06 brugeres forventninger

The Role of Work, Play, and Fun in Microcomputer Software Training Elissa L. Perry University of Illinois, Urbana-Champaign

Deborah J. Ballou University of Notre Dame

Acknowledgement

The authors would like to thank Carol Kulik and Joe Martocchio for their assistance and helpful comments at various stages of this research. We would also like to thank Ruth Reingold, Manager of System Services, for her cooper- ation in this research endeavor.

Abstract

A field study of MBA students enrolled in a microcomputer software training class was conducted. Trainees' expectations of the extent to which the training would be like work and play were collected prior to the training and their perceptions of the extent to which the training was like work and play were collected after the training. In addition, trainees' perceptions of the extent to which the training was fun were also measured. Results indicated that play perceptions operated as a suppressor variable. Post- training play perceptions had a marginally significant and negative effect on learning and #7- creased the positive and significant effect of post-training fun perceptions on learning. Re- suits also indicated that despite the fact that much of the training occurred on the computer, trainers influenced trainees' perceptions that the training seemed like work, play, and fun. Finally, learning was negatively affected when trainees with high pre-training play expectations perceived trainers to have a high work orientation in the training. These results suggest that play and fun perceptions have potentially important consequences for learning and that trainers play an important role in influencing these perceptions in microcomputer training.

Keywords: Computer-based training, human- computer interaction, work, play, fun, learning

ACM Categories: H.4.1, K3.1, K.81

Introduction

The use of microcomputer technology in organizations is widespread (Ballou & Rush, 1996; Turnage, 1990). Training and retraining demands increase with the implementation of technology. In addition, some have suggested that the primary causes for the failure of office technologies (e.g., computer systems) are human and organizational, including the lack of employee training (Turnage, 1990). As a result, interest in training individuals in the use of microcomputer technology has risen (Allan, 1993; Ballou & Rush, 1996; Geber, 1994; and Klein- schrod, 1988). At the same time, a growing body of research has developed which explores microcomputer training issues in the workplace

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(e.g., Gist, Schwoerer, & Rosen, 1989; Martoc- chio, 1992; Martocchio & Webster, 1992; and Webster & Martocchio, 1993).

Although the structural design of microcomputer software is likely to influence how easy it is to learn, a recent stream of microcomputer training research suggests that an individual's approach to a task as work-versus-play may also influence computer training effectiveness (Martoc- chio & Webster, 1992; Webster, Heian, & Michelman, 1990; Webster & Martocchio, 1992; and Webster & Martocchio, 1993). This research suggests that a work-versus-play orientation may be the result of individual attributes (e.g., a playfulness trait) (Martocchio & Web- ster, 1992; Webster & Martocchio, 1992) or social contextual cues (e.g., labeling) (Webster, 1990; Webster & Martocchio, 1993). It has been argued that individuals demonstrate greater creativity and develop skills through exploratory behaviors during playful interactions with tasks. Therefore, those who approach a task as play are expected to learn more than those who approach a task in less playful terms or who approach it as work. Consistent with this, research suggests that perceptions of computer training as play as opposed to work result in more positive training outcomes.

The little research that has explored the influence of labeling computer training tasks as work versus play (Webster et al., 1990; Webster & Martocchio, 1993) has for the most part done so in the context of an experimental research design which explicitly manipulates task labels. As a result, these research efforts have high internal validity and have thus been able to assess causal relationships. However, this research provides little infonTlation about how individuals naturally and spontaneously perceive actual computer training contexts. It is also unclear to what extent actua~ trainers influence trainees' perceptions of a task as work versus play when trainers are not explicitly instructed to label tasks. It is possible that individuals do not spontaneously perceive computer training in work versus play terms in the course of an actual training program. Further, even if individuals do perceive computer training in work- versus-play terms, these perceptions may not influence learning in a training context that does not explicitly and clearly prime these concepts (e.g., using task labels). Consistent with this,

Glynn (1994) has suggested that ".. .research is n e e d e d . . . o n how task interpretations may occur spontaneously, even in the absence of experimental cues that send the message that 'this is work' or 'this is play.'"

Both the social contextual and individual difference approaches to work-versus-play orienta- tions suggest that play has multiple dimensions. Martocchio and Webster (1992) suggest that while the most relevant aspect of individual playfulness in human-computer interactions is cognitive playfulness, other dimensions of playfulness (e.g., manifest joy) may be relevant and should be explored. The literature is less clear about what aspects of labeling a computer task as "play" may contribute to its beneficial effects. Some research suggests that one dimension of play is fun (Bamett, 1990; Glynn & Webster, 1992).

Other research suggests that play and fun are closely related but distinct concepts (e.g., Abramis, 1990). Although "fun" is likely to be associated with play more than work (Dan- dridge, 1986) this is not always the case (Burke, 1971). Work can sometimes be fun and enjoyable while play may not be. Currently, little research has explored the extent to which computer training tasks may be perceived as fun and the extent to which this perception is related to perceptions of the task as work versus play. It is also unclear how perceptions of a task (e.g., computer training) as work, play, and fun influence training outcomes relative to one another.

The current paper presents exploratory research that addresses four issues. First, this paper explores the extent to which individuals in an actual computer training context spontaneously perceive the training as work versus play and the influence of these perceptions on learning. A field study approach is adopted in order to determine the extent to which previous research results which indicate that task labeling (work versus play) influences training outcomes in a field experiment generalize to a non- experimental context.

Second, this paper explores the extent to which individuals' work and play perceptions of the training are influenced by the trainer. Although other social contextual factors (e.g., classmates) may influence individuals' perceptions and training outcomes, the focus in the current research

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is on the role of the trainer for two reasons. First, previous experimental research suggests that the social context (i.e., the trainer) can influence the extent to which individuals perceive training as work versus play (e.g., Webster et al., 1990; Webster & Martocchio, 1993). It is informative to assess the extent to which trainer effects also operate in a non-experimental set- ting. Second, trainers constitute an element of the social context over which training designers have relatively more control. As a result, it is particularly important to focus on this aspect of the training context. The current paper assess- es the extent to which actual trainers influence work, play, and fun perceptions in a context where they are left to their own devices and are not instructed to label the training in any particular way.

Third, we examine the extent to which individuals' pre-training work and play expectations interact with their perceptions of the trainers' work and play orientation to influence training outcomes. Research suggests that it is important to explore the effects of individual difference factors on work-and-play labeling (e.g., Tang & Baumeister, 1984). In addition, research suggests that pre-training expectations of a task (e.g., as work or play) are important to statistical control (Martocchio, 1992; Webster & Martocchio, 1993). However, little research has explored the extent to which pre-training work- and-play expectations interact with perceptions, which are not experimentally manipulated, that the trainer made the task seem like work or play.

