Technical Report 1164 

The Influence of Trainee Gaming Experience and 

Computer Self-Efficacy on Learner Outcomes of 

Videogame-Based Learning Environments 

Karin A. Orvis 

George Mason University 

Consortium Research Fellows Program 

Kara L. Orvis 

Consortium Post-Doctoral Fellows

James Belanich 

U.S. Army Research Institute 

Laura N. Mullin 

The Catholic University of America 

Consortium Research Fellows Program 

 June 2005 

United States Army Research Institute 

for the Behavioral And Social Sciences 

 Approved for public release; distribution is unlimited
U.S. Army Research Institute 

for the Behavioral and Social Sciences 

A Directorate of the Department of the Army 

Deputy Chief of Staff, G1 

 ZITA M. SIMUTIS 

 Director 

Technical Review by 

Andrea Rittman Lassiter, Minnesota State University - Mankato 

Jennifer Solberg, U.S. Army Research Institute 

NOTICES 

DISTRIBUTION: Primary distribution of this Technical Report has been made by ARI. 

Please address correspondence concerning distribution of reports to: U.S. Army 

Research Institute for the Behavioral and Social Sciences, Attn: DAPE-ARI-MS, 

2511 Jefferson Davis Highway, Arlington, Virginia 22202-3926 

FINAL DISPOSITION: This Technical Report may be destroyed when it is no longer 

needed. Please do not return it to the U.S. Army Research Institute for the Behavioral 

and Social Sciences. 

NOTE: The findings in this Technical Report are not to be construed as an official 

Department of the Army position, unless so designated by other authorized documents. 
REPORT DOCUMENTATION PAGE

1. REPORT DATE (dd-mm-yy)

 June 2005 

2. REPORT TYPE

 Final 

3. DATES COVERED (from. . . to) 

 December 2003 - March 2005 

5a. CONTRACT OR GRANT NUMBER

 

4. TITLE AND SUBTITLE

The Influence of Trainee Gaming Experience and Computer SelfEfficacy on Learner Outcomes of Videogame-Based Learning 

Environments

5b. PROGRAM ELEMENT NUMBER 

 633007 

5c. PROJECT NUMBER

 A792 

6. AUTHOR(S) 

Karin A. Orvis (George Mason University), Kara L. Orvis

(Consortium Post-Doctoral Fellows), James Belanich (U.S. Army

Research Institute), and Laura N. Mullin (The Catholic University

of America)

5d. TASK NUMBER

 214 

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U.S. Army Research Institute for the Behavioral and Social Sciences

Research and Advanced Concepts Office 

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Arlington, VA 22202-3926

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 ARI 

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U.S. Army Research Institute for the Behavioral and Social 

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Arlington, VA 22202-3926

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 Technical Report 1164 

12. DISTRIBUTION/AVAILABILITY STATEMENT 

Approved for public release; distribution is unlimited. 

13. SUPPLEMENTARY NOTES

Subject Matter POC: James Belanich 

14. ABSTRACT (Maximum 200 words): 

Videogame-based environments are an increasingly popular choice to facilitate training. The purpose of

the current research was to investigate the influence of two trainee characteristics, prior videogame

experience and computer self-efficacy, on learner outcomes of a videogame-based training environment.

In this research, 413 participants played a first-person-perspective videogame that began with a singleplayer section to introduce game-specific tasks, followed by a multi-player section where participants 

formed small teams to conduct several collaborative missions. Results indicated that computer selfefficacy and prior videogame experience were predictive of several learner outcomes such that trainees

with greater computer self-efficacy and prior videogame experience reported less difficulty using the 

game interface and greater team cohesion, training satisfaction, and training motivation. Further, a 

videogame genre-specific effect was demonstrated in that only specific prior game experiences that

share similar characteristics with the current training game were significantly predictive of the learner

outcomes. These findings have implications for training game developers and instructors utilizing such 

games.

