way.

In large organizations workgroups are usually isolated from each other, following set policies and procedures that define the responsibilities of workers and departments. Training often receives less attention than other goals: providing services to clients, maintaining records, and managing internal reporting relationships.

Even in big organizations, computer users who do similar work in different departments tend to learn about one another and share information, so that an informal network of computer users develops. Over time, the informal network of users may develop its own lines of communication and leaders. Some of the least powerful members of the organization (such as female clerical workers) may be recognized by their peers as authorities within this informal network. If computer users do not have adequate support or opportunities to participate in decisions about the systems they work with, they rely almost entirely on informal networks for help and information. Sometimes this situation can create tension.

The formal structure of an organization is based on written job descriptions, organizational charts, and other documents. In contrast, an informal network of computer users is an outgrowth of daily work habits. These differences can cause conflicts between workers and administrators even though all the parties involved share many of the same organizational goals. One of the challenges of managing large organizations is to ensure that workers have adequate computer resources and skills to do their jobs. This may require letting local experts help plan training and other activities. Using the expertise already available in the organization can raise overall skill levels.

Another important factor is the relationship between computer users and computer support staff. The success of a computer support team depends on the size of the team, the experience and education of its members, and the financial backing it receives. It also depends on the team’s attitude about the departments and individuals they support. Computer professionals can encourage workgroups to strengthen their computer skills by taking a ‘customer service’ approach of helping departments identify their own computing needs and involving local experts in decision-making about hardware and software.

Taken as a whole, the findings of this study indicate that most people learn to work with computers as a result of their experiences in workgroups and organizations. Becoming a skillful computer user is not a purely personal achievement. Instead, it is a process of adapting to the opportunities and obstacles presented by an organizational situation. In turn, the computer productivity of an organization depends on allowing its members to share their knowledge with each other.