Fourth, we explore the relationship between perceptions of training as work, play, and fun and determine their effects on learning in order to understand better the types of task perceptions that are likely to have beneficial effects. To date, research has primarily focused on the role of work and play perceptions in the context of computer training. In addition, little research has explored dimensions of play other than cognitive playfulness in computer training (Mar- tocchio & Webster, 1992; Webster & Mar- tocchio, 1992).

Theoretical Basis for Work-Versus- Play Effects

Research suggests that whether individuals approach a task as work versus play may influ-

ence work related (e.g., training) outcomes (e.g., Abramis, 1990; Cellar & Barrett, 1987; Glynn, 1994; Sandelands, 1988; Tang & Bau- meister, 1984; Webster et al., 1990; and Web- ster & Martocchio, 1992, 1993). This is hypothesized when a work-versus-play approach is a function of individual attributes (e.g., Glynn & Webster, 1992; Webster & Martocchio, 1992), contextual factors (Abramis, 1990; Glynn, 1994; Sandelands, 1988; Webster et al., 1990; and Webster & Martocchio, 1993), or both (e.g., Tang & Baumeister, 1984). Research has generally hypothesized and found positive effects for individuals who approach a task as play (Abramis, 1990; Cellar & Barrett, 1987; Csikszentmihalyi, 1975; Martocchio & Webster, 1992; Miller, 1973; Webster et al., 1990; and Webster & Martocchio, 1992, 1993). For example, play has been found to be positively associated with mood, satisfaction, learning, performance, and intrinsic motivation.

Research that has taken an individual difference approach to work-versus-play orientation suggests that one of the most important aspects of playfulness in human computer interaction is cognitive spontaneity (Martocchio & Webster, 1992; Webster & Martocchio, 1992). This aspect of playfulness refers to an individual's tendency to interact spontaneously, inventively, and imaginatively with microcomputers (Web- ster & Martocchio, 1992). It is hypothesized that those who are higher in microcomputer playfulness will view computer interactions more positively, be more motivated to engage in computer interactions in the future, engage in more exploratory behaviors, and thus learn more than less playful people.

In their review of multiple microcomputer studies, Webster and Martocchio (1992) found that the individual attribute of microcomputer playfulness was positively related to computer attitudes, computer competence, computer efficacy, involvement, positive mood, satisfaction, and learning. In addition, they found that playfulness influenced learning more than other attitude factors (e.g., computer anxiety). Com- puter training study results are consistent with research that finds that measures of general playfulness are positively related to creativity, and more exploratory behaviors during interactions with tasks (e.g., Glynn & Webster, 1992).


Similarly, those taking a social contextual approach to work-versus-play orientation suggest that labeling a task as work or play will affect the evaluation of a task, which in turn, will influence learning in training (Webster & Martocchio, 1993). The theoretical basis for this approach is social information processing theory developed by Salancik and Pfeffer (1977, 1978), cognitive categorization theory (Fiske & Taylor, 1991), and play research and theory. Speci- fically, social information processing theory suggests that task attitudes may be influenced by the labeling of tasks by others (Salancik & Pfeffer, 1977, 1978; Staw, 1984). The social context makes certain information salient to the individual. Consistent with this, organizational research finds that labeling a task as work- versus-play influences a variety of work related outcomes (e.g., learning, positive affect, task evaluation, motivation) with more positive outcomes typically found in the play condition (Cellar & Barrett, 1987; Sandelands, 1988; Webster et al., 1990; and Webster & Martoc- chio, 1993).

One mechanism that has been used to explain these labeling effects is cognitive categorization. Research and theory suggests that individuals have and use different types of job- related categories under certain conditions (Ku- Ilk & Perry, 1994). For example, there is some evidence that individuals have work-and-play cognitive categories which are more or less available to the perceiver (e.g., Cellar & Barrett, 1987; Porac & Meindl, 1982; and Webster & Martocchio, 1993).

Play research and theory suggests that the play category is likely to include a greater emphasis on means than ends and feelings of both plea- sure and involvement (Sandelands, 1988; Sandelands & Buckner, 1989; and Webster & Martocchio, 1993). Researchers studying play (e.g., Csikszentmihalyi, 1975; Miller, 1973; Sandelands, 1988; Sandelands & Buckner, 1989; and Schuck, 1985) suggest that during more playful interactions with tasks, people engage in exploratory behaviors, spend more time and effort on task: performance, enjoy what they are doing more, and learn more effectively. Therefore, labeling a task as play should have more positive implications for learning than labeling a task as work. This research and theory suggests that the social context of

training may prime trainees' work or play categories which in turn influence trainees' evalu- ations of the task and the extent to which they learn in training.

Consistent with this, Glynn (1994) found that the influence of task labeling on performance outcomes was mediated by cognitive processes (i.e., means-end orientation). Specifically, she found that the label play induced a means orientation which, in turn, resulted in higher task performance outcomes. In contrast, the label work induced an ends orientation which, in turn, resulted in lower task performance outcomes. Webster and Martocchio (1993) found that younger employees who received training labeled as play showed higher motivation to learn and learned more than older employees. Finally, Webster et al. (1990) found that students experienced higher mood and involvement and learned more in computer training classes labeled as play rather than work.

While we have suggested that a play orientation is frequently found to have positive effects, research and theory suggests that it can also have potentially negative effects. For example, Sandelands (1988) found that when a task was labeled play, individuals took longer on the task than when the task was labeled work. Csikszentmihalyi (1975) suggested that playfulness may lead to over-involvement. Finally, Schuck (1985) argued that play can have negative consequences for work equipment and processes. However, there is little research evidence that a play orientation has negative consequences in the context of computer training (e.g., Martocchio & Webster, 1992; Webster et al. 1990; and Webster & Martocchio, 1992, 1993).

There is some evidence that perceptions of play may have a greater influence on training outcomes than perceptions of work. Much of the research that has explored the effects of task labeling on work outcomes has manipulated work and play task perceptions in an experimental between-subject factorial design. How- ever, Cellar and Barrett (1987) assessed the effects of a within-subject measure of work and play perceptions which enabled them to determine the relative influence of these perceptions on task outcomes. They found that two play measures significantly predicted intrinsic

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motivation, one work measure was non- significant, and the second work measure only marginally significantly predicted intrinsic motivation. Additionally, work-and-play research and theory tends to emphasize the positive impact of a playful approach to tasks, suggesting that a play orientation may have more important consequences for work outcomes than a work orientation. This suggests that play perceptions may have a greater impact on work outcomes than work perceptions.-

Based on the above research, we expect that individuals who perceive training as play will experience greater positive outcomes than those who perceive it as work. This positive effect is expected regardless of whether perceptions are a function of individual attributes or social context. In addition, play perceptions are expected to have a greater influence on training outcomes than work perceptions. Therefore we hypothesize the following:

Hypothesis 1: Trainees' perceptions of computer training as play will more positively and significantly affect training outcomes (e.g., learning) than their perceptions of training as work.