15. SUBJECT TERMS 

Games, training, computer games, desktop simulations, individual differences, computer experience,

computer self-efficacy

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 Unlimited 39 

Ellen Kinzer 

 Technical Publications Specialist 

 703-602-8047

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Technical Report 1164 

The Influence of Trainee Gaming Experience and 

Computer Self-Efficacy on Learner Outcomes of 

Videogame-Based Learning Environments 

Karin A. Orvis 

George Mason University 

Consortium Research Fellows Program 

Kara L. Orvis 

Consortium Post-Doctoral Fellows

James Belanich 

U.S. Army Research Institute 

Laura N. Mullin 

The Catholic University of America 

Consortium Research Fellows Program 

Research and Advanced Concepts Unit 

Paul A. Gade, Chief 

U. S. Army Research Institute for the Behavioral And Social Sciences 

2511 Jefferson Davis Highway, Arlington, Virginia 22202-3926 

June 2005 

Army Project Number Personnel Performance 

633007A792 and Training 

Approved for public release; distribution is unlimited

iii
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FOREWORD 

The U.S. Army Research Institute for the Behavioral and Social Sciences (ARI), as part 

of its Training for Interactive Distributed Environments work package, is investigating the use of 

training technology that is effective, affordable, and distributable. ARI seeks to provide the 

Army with guidance on how game-based training tools can be used for military training. 

The focus of this research effort was to assess how trainee characteristics specific to 

previous computer and videogame experiences impact training outcomes of a game-based 

training environment. The game used for this research was the America’s Army game. 

America’s Army was developed by the Office of Economic and Manpower Analysis to serve as 

an interactive tool for providing potential recruits with information regarding U.S. Army 

opportunities. The game has been well received by the public with over four million registered 

players. In Janurary 2004, America’s Army was used during a four-day inter-semester gamebased training exercise at the U. S. Military Academy. This game was used to further develop 

cadet tactics skills and was chosen because of its ability to allow for the virtual simulation of

small team maneuvers. 

A summary of this research was briefed to representatives from the Research, 

Development, Experimentation Command/Simulation and Training Technology Center; the 

Training and Doctrine Command—Training Development and Analysis Directorate; the Army

Research Lab – Human Research & Engineering Directorate; and the Institute for Creative 

Technologies on 28 September 2004. The findings of this research were also presented at the ELearn World Conference on E-Learning in Corporate, Government, Healthcare, and Higher 

Education Conference in November 2004, where it received the Outstanding Paper Award, and 

at the American Psychological Association Division 19/21 Annual Symposium on Applied 

Experimental Research in March 2005, where it received the Dr. Jimmy Mitchell Award for Best 

Graduate Student Poster. 

MICHELLE SAMS 

Technical Director 

v
ACKNOWLEDGEMENT 

The authors acknowledge the cooperation of MAJ Carl Jacquet, Director of the War 

Fighting Simulation Center at the U. S. Military Academy, for his aid in coordinating the data 

collection. In addition, the authors would like to acknowledge the assistance provided by Sharon 

Meyers in posting the questionnaire online. Also, the authors would like to thank Dr. Jennifer 

Solberg (ARI, Selection and Assignment Research Unit) and Dr. Andrea Rittman Lassiter 

(Minnesota State University- Mankato) for their comments and suggestions on this report.

vi
THE INFLUENCE OF TRAINEE GAMING EXPERIENCE AND COMPUTER SELF-EFFICACY 

ON LEARNER OUTCOMES OF VIDEOGAME-BASED LEARNING ENVIRONMENTS 

EXECUTIVE SUMMARY 

Research Requirement: 

Videogame-based environments are an increasingly popular choice to facilitate training. 

The purpose of the current research was to investigate the influence of two trainee 

characteristics, prior videogame experience and computer self-efficacy, on learner outcomes of a

videogame-based training environment (i.e., ease in using the game interface, team cohesion, 

training satisfaction, and training motivation). Additionally, this research sought to analyze the 

contribution of specific types of videogame experience versus general videogame experience in 

predicting learner outcomes. 

Procedure: 

In this research, 413 participants played a first-person-perspective videogame that began 

with a single-player section to introduce game-specific tasks, followed by a multi-player section 

where participants formed small teams to conduct several collaborative missions. Following the 

four-day training game exercise, participants completed an online questionnaire. 

Findings: 

Results indicated that computer self-efficacy and prior videogame experience were 

predictive of several learner outcomes such that trainees with greater computer self-efficacy and 

prior videogame experience reported less difficulty using the game interface and greater team

cohesion, training satisfaction and training motivation. Further, a videogame genre-specific 

effect was demonstrated in that only specific prior game experiences that share similar 

characteristics with the current training game were significantly predictive of the learner 

outcomes. Additionally, results indicate that there is a wide range of prior videogame experience 

across the military participants in this sample, with 17% of cadets reporting they have no 

experience playing videogames and 44% reporting they have limited videogame experience. 