We have suggested that individuals' perceptions of a task as work or play may be the result of individual difference characteristics as well as social contextual factors. Specifically, previous research has found that having a trainer label a task as work-versus-play influenced training outcomes (Webster et al., 1990; Webster & Martocchio, 1993). Therefore, it is likely that trainers can and often do influence individuals' perceptions of the task as work-versus-play. This might occur because of the trainer's labeling of the task as well as his or her presentation of the material and behavior during the training. For example, some research suggests that behavior modeling can have particularly positive implications for learning computer software (e.g., Gist et al., 1989). Therefore, we hypothesize the following:

Hypothesis 2: Trainees' perceptions of the training as work and play will be influenced by the trainer. Specifically, trainees' perceptions of the training as play should be high when the trainer is perceived to have a high play orientation. Trainees' perceptions of the train-

ing as work should be high when the trainer is perceived to have a high work orientation.

We suggested earlier that individuals have cognitive categories for work and play. These categories provide expectations that guide the understanding of new information (Fiske & Taylor, 1991). As a result, individuals are likely to have expectations about the extent to which training will be like work or play prior to the start of the training. These expectations result from the priming of one category or the other. Work- and-play categories may be activated by the social context. For example, individuals who have previously taken the training course may tell current trainees what they thought of the training. Alternatively, work-and-play categories may be activated by individual level attributes. For example, those who have a higher level of the playfulness trait may have a play category that is chronically activated. Research suggests that pre-training expectations are likely to influence training outcomes and therefore are often statistically controlled (Martocchio, 1992; Web- ster & Martocchio, 1993).

However, while researchers have called for research exploring the moderating effects of individual differences on work-and-play labeling (Cellar & Barrett, 1987; Tang & Baumeister, 1984), little research has directly explored the extent to which pre-training work-and-play expectations are moderated by trainer work- and- play orientation. We suggest that individuals' pre-training expectations about the extent to which the task will be like work or play will interact with perceptions of the trainer's orientation (perceptions that the trainer made the training seem like work or play) to influence training outcomes such as learning. It seems logical to predict that individuals whose expectations are consistent with perceptions of the trainer's work and play orientation will have more positive outcomes than those whose expectations are inconsistent.

Consistent with this, Tang and Baumeister (1984) found that individuals with a high work ethic showed greater intrinsic motivation on a task labeled work-versus-play than those with a lower work ethic. The effect was eliminated or reversed when the task was labeled leisure (i.e., play). To the extent that worker values (e.g., work ethic) are correlated with task expectations, this suggests that exl-Jctations that are


fulfilled will have more positive consequences than expectations that are unfulfilled. In addition, previous research suggests that play perceptions may, have more positive and significant effects on training outcomes than work perceptions (e.g., Cellar & Barrett, 1987). Therefore, the extent to which trainees' play expectations are fulfilled or unfulfilled should have a greater effect on training outcomes than work expectations. We therefore posit the following hypothesis:

Hypothesis 3: Training outcomes (e.g., learning) will be more positive when trainees' pre- training work-and-play expectations are consistent with perceptions of the trainer's work- and-play orientation than when they are inconsistent. The extent to which play expectations are fulfilled or unfulfilled will have a stronger influence on training outcomes than the extent to which work expectations are fulfilled or unfulfilled.

Research suggests that playfulness encom- passes cognitive (e.g., cognitive playfulness), affective (e.g., manifest joy), and behavioral (e.g., physical spontaneity) components (Bar- nett, 1990; Glynn & Webster, 1992). Webster and Martocchio (1992) argued that cognitive playfulness represents the most relevant aspect of playfulness in human-computer interactions and have studied it to the exclusion of other dimensions. However, they suggest that further investigation should be made to determine whether other dimensions of playfulness are relevant in human-computer interactions.

Some theorists have suggested that play and fun are not synonymous. Specifically, Biesty (1986) notes that recent work has confused play with fun. Because something is fun does not mean that it is play. The notion that play and fun are related but not necessarily completely overlapping concepts is suggested in research by Glynn and Webster (1992) and Abramis (1990). Glynn and Webster (1992) found that a measure of playfulness was comprised of five factors, one of which was fun. Abramis (1990) found that one measure of play was positively, significantly, and highly correlated with six measures of various aspects of fun. This research and theory suggests that perceptions of a task as fun may be significantly correlated with, but distinct from, perceptions of a task as work or play.

If perceptions of a task as work, play, and fun are distinct, it is not entirely clear how they may be related to one another and how they influence training outcomes relative to one another. Although no firm hypotheses are offered, we expect that individuals form perceptions of training tasks as work, play, and fun and that these perceptions independently affect learning.

The Study

The current research was a field study of MBA students enrolled in a compulsory software- training module. Questionnaires asking trainees about their work-and-play related expectations and perceptions of the training were administered prior to and following the training module respectively. A field study was used because we were primarily interested in describ- ing how individuals spontaneously and naturally perceive training contexts, the extent to which these perceptions are influenced by trainers, and the extent to which these perceptions influence learning in training.

The Method

Sample Participants in this study were 75 first-year MBA students at a large midwestern university. This sample consisted of 52 males and 23 females with an average age of 25.48 years and an average of 2.46 years of work experience. These individuals were enrolled in a compulsory software-training module which covered Micro- soft Excel 5.0.1 Although all first-year MBA students were required to attend this training module, students could exempt out if they passed a competency test.

Procedure First-year MBA students at this university are required to participate in a series of compulsory microcomputer software-training modules cover- ing a variety of software packages (e.g., word- processing, presentation graphics, spread- sheet). The MBA training coordinator was con- tacted by the experimenters and agreed to allow the experimenters access to first-year MBA students prior to and following their participation

1Microsoft Excel 5.0, Copyright by Microsoft Corporation, 1985-1993. All rights reserved.

98 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)

in one training module. The Excel training module was selected primarily because the training coordinator believed that this module would allow the most time for the study and because the experimenters' presence would be least disruptive in this module. Subjects partici- pating in this module were assigned to one of seven sections each of which was taught by a different "head" trainer. A total of 273 students was enrolled in the Excel training module.

Prior to the start of the Excel training module, two assistants administered a questionnaire to all of the individuals present in each of the seven training sections. A cover letter from the experimenters was attached to the questionnaires stating that the purpose of the study was to "better understand how people approach training and learn in training programs." The letter also indicated that participation in this study was voluntary and that all requested information would be kept confidential.

One hundred and sixty-eight individuals (61% of the total enrolled) returned completed pre- training questionnaires. The Excel training module consisted of approximately five sessions which took place over a five-week period. At the completion of this module, the same two assistants administered a questionnaire to all of the individuals present in each of the seven training sections. One hundred and two individuals completed the post-training questionnaire (37% of the total enrolled). Only those trainees who returned both the pre- and post-training questionnaires were included in the study analyses. The total number of trainees who completed both the pre- and post-training questionnaires was 77 (28% of the total enrolled). Two subjects' data were eliminated because they made ratings off of the rating scales, resulting in a final sample size of 75.

The MBA training coordinator requested that administration of the questionnaires take no more than fifteen minutes of the training class. Therefore, there were limitations on the number of questions that trainees could be asked. The questionnaires collected information about work, play, and fun expectations and perceptions, control variables (e.g., microcomputer experience, computer anxiety), and the dependent measure. Because the primary objective of this training module was to increase learning, learning was the dependent measure used in this

research. Learning was assessed by an Excel quiz which was included in both the pre- and post-training questionnaires. Two versions of the pre-training and post-training questionnaires were given to trainees. These versions differed only in the order in which measures were collected. In addition, the order of the items on the Excel quiz was randomly determined and was different in the pre-training and post-training questionnaires.

Measures

Pre-training Play Expectations Two items measured the extent to which subjects expected the computer training to be like "play." These items included: "To what extent do you expect the Excel training to be like 'play'?" (1 = Not at all like play; 7 = Very much like play) and "To what extent do you expect it to feel like you are playing in the Excel training?" (1 = Not at all; 7 = Very much). These items were averaged to form a pre-training play expectations scale (r = .65, io < .01).

Pre-training Work Expectations Two items measured the extent to which subjects expected the computer training to be like "work." These items included: "To what extent do you expect the Excel training to be like 'work'?" (1 = Not at all like work; 7 = Very much like work) and "To what extent do you expect it to feel like you are working in the Excel training?" (1 = Not at all; 7 = Very much). These items were averaged to form a pre-training work expectations scale (_r = .46, 12 < .01 ).

Post-training Play Perceptions Two items, parallel to those used in the pre- training play expectations scalel were asked following the completion of the Excel training module. These items included: "To what extent was the Excel training like 'play'.'?" (1 = Not at all like play; 7 = Very much like play) and "To what extent did it feel like you were playing in the Excel training?" (1 = Not at all; 7 = Very much). These items were averaged to form a post- training play perceptions scale (_r = .69, 12 < .01 ).

Post-training Work Perceptions Two items, parallel to those used in the pre- training work expectations scale, were asked following the completion of the Excel training module. These items included: "To what extent was the Excel training like 'work'?" (1 = Not at


all like work; 7 = Very much like work) and "To what extent did it feel like you were working in the Excel training?" (1 = Netat all; 7 = Vey nuah). These items were averaged to form a post- training work perceptions scale (.[ = .75, 1o < .01).

Post-training Fun Perceptions Two items measured the extent to which subjects perceived the training to be fun. These items included: "ro what extent was the Excel training fun?" (1 = Not at all fun; 7 = Very fun) and "How enjoyable was the Excel training?" (1 = Not at all enjoyable; 7 = Extremely enjoyable). These items were averaged to form a post- training fun perceptions scale (_r = .84, 12 < .01 ).

Trainer Work-Versus-Play Orientation Two questions on the post-training questionnaire asked subjects to indicate the extent to which they perceived that the training instructors made the Excel training seem like work and play respectively. One item assessed trainer play orientation, "To what extent did your instructors make the Excel training seem like play?" (1 = Not at all; 7 = Very much). The other item assessed trainer work orientation, "To what extent did your instructors make the Excel training seem like work?" (1 = Not at all; 7 = Very much).

A number of control measures were also collected on the pre-training questionnaire. These measures are consistent with those used in related research (e.g., Martocchio & Webster, 1992; Webster & Martocchio, 1993). These measures are described next.

PC knowledge Two items were used to assess the extent to which individuals were knowledgeable about personal computers. These items included: "How skilled are you at using PCs?" (1 = Not at all skilled; 7 = Extremely skilled) and "How much experience have ,.you had using PCs~ (1 = No experience at all; 7 = A great deal of experience). These items were averaged to form a PC-knowledge scale (r = .86, 12 < .01).

Excel Knowledge Three items were used to assess the extent to which individuals were knowledgeable about Ex- cel. These items included: "How skilled are you at using Excel?" (.1 = Not at all skilled; 7 = Ex- tremely skilled); "How much experience have you had using Excel?" (1 = No experience at all; 7 = A great deal of experience); and "How knowledgeable are you about Excel?" (1 = Not

at all knowledgeable; 7 = Extremely knowledgeable). These items were averaged to form an Excel knowledge scale (Cronbach's alpha = .96).

Computer Anxiety Ten items adapted from Heinssen, Glass, and Knight (1987) were used to assess computer anxiety. A typical item on this scale was, "1 feel insecure about my ability to interpret a computer printout" (1 = Strongly disagree; 5 = Strongly Agree). These items were averaged to form a computer anxiety scale (Cronbach's alpha = .83). Higher values indicate more computer anxiety.

Motivation Seven items were used to assess pre-training motivation for the Excel training. These items were adapted from Baldwin and Karl (1987). A sample item is, "1 am willing to exert consider- able effort to improve my skills in the upcoming Excel training module" (1 = Strongly disagree; 7 = Strongly agree). These items were averaged to form a motivation scale (Cronbach's alpha = .85). Higher values indicate more motivation.

Demographic Information Demographic information was collected for des- criptive purposes only. Subjects were asked to indicate their age, sex, and years of full-time work experience.

Learning The same ten-item, multiple-choice quiz assessing Excel knowledge was administered prior to and following the Excel training module. The content of the quiz was developed by the experimenters with the help of the MBA training coordinator based on actual competency tests used by the training program in previous years. Items on the quiz were scored 0 = incorrect or 1 = correct. The total number of items answered correctly was summed to form a measure of quiz performance at both pre- and post-training. Learning was measured as post-training quiz performance controlling for pre-training quiz performance.

Results

Correlations among Study Measures

A correlation matrix which includes the study measures is located in Table 1. This table reveals several significant and interesting


Variables 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Play - .14 .63"* .64"* .10 .27" .06 .07 -.03 -.16 .09 -.03 -.04 Perceptions