Utilization of Findings: 

The results of this research provide useful information to individuals developing or using 

game-based training environments. This research extends prior findings by demonstrating the 

importance of trainee characteristics such as prior videogame experience and computer selfefficacy for the prediction and explanation of learner outcomes in videogame-based training. It 

is suggested that modification of these trainee characteristics prior to training would help to 

enhance training outcomes.

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THE INFLUENCE OF TRAINEE GAMING EXPERIENCE AND COMPUTER SELF-EFFICACY 

ON LEARNER OUTCOMES OF VIDEOGAME-BASED LEARNING ENVIRONMENTS 

CONTENTS

Page 

Introduction..................................................................................................................................... 1 

Learner Outcomes of Game-Based Training Environments........................................................... 2 

Prior Computer Experience............................................................................................................. 3 

Computer Self-Efficacy .................................................................................................................. 7 

Method............................................................................................................................................ 8 

Participants...................................................................................................................................... 8 

Game ............................................................................................................................................... 8 

Procedure ........................................................................................................................................ 8 

Measures......................................................................................................................................... 9 

Results........................................................................................................................................... 11 

Descriptive Statistics..................................................................................................................... 11 

Role of General Videogame Experience....................................................................................... 12 

Role of Specific Videogame Experience ...................................................................................... 13 

Role of Computer Self-Efficacy ................................................................................................... 15 

Influence of Prior Game Experience on Military Skills............................................................... 17 

Discussion..................................................................................................................................... 18 

General Videogame Experience ................................................................................................... 18 

Specific Videogame Experience ................................................................................................... 19 

Computer Self-Efficacy ................................................................................................................ 20

Influence of Prior Game Experience on Military Skills............................................................... 20 

Implications and Conclusions....................................................................................................... 20 

References..................................................................................................................................... 23 

Appendix A................................................................................................................................. A-1 

ix
CONTENTS (continued) 

Page 

List of Tables 

Table 1 Means, Standard Deviations, and Correlations of Variables........................................ 11 

Table 2 Regression Analyses for Training Satisfaction, Team Cohesion, and Ease in Using 

the Interface Mediating the Relationship Between General Videogame 

Experience and Training Motivation ................................................................... 12 

Table 3 Regression Analyses for Team Cohesion Mediating the Relationship Between 

General Videogame Experience and Training Motivation ................................... 13 

Table 4 Regression Analyses for Specific Videogame Experiences Predicting Team 

Cohesion, Training Satisfaction, Ease in Using the Interface, and Training

Motivation............................................................................................................. 14 

Table 5 Incremental Validity Results of Specific Videogame Experiences Over General 

Videogame Experience ......................................................................................... 14 

Table 6 Regression Analyses for Team Cohesion Mediating the Relationship Between 

Prior America’s Army Videogame Experience and Training Motivation............ 15 

Table 7 Incremental Validity Results of Computer Self-Efficacy Over General Videogame

Experience............................................................................................................. 16 

Table 8 Interaction Between General Videogame Experience and Computer Self-Efficacy 

on Training Motivation......................................................................................... 16 

List of Figures 

Figure 1 Conceptual model of training motivation...................................................................... 5 

Figure 2 Significant interaction between general videogame experience and computer selfefficacy on training motivation............................................................................. 17 

x
THE INFLUENCE OF TRAINEE GAMING EXPERIENCE AND COMPUTER SELF-EFFICACY 

ON LEARNER OUTCOMES OF VIDEOGAME-BASED LEARNING ENVIRONMENTS 

Introduction

Videogames are emerging as an increasingly popular tool in helping to train and ensure 

the preparedness of U.S. Army Soldiers (Herz & Macedonia, 2002). As opposed to the more 

traditional lecture-based form of training, training games allow for greater interactivity as well as 

providing realistic feedback and multi-sensory stimulation (Garris, Ahlers, & Driskell, 2002; 

Tarr, Morris, & Singer, 2002). These games are found to be intrinsically motivating and can 

facilitate learning (Gee, 2003; Prensky, 2001). Research also indicates that skills learned in 

game-based training environments transfer to real-life situations (Gopher, Weil, & Bareket, 

1994; Knerr, Simutis, & Johnson, 1979). 