2. Work .25" .21 .67** -.02 .53** .23* -.23* -.41"* .40** -.21 -.12 Perceptions

3. Fun - .55"* .22 .02 .08 .06 .01 -.12 .22 -.10 .13 Perceptions

4. Trainer Play Orientation

5. Trainer Work Orientation

-.03 .05 .03 -.05 .04 -.12 .10 -.06 .13

-.01 .43** .36** -.18 -.24* .33** -.19 -.32**

6. Play -,18 -.12 .13 .16 .18 .17 -.03 Expectations

7. Work .25" -.16 -.43"* -.43" -,23" -.16 Expectations

8. Computer -.54"* -.49"* .15 -.39"* -.40"* Anxiety

9. Pc .55** -.06 .48** .20 Knowledge

10. Excel -.36"* .64** .20 Knowledge

11. Motivation

12. Pre-Training Quiz Performance

13, Post-Training Quiz Performance

-.03 .01

.30"*

** 12 < .01, * 12 < .05, two-tailed

Table 1. Correlations among Study Measures

correlations. First, post-training fun perceptions were significantly and positively correlated with both post-training play and post-training work perceptions although the former correlation is higher and more significant than the latter. This is consistent with research and theory that suggests that fun and play are not necessarily equivalent concepts and that both work and play may be fun. Second, this matrix reveals that computer anxiety is negatively and significantly

correlated with PC and Excel knowledge and pre- and post-training Excel quiz performance. This is consistent with research that finds that computer anxiety can have negative implications for learning (e.g., Heinssen et al., 1987; Martocchio, 1992; and Martocchio & Webster, 1992). Third, a positive and significant correlation was found between computer anxiety and post-training work perceptions and pre-training work expectations. This suggests that indi-


viduals who werE; more anxious about computers were more likely to perceive computer training as work. This finding is consistent with research suggesting that work perceptions are less likely to be .associated with positive outcomes than play perceptions.

Effects of Work-and-Play Perceptions on Learning

To test Hypothesis; 1 and examine the effects of perceptions of work compared to play on training program learning, two, two-step hierarchical regression analyses were conducted. In the first hierarchical regression analysis, all control variables were entered in the first step and the post-training play perceptions scale was entered in the second step. The control variables included: computer anxiety, PC knowledge, Excel knowledge, motivation, and pre-training quiz performance.

In the second, two-step hierarchical regression analysis, the control variables were entered in the first step and the post-training work perceptions scale was entered in the second step. The increase in r 2 contributed by each step is of particular interest (Horn, Griffith, & Sellaro, 1984). if the r 2 change is significant, it suggests that the associated step accounts for a substantial amount of additional variance in the dependent variable. These analyses are summarized in Table 2.

In the first two-step hierarchical regression analysis, the first step in the analysis was significant, indicating a significant main effect of the control variables on learning. Specifically, computer anxiety was found to have a significant and negative effect on learning. However, the second step in this analysis did not account for a significant increase in variance. Post-training perceptions of the extent to which the training was like play did not influence learning in the training beyond the effects of the control variables.

In the second, two-step hierarchical regression analysis, the first step was the same as that reported for the first hierarchical regression analysis. Of particular interest is the second step which did not account for a significant increase in variance. Post-training perceptions of the extent to which the training was like work did not influence learning in training beyond the effects of the control variables. These results do not support Hypothesis 1 which predicted that perceptions of the training as play would positively and significantly influence learning and would do so to a greater extent than perceptions of the training as work. These analyses suggest that while the model appears to account for a significant amount of variance in learning, neither play nor work perceptions accounted for additional variance in learning beyond the effects of the control variables.

Step Independent Measure " beta r 2 &r2

(1)

(2)

(2)

(2)

Computer Anxiety -.40"* PC Knowledge -.09 Excel Knowledge -.09 Motivation .04 Pre-Training Quiz Performance .24t

Play Perceptions -.03

Work Perceptions -.07

.20"* .20"*

.20" .00

.20" .00

Play Perceptions -.23t Fun Pemeptions .32" .26"* .06t

**]2<.01, *D<.05, t l ~< .10

Table 2. Hierarchical Regression Analyses on Leaming


Work, Play, and Fun Perceptions

Analyses were conducted to determine the relationship between work, play, and fun perceptions and how these perceptions, in turn, influenced ]earning in training. First, correlation analyses indicated that the correlation between post-training pray and fun perceptions was positive and significant (_r = .63, p < .01 ) as was the correlation between post-training work and fun perceptions (r = .25, p < .05). This pattern of results is consistent with the contention that fun is more highly correlated with play compared to work (Dandridge, 1986). Results are also consistent with research by Abramis (1990) which found that a measure of play was signi- ficentiy and highly correlated with six measures of various aspects of fun (_r = .37 - .52).

Second, a regression analysis was conducted which regressed post-training quiz performance on the five control variables (computer anxiety, PC knowledge, Excel knowledge, motivation, and pre-training quiz performance), and the post-training work, play, and fun perception scales. The results of this regression analysis are summarized in Table 3. This analysis revealed that the variables explained a significant amount of variance in learning (r 2= .27, .o < .01 ).

Computer anxiety was found to have a significant and negative effect on learning, while pre- training quiz performance had a positive and significant effect on post-training quiz performance. In addition, this analysis revealed a marginal and negative effect of post-training

Variable beta Computer Anxiety -.40"* PC Knowledge -. 11 Excel Knowledge -. 19 Motivation .00 Pre-Training Quiz Performance .32* Play Perceptions -.24t Work Perceptions -. 12 Fun Perceptions .35"

r 2 .27**

**1::)<.01, *p< .05 , t P < . 1 0

Table 3. Regression Analysis Exploring the Effects of Post-training Work, Play,

and Fun Perceptions on Learning

play perceptions (beta = -.24, 12 < .10) and a significant and positive effect of post training fun perceptions on learning (beta = .35, p < .05). Post-training work perceptions did not have a significant effect on learning.

This and the correlation analyses indicate that the post-training play perceptions measure operated as a suppressor variable (Cascio, 1991; Pedhazur, 1982). First, post-training play and fun perceptions were positively and significantly correlated with each other. Second, post-training perceptions of play had a near zero correlation with the criterion (post-training quiz performance). Third, when the post- training play perceptions scale was entered into the regression equation, the coefficient on the post-training fun perceptions scale increased (from .19 to .35), r 2 increased (from .23 to .27), and the coefficient on the post-training play per- captions scale was negative and marginally significant (beta = -.24, p < .10).

This series of analyses suggests that fun and play perceptions are related but not necessarily equivalent concepts. In light of these results, a two-step hierarchical regression analysis was conducted to determine whether post-training play and fun perceptions together accounted for a significant amount of additional variance in learning beyond the effects of the control variables. In the first step, the control variables were entered (computer anxiety, PC knowledge, Excel knowledge, motivation, and pre-training quiz performance). In the second step, both the post-training play and fun perceptions scales were entered. The results are reported in Table 2. The analyses indicate that the second step accounted for a marginally significant amount of additional variance in learning. In addition, consistent with earlier analyses, post-training play perceptions had a marginally significant but negative effect on learning while post-training fun perceptions had a significant and positive effect on learning.

Trainer Effects

Hypothesis 2 predicted that trainees' perceptions of the training as work and play would be influenced by the trainer. We predicted that trainees' play perceptions would be high when their trainer was perceived to have a high play orientation and trainees' work perceptions would be high when their trainer was perceived to

The DATA BASE for Advances in Information S y s t e m s - Spring 1997 (Vol. 28, No. 2) 103

Variable

Trainer Play Orientation Trainer Work Orientation

Play Perceptions

beta r 2 .64"* • 12 .42.*


Work Perceptions .23** .67"* .49**


Fun Perceptions .55** .23" .35"*

*'12<.01, *10<.05, 1"12<.10

Table 4. Regression Analyses Exploring the Effects of Trainer Work-and-Play Orientation on Post-training Work, Play, and Fun Perceptions

have a high work orientation. In order to test this hypothesis, a number of analyses were conducted.

First, post-training work-and-play perceptions scales respectively were regressed on the two items that measured perceptions of the trainer's work and play orientation. The first question asked trainees to indicate the extent to which the trainers made the Excel training seem like work and the second question asked trainees to indicate the extent to which the trainers made the Excel training seem like play. Results of this analysis are presented in Table 4. Consistent with Hypothesis 2, results indicated that post- training play perceptions were significantly influenced by perceptions of the trainer's play orientation. Also consistent with Hypothesis 2, post-training work perceptions were significantly influenced by perceptions of the trainer's work orientation. Although unanticipated, this analysis also revealed that post-training work perceptions were significantly influenced by perceptions of the trainer's play orientation. Finally, even though we did not hypothesize that instructor orientation would influence post- training perceptions of fun, we conducted additional analyses to explore this possibility. Analyses revealed that post-training fun perceptions were significantly influenced by perceptions of both the trainer's work and play orientation.

Second, four additional regression analyses were conducted which regressed pre-training play expectations, pre-training work expect-

ations, post-training play perceptions, and post- training work perceptions respectively on the training section, which was dummy coded. Re- call that subjects were assigned to one of seven training sessions each of which had a different head trainer. Analyses revealed that there was no main effect of section on the pre-training play expectations F(6, 68) = 1.30, 2 = ns, r 2 = .10, or pre-training work expectations scales F(6, 68) = .58, 12 = ns, r 2 = .05. However, a main effect of section was found on the post-training play perceptions scale F(6, 68) = 2.90, 13 < .05, r~= .20, but not the post-training work perceptions scale F(6, 68) = 1.18, p = ns, r 2 = .09. Third, additional correlation analyses suggested that training section was significantly correlated with trainer play orientation (r = .31, 12 < .01), but not trainer work orientation (r = .00, 1o = ns).

Together these analyses suggest that social context (e.g., trainers) can influence trainees' work and play perceptions even in the absence of explicit instructions to label tasks as work- versus-play.

Trainee by Trainer Interaction Effects

Hypotheses 3 predicted that trainees' pre- training expectations of the task as work or play would interact with trainer work and play orientation to influence training outcomes. Spe- cifically, we predicted that training outcomes (learning) would be more positive when trainees' expectations about whether the task would be like work and play were consistent with their perceptions of whether the trainer in


fact made the task seem like work and play. Additionally, we suggested that the fulfillment or lack of fulfillment of play expectations was likely to have a greater effect on learning than the fulfillment or lack of fulfillment of work expectations.

In order to test this hypothesis, a regression analysis was conducted in which post-training quiz performance was regressed on the control variables (computer anxiety, PC knowledge, Ex- cel knowledge, motivation, and pre-training quiz performance), pre-training work and play expectations, trainer work-and-play orientation, and the four relevant two-way interactions between trainees' work-and-play expectations and trainer work-and-play orientation. This regression analysis is reported in Table 5.

Analyses suggest that these variables accounted for a significant amount of variance in learning (r 2 = .34, P < .05). Results revealed a marginally significant and negative effect of computer anxiety on learning. In addition, a significant and negative effect for one of the two-way interactions was found (pre-training play expectations x trainer-work orientation). Following procedures recommended by Peters, O'Connor, and Wise (1984) we used within- subgroup regression equations to examine this interaction. First, high play expectation and low play expectation conditions were created by doing a median split on the pre-training play expectations scale. Next, equations regressing post-training quiz performance on trainer work orientation were plotted for the high and low play expectation conditions using unstan- dardized regression coefficients. This plot is shown in Figure 1.

Consistent with Hypothesis 3, this figure indicates that subjects learned less when their pre-training play expectations were high and they perceived that the trainer made the training seem more like work. However, the interaction between pre-training play expectations and trainer play orientation was not significant. Consequently, only partial support was found for Hypothesis 3. These results suggest that unfulfilled play expectations have a greater impact on learning than fulfilled play expectations.

Discussion

This research explored the effects of work, play, and fun perceptions of computer training on

Variable Beta Computer Anxiety -.25? PC Knowledge -. 11 Excel Knowledge -.03 Motivation .14 Pre-Training Quiz Performance .24 Play Expectations (PE) .13 Work Expectations (WE) -.28 Trainer Play Orientation (TP) -. 12 Trainer Work Orientation (TW) .29 PE x TP .63 PE x TW -1.11" WE x TP -.08 WE x TW .43 R 2 .34" *P < .05, t P < . 1 0

Table 5. Regression Analyses Exploring the Independent and Combined Effects of Pre- training Work and Play Expectations and

Trainer Work and Play Orientation on Learning

learning in a field study. The main findings of this research are reviewed next.

Effects of Work-and-Play Perceptions on Leaming

We predicted that perceptions of the training as play would more positively and significantly affect learning than perceptions of the training as work after controlling for a number of factors (Hypothesis 1). However, contrary to prediction, perceptions of the computer training as play did not account for a significant amount of additional variance in learning after controlling for computer anxiety, PC knowledge, Excel knowledge, motivation, and pre-training quiz performance. As expected, perceptions of the training as work did not account for a significant amount of additional variance in learning beyond the effects of the control variables. These findings are inconsistent with prior research which finds that labeling computer training play positively influences training outcomes (Web- ster et al., 1990; Webster & Martocchio, 1993).

One explanation for the lack of effect for play perceptions in the current study is that individuals' perceptions of play may be especially predictive when trainers explicitly label computer training tasks. Prior research that has explored the effects of labeling in computer training has explicitly manipulated task labels.


Explicit manipulations of tasks as work or play are likely to prime individuals' work and play categories and influence training outcomes. In the current study, perceptions were measured and not manipulalled. This suggests that perceptions of a task as play may be less influential when the social context does not consistently and explicitly m~=ke task labels salient. A second explanation for the lack of effect for play perceptions is suggested by the research of Webster and Martocchio (1993) which found that the effects ,of labeling training play on learning were moderated by an individual difference characteristic (i.e., age). This research suggests that play perceptions may only have beneficial el~ects for certain types of individuals obscuring a main effect in the present study.