Given the increasing popularity of using videogames for training, it is important to 

investigate factors that maximize the effectiveness of this training medium. The training 

literature suggests that training effectiveness is influenced by three primary determinants: a) the 

training program itself (e.g., the actual videogame), b) the trainee (in terms of personal 

characteristics and attitudes), and c) the situational context in which the training takes place 

(Campbell & Kuncel, 2001; Colquitt, LePine, & Noe, 2000; Mathieu, Tannenbaum, & Salas, 

1992; Salas & Cannon-Bowers, 2001). Available research on training games has primarily 

focused on the first determinant of training effectiveness: videogame features or characteristics. 

Game features such as challenge, realism, and interactivity have been found to influence trainee 

motivation and the length of time in which trainees are willing to invest in mastering the skills 

taught during game play (e.g., Belanich, Sibley, & Orvis, 2004; Corbeil, 1999; Garris et al., 

2002). Such research has enhanced our understanding on how to design the actual training game

to improve its effectiveness. Yet, to date, little emphasis has been paid to the second determinant 

of training effectiveness; namely, how trainee characteristics influence learner outcomes in 

videogame-based training environments. 

There is reason to believe that individual characteristics of the trainee may play an 

important role in predicting learner outcomes. Limited research on e-learning environments has 

found that trainees’ characteristics significantly influence learner outcomes such as learning and 

motivation to train. Both stable characteristics, such as personality traits, and more malleable 

characteristics, such as prior computer experience, have been found to predict e-learning 

outcomes (Brown, 2001; Orvis, Fisher, & Wasserman, 2003; Schmidt & Ford, 2003). The 

purpose of the current research is to investigate the influence of trainee characteristics on training 

motivation and other learner outcomes in videogame-based learning environments. Specifically, 

this research focuses on two malleable trainee characteristics that may be particularly relevant in 

a videogame-based training environment: trainee’s prior videogame experience and computer 

self-efficacy. These characteristics were chosen because instructors have the ability to influence 

them prior to training implementation in an effort to ensure maximum training effectiveness. In 

contrast, stable characteristics, such as personality variables, are not easily altered. The ability to 

identify the individual attributes that lead to success in game-based training environments will 

help to better prepare Soldiers for training and will lead to increased operational capabilities. 

1
Learner Outcomes of Game-Based Training Environments 

The fundamental goal of training is to positively impact learners in terms of their 

knowledge, skills, and/or attitudes; therefore, identifying training variables that influence learner 

outcomes will lead to enhanced training effectiveness. The current research focuses on four 

learner outcomes that are significant in videogame-based training environments: training 

motivation, training satisfaction, ease in using the training game’s user interface, and perceived 

cohesion with one’s teammates while playing the game. 

One of the principal perceived benefits of using videogames for training purposes is that 

they are motivating for individuals to play (Prensky, 2001). Therefore, motivation to train is of 

particular interest to the current research. Motivation can be defined as the direction, strength, 

and persistence of volitional behavior (Campbell & Kuncel, 2001); and in the context of 

instruction, the volitional behavior can be the purposeful engagement in or interaction with the 

instructional media. Motivation to learn in a training program has been found to predict 

subsequent training outcomes such as skill and knowledge acquisition and retention (Colquitt et 

al., 2000; Mathieu et al., 1992; Tannenbaum & Yukl, 1992). Unfortunately, literature on 

computer-based instruction has also found that trainees do not always make choices that increase 

learning. For example, trainees sometimes terminate training before learning the intended 

training objectives, in part, because of low training motivation levels (Steinberg, 1989). Thus, 

ways in which to maximize an individual’s level of training motivation is of great concern to 

instructors and is an important outcome to investigate in videogame-based learning 

environments. 

Another outcome of interest to the current research is the learner’s satisfaction with the 

training game experience. Training satisfaction focuses on both emotionally-based opinions 

concerning the training (e.g., the trainee liking the training) and reactions regarding the utility of 

the training (e.g., the trainee believing the training enhanced his/her knowledge or skills). 