Work, Play, and Fun Perceptions

Further analysis of the data suggested that play perceptions did in fact influence learning but did so in a complicated manner. The current study measured the extent to which trainees perceived the training as work, play, and fun in order to determine the relationship between these perceptions and to assess their relative

influence on training outcomes. Learning was regressed on a number of control variables, and post-training work, play, and fun perceptions. Results of this regression analysis and correlation analyses indicated that the post-training play perceptions measure operated as a suppressor variable (Cascio, 1991; Pedhazur, 1982). Specifically, post-training perceptions of fun appeared to have a significant and positive effect on learning while post-training perceptions of play had a marginally significant and negative effect on learning. No significant effect was found for post-training work perceptions.

The current results suggest that perceptions of the task as play had a negative effect on learning in the training. This may be because individuals who perceived the training as play perceived it to be less serious or important and therefore performed less well. On the other hand, those who perceived the training as fun found the training enjoyable, may have been more motivated to perform in the training, and learned more. This interpretation is consistent with the pattern of correlations that reveals that pre-training motivation was more highly and positively correlated with post-training fun

10- 9 8

Post-training Quiz 7

Performance 6

(Number of 5 correct ~tem~) 4"

3

2 1 0

0

- . . .

I I '1 ' I I

1 2 3 4 5 Low Orientation Trainer Work Orientation

I : : 6 ? 8

High Orientation

Figure 1. Interaction Between Pre-training Play Expectat ions and Trainer Work Orientation on Learning


perceptions (r = .22, 12 = ns) than post-training play perceptions (r = .09, 12 = ns) although neither of these correlations is significant. This interpretation is also consistent with the finding that post-training work perceptions were more highly correlated with post-training fun perceptions (r = .25, 12 < .05) than post-training play perceptions (r = .14, 12 = ns) and that post- training work perceptions were highly and positively correlated with motivation (r = .40, p_ < .01).

The suppressor effect suggests that play and fun perceptions were highly related but perceptions of the training as fun were beneficial while perceptions of the training as play were not. This pattern of results is consistent with research and theory that suggests that play and fun are not necessarily equivalent concepts and that work as well as play may be fun (Abramis, 1990; Biesty, 1986; Burke, 1971; Glynn and Webster, 1992). It is also consistent with the finding that a play orientation can in some cir- cumstances have negative effects (e.g., San- delands, 1988; Schuck, 1985).

Trainer Effects

Results suggest that trainers influenced trainees' work-and-play perceptions. This was indicated by a number of analyses. First, work and play perceptions respectively were regressed on perceptions that the trainer made the training seem like work and like play. These analyses indicated that trainer work orientation influenced trainees' perceptions of the training as work and trainer play orientation influenced trainees' perceptions of the training as play. Additional analyses also revealed that trainer orientation significantly influenced post-training fun perceptions.

Second, results revealed no differences between training sections on work-and-play expectations prior to the start of training. How- ever, following the training, differences in play perceptions among training sections were found. Third, the training section was significantly correlated with trainer play orientation. Although training- section effects may have also resulted from other aspects of the training context (e.g., classmates), the pattern of results presented suggests that trainers influenced trainees' perceptions of the task. The assumption that section differences are

primarily driven by differences between trainers appears reasonable in light of the first set of analyses showing the direct effect of trainer orientation on trainees' work, play, and fun perceptions. This assumption is also consistent with the fact that the training module material and computer resources were standardized across sections.

Trainee by Trainer Interaction Effects

Hypothesis 3 suggested that trainees' pre- training expectations about whether the task would be like work or play would interact with trainer orientation, whether trainees perceived the trainer made the task seem like work or play, to influence learning. Specifically, we suggested that pre-training work-and-play expectations that were consistent with perceptions of the trainer's work-and-play orientation would have a positive influence on learning, while expectations that were inconsistent with the trainers orientation would have a negative influence on learning. Further, we anticipated that the fulfillment or lack of fulfillment of play expectations would have a greater effect on learning than the fulfillment or lack of fulfillment of work expectations. Partial support for this hypothesis was found.

A regression analysis was conducted which regressed learning on the control variables, work- and-play expectations, trainer work-and-play orientation, and the interactions between trainee work-and-play expectations and trainer work- and-play orientation. The regression accounted for a significant amount of variance in learning and indicated that one interaction term had a significant and negative effect on learning. Spe- cifically, trainees who had higher play expectations learned less when they perceived that their trainer made the training seem more like work. Contrary to expectation, no evidence was found for a play expectations x trainer play orientation interaction, suggesting that unfulfilled play expectations had a greater influence on learning than fulfilled expectations. Finally, as expected, there was little evidence that the fulfillment or lack of fulfillment of trainees' work expectations influenced learning. These analyses suggest that the trainer may play an important role in the context of computer training.


Implications

First, current results suggest that perceptions of a task as play may, not necessarily have a positive effect and may even have a negative effect on learning. Our results suggest that perceptions of training as fun may have more positive and beneficial effects on learning than perceptions of the training as play or work. The post-training play perceptions measure appeared to operate as a suppressor variable, in- creasing the positiive effect of post-training fun perceptions on learning. Perceptions of the training as play may have been accompanied by perceptions that the training was tess serious or important. In contrast, perceptions of the training as fun appeared to be more highly and positively correlated with pre-training motivation and work perceptions.

The current results suggest that it is particularly important that trainees perceive training as fun but not necessarily as play. This could be accomplished by having trainers explicitly label training situations as fun. Research by Webster and Martocchio (1993) suggests that this might be accomplished in a fairly straightforward manner. Fun and enjoyable aspects of the training could be highlighted for trainees by the trainer or training material.

Second, study results suggest that social context appears to have an influence on trainees' perceptions of the training as work or play. Specifically, trainers appeared to influence trainees' work, play, and fun perceptions. To the extent that these perceptions affect learning, trainer influence is important. These findings suggest that trainers may be able to shape perceptions in a way that can have a significant and positive influence on learning. For example, current results suggest that trainers can shape the extent to which trainees perceive training as fun and thus positively influence learning. This can be done by having trainers behave in particular ways (e.g., model certain types of behavior), or by specifically labeling training fun. The influence of trainers in the context of training is not always acknowledged nor is it aT~vays intentional. Current results suggest that trainers are likely to differ in the extent to which they influence trainees' perceptions of the training (as work, play, and fun) in the absence of specific instructions to

label training contexts. This may suggest that trainers need to be aware of how they influence trainees' work, play, and fun perceptions and learn how to intentionally influence these perceptions.

Third, current results revealed that the extent to which there was congruence between trainees' expectations that the training would be like work or play and perceptions that the trainer made the training seem like work or play influenced learning. Specifically, results indicated that when individuals expected the training to be like play and they perceived that the trainer made it seem more like work, learning was negatively affected. This suggests that trainers should attempt to assess and in some cases influence trainees' pre-training expectations. It is likely that many trainees have inappropriate and unrealistic expectations about the training. In addition, this finding suggests that trainers may need to alter their behavior (where appropriate) to reduce the potential for unfulfilled training expectations. Therefore, these results suggest that it is important that trainers understand trainees' expectations, make sure that they are accurate and realistic, and behave in a manner that is consistent with these expectations.