Trainees’ level of satisfaction with the training has been found to influence learning in an elearning environment (Wasserman, Orvis, Fisher, & Barry, 2002). This may be because when 

trainees are more satisfied with their training experiences, they are likely to stay engaged for 

longer periods of time or put forth greater mental effort in trying to learn the training content, 

thus resulting in greater levels of learning. 

The perception of ease in using the training game interface is another criterion that should 

influence the level of engagement in a videogame-based training environment. If e-learning 

environments are frustrating and difficult to use, trainees may experience decreased motivation 

and not fully engage in the program (Park & Tennyson, 1980; Tennyson, 1980). Difficulties 

with the technology or interface in which the training content is delivered has been cited as a key 

frustration source and a reason for low completion rates in e-learning programs (Frankola, 2001). 

Moreover, prior research has found that trainees’ perceptions regarding the user interface of an elearning training program were positively related to their satisfaction with the overall training; 

which, in turn, positively influenced learning (Wasserman et al., 2002). This suggests that the 

ease in using a game’s user interface is a valuable learner outcome in game-based learning 

environments. 

2
Finally, many training videogames are collaborative in nature, requiring the interaction

and cooperation among trainee team members in order to be successful in the game and to learn 

the training content. Previous collaborative learning research has found that the quality of intrateam interactions is a key element in determining the extent and depth of learning in such 

environments (Gilbert & Moore, 1998; Northrup, 2001; Shute, Lajoie, & Gluck, 2000; Wagner, 

1997). Quality team interactions originate, in part, from collaborative team states such as team

cohesion. Indeed, team cohesion, most commonly defined as members liking for one another 

(Evans & Jarvis, 1980) and the extent to which team members are attracted to the idea of the 

group (Hogg, 1992), has been found to be directly related to group effectiveness (Evans & Dion, 

1991; Mullen, Anthony, Salas, & Driskell, 1993; Mullen & Copper, 1994). Effective 

collaboration is also critical to the unit combat performance of Soldiers. Accordingly, this 

suggests that the level of cohesion trainees perceive with their teammates is an important learner 

outcome to investigate in collaborative game-based learning environments. 

Prior Computer Experience 

In general, research on the relationship between experience and various computer-based 

attitudinal and learning outcomes is equivocal. Some research found that previous experience is 

positively related to computer-related attitudes, such as interest and comfort with electronic 

learning (Dias, 2000; Dyck & Smither, 1994; Houle, 1996; Rozell & Gardner, 1999; Shashaani, 

1994); and negatively related to anxiety in using computers (Dyck & Smither, 1994; Keeler & 

Anson, 1995). Additional research has found previous experience to have a positive influence on 

computer-based learning, such that computer experience positively predicts time spent in a 

distributed learning class (Patterson, 1999), motivation to learn, and actual learning in a 

computer-based training course (Dyck & Smither, 1996; Martocchio & Webster, 1992). In 

contrast, other research has found no clear relationship between previous experience and 

computer-based outcomes (Kay, 1992). For instance, some research either failed to find or 

found mixed results regarding the relationships between computer experience and anxiety in 

using computers (Henderson, Deane, Barrelle, & Mahar, 1995; Houle, 1996; Rozell & Gardner, 

2000) and computer-related attitudes (Henderson et al., 1995; Woodrow, 1991). Moreover, other 

research failed to find a relationship between experience and time spent in a distributed learning 

course (Brown, 2001). 

Several researchers have suggested that these mixed findings may be due, in part, to the 

different approaches taken to operationalize prior computer experience (Hasan, 2003; Smith, 

Caputi, Crittenden, Jayasuriya, & Rawstone, 1999). The majority of studies examine experience 

with computers globally as a unidimensional construct, and address level of computer experience 

as the frequency or length of time of general computer use (e.g., Al-Khaldi & Al-Jabri, 1998; 

Loyd & Loyd, 1985; McInerney, McInerney, & Sinclair, 1994; Salzer & Burks, 2003). 

Operationalizing experience as a global measure does not account for experiences with specific 

types of computer applications, such as word processing, spreadsheets, data analysis, computer 

games, e-mail, or programming. As such, the implicit assumption is that one type of computer 

experience is equivalent to all others, and any computer experience should positively influence 

subsequent training in a completely different type of computer task. 