Finally, while trainers appeared to influence trainees' perceptions and learning, the current study also found some evidence that individual difference factors played an important role in learning. Specifically, subjects who experienced a greater amount of computer anxiety did less well on the Excel quizzes. This finding is consistent with previous research that finds that computer anxiety can have detrimental effects on learning (e.g., Heinssen et al., 1987; Martoc- chio, 1992; and Martocchio & Webster, 1992). This result suggests that it is important to consider the role of individual difference factors as well as social contextual factors in microcomputer training. This might suggest that trainers assess the extent to which individuals are anxious about computer training and take steps to alleviate this anxiety (e.g., showing trainees that they are unlikely to break the computer).

Limitations and Future Research

These research results should be interpreted in the context of several of the study's limitations.


First, and most importantly, this research was a field study. Consequently, the external validity of this study is quite high, while internal validity is likely to be lower due to the lack of experimental control. Because much of the previous research on work-and-play orientation in computer training has been experimental in nature, we chose to conduct a field study. However, this research was relational and exploratory in nature and therefore few causal claims can be made. For example, we cannot conclude that work and play perceptions were influenced by trainer work-and- play orientation based solely on the regression analyses reported in Table 4.

One could argue that work and play perceptions influenced perceptions of the extent to which trainers made the task seem like work or play. Therefore, wherever possible, we included additional analyses to help isolate the nature of the effects that were found. For example, in order to provide additional evidence that trainers influenced trainees' work-and-play perceptions, we looked for differences in these perceptions by training section before and after the training. In addition, we believe that it is reasonable to conclude that perceptions of play and fun influenced learning and not the reverse for two reasons. First, subjects did not know how well they scored on either the pre- or the post-training Excel quiz. It is difficult to imagine how learning would influence perceptions of the task if subjects were not told how much they learned. Second, previous experimental research provides evidence that task perceptions (e.g., play perceptions) influence learning.

Although 273 individuals were enrolled in the Excel training module, only 75 individuals provided complete and usable pre- and post-training questionnaires. This participation rate was low and is likely due to two factors. First, trainees believed that they could skip a training class when they were familiar with the material covered on that day. Second, the post-training questionnaire was administered close to students' midterm exams. This was unavoidable because the timing of both the training and exams was determined by the MBA department.

It is not clear how representative these 75 individuals are of the entire MBA program or of other individuals who are likely to take computer training classes. Additionally, the sample size

was small in the context of some of our analyses which included a relatively large number of variables. However, while a relatively small sample may limit our ability to detect small effects, it also increases our confidence in the effects we did find. Effects must be quite large to be detected in small samples using con- ventional levels of statistical significance (Co- hen, 1988).

Future research should explore work, play, and fun perceptions of more and different types of subjects. For example, current study subjects had some familiarity with micro-computers because they had already taken several training modules prior to the Excel module. Thus, effects found in this study may not generalize to less experienced trainees. However, we believe that these findings have implications for organizations. Study subjects had some work experience and organizations offer their employees software training similar to that provided in the current study (e.g., Ballou & Rush, 1996).

The current study explored work, play, and fun perceptions following subjects' participation in an Excel training module. However, this training module was the fourth module to be covered in a series of modules. It is possible that the effects found in the current study might not be found in other types of computer-based training. Certain types of software may require more creativity, spontaneity, and imagination to use (e.g., graphics software packages). We would predict that perceptions of the task as play might be even more important in these training contexts.

In addition, computer training on non-computer related topics (e.g., problem-solving) may differ from training on computer applications such as Excel. It is also unclear how work-and-play perceptions may have differed across the training modules. It might be that perceptions of the training changed as the content of the training changed and as trainees' exposure to the trainer increased. Consequently, future research should explore work, play, and fun perceptions in the context of different types of microcomputer training and observe how these perceptions change over time as a function of the content of the training and the nature of the trainees' relationship with the trainer. It is also important to explore the extent to which work, play, and fun perceptions at different points


during the training are predictive of important training outcomes.

The current research used a multiple-item quiz administered prior' to and following the Excel training to measure learning. However, it would be useful to expllore other types of learning measures in futu~re research. For example, future research might explore the speed with which learned skills are executed in a simulated work task. In addition, it may also be important to explore the number of errors made in the execution of learned skills. Processing speed and errors measured in human-computer interaction research can provide additional information about the extent to which computer skills and knowledge are well-learned (e.g., Card, Moran, & Newell, 1983; Rubinstein & Hersh, 1984).

In addition, future research should develop and assess construct valid measures of work, play, and fun perceptions in the context of computer training. The current research was exploratory in nature and suggests that work, play, and fun perceptions are distinct but correlated. How- ever, this study does not provide detailed information regarding the basis of these perceptions or the nature of the relationship between these perceptions. In light of current study results, it is important to explore the nature of work, play, and fun perceptions in some detail and to determine whether the concepts of play and fun are in fact separable entities that influence learning differently. This requires greater attention to the measurement of work, play, and fun perceptions in future research.

The current study suggests that trainers can have a strong influence on trainees' perceptions of training as work, play, or fun, with a resulting impact on learning. However, it would be interesting to explore the effects of computer-based training which effectively eliminates the role of the trainer on trainees' work, play, and fun perceptions and learning. It may be the case that software-based training is more or less like work, play, or fun than human-led training. The extent to which there are differences between the two types of training suggests the following questions: Are individual differences in pre- dispositions toward work, play, and fun more influential in human-led or computer-based training? Can computer-based training de- velopers incorporate cues into the training

software that shape trainees' perceptions and learning much as human trainers do? Future research is necessary to assess the differences between human-led and computer-based training and to determine the effect of incorporating the role of the trainer into the computer itself on training outcomes.

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About the Authors

Elissa L. Perry is an assistant professor of labor and industrial relations at the University of Illinois at Urbana-Champaign. She earned her M.S. and Ph.D. in organizational behavior and theory from Carnegie Mellon University. Pro- fessor Perry has research interests in the role of demographic variables in human resource judgments, social ,cognition and human resource decision making, individual differences and the training process, and sexual harassment. She has published articles in journals such as Academy of Management Review, Journal of Applied Psychology, and Journal of Applied Social Psychology'. E-mail: [email protected]

Deborah J. Ballou is an assistant professor in the Department of Management at the Univer- sity of Notre Dame. She earned her M.S. and Ph.D. in information systems from Carnegie Mellon University. Professor Ballou has research interests in the study of information acquisition and decision making as the basis for designing more effective computer-based support. The applied areas in which she has conducted most of her work are computer-based performance monitoring, and decision making in time-pressured, dynamic work environments. She has published articles in journals such as the Annals of Software Engineering, SIGCHI Bulletin, and Journal of Applied Social Psycho- Iogy. E-mail: [email protected]


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