3
Such an assumption may not be appropriate. Some research demonstrates that specific 

computer experiences are differentially related to learning outcomes in computer-based learning 

environments (Polman & Fishman, 1995; Salanova, Grau, Cifre, & Llorens, 2000; Woodrow, 

1991). For example, Woodrow (1991) found that prior programming experience significantly 

predicted learning (measured as final course grade) in a computer training course, while prior 

word processing experience was not predictive of learning. Woodrow explained that the final 

course grade was heavily skewed toward programming ability rather than other applications such 

as word processing. Such findings indicate that previous experiences with tasks and technology 

similar to the given computer-based training environment are most predictive of attitudes and 

performance in such learning environments. As such, a growing number of researchers have 

begun to adopt a multidimensional view of computer-related experience, arguing that reducing 

experience to a unidimensional construct has resulted in an oversimplication of the construct 

(Smith et al., 1999; Szajna & MacKay, 1995). This line of research advocates that measurements 

of computer experience assess diversity of computer experience, in terms of familiarity or 

frequency of use of various computer technology applications (e.g., Anderson & Reed, 1998; 

Busch, 1995; Chu, 2003; Chua, Chen, & Wong, 1999; Hasan, 2003; Polman & Fishman, 1995). 

It also suggests that the validity of computer experience as a predictor of training outcomes 

depends upon the relatedness of the particular training criterion of interest (e.g., particular learner 

outcomes) and type of computer experience examined. 

Although it seems that the relevance of computer experience (i.e., the degree of similarity 

between the prior experience and current training environment) rather than the quantity, may be 

the most predictive of training criteria, much of the research subscribing to a multidimensional 

view of experience continues to analyze the relationships between computer experience and 

learning criteria using a summative composite measure of various experience types (e.g., 

Bozionelos, 2001; Gardner, Discenza, & Dukes, 1993). As a result, while prior research does 

demonstrate that previous experience with computer applications is predictive of success, less is 

known about the particular types of experience that are most relevant to a given learning context. 

More research is needed to better understand what types of experiences contribute most to 

success in a given technology environment. It is useful to understand whether one type of 

previous technology experience significantly contributes to the prediction of learner outcomes, 

such as training motivation, satisfaction and learning, in a different type of environment. 

Videogame experience. There is a paucity of research on the influence of prior 

experience on learner outcomes of videogame-based training environments. The prior training 

game research has primarily focused on enhancing our understanding of the features or 

characteristics of the videogame that impact training effectiveness (e.g., Belanich et al., 2004; 

Corbeil, 1999; Garris et al., 2002). Research that has investigated prior experience in gaming 

environments tends to mirror the majority of work on previous computer experience, 

operationalizing the experience construct as general experience in using computers, regardless of 

the particular types of computer experiences one has acquired. Some subsequent gaming 

research has examined prior experience with videogames in particular and found that prior 

overall or general videogame experience (regardless of the type of videogame previously played) 

was related to future game performance in videogame-based environments (Gagnon, 1985; 

Young, Broach, & Farmer, 1997). 

4
We propose that trainees’ previous videogame experience will predict the four learner 

outcomes of interest: training motivation, training satisfaction, ease in using the game interface, 

and perceived team cohesion (Hypothesis 1). For the purpose of this research, previous 

videogame experience is operationalized as any game experience with computer-based 

videogames or console-based videogames (e.g., Playstation, Xbox). Specifically, we suggest 

that trainees with greater levels of experience (e.g., those who play videogames on a more 

frequent basis for personal enjoyment purposes) should be more motivated to engage in such 

environments for training purposes as well. Baldwin & Magjuka (1997) suggest that the 

motivating influence of any training design element is partially contingent on the trainees’ 

accumulated experience with that design element in other settings. Thus if trainees have had 

frequent, positive experiences with videogames in the past, they should be more likely to find 

such environments motivating in the future. Further, because trainees with greater levels of 

videogame experience enjoy this type of environment, they should be more satisfied with gaining 

new knowledge or skills from a training environment with similar characteristics, as compared to 

trainees who have not had much exposure to this type of environment in the past. In support of 

this proposition, previous research on computer-based training contexts has found that frequency 

of computer use (i.e., prior computer experience) is positively related to favorable attitudes 

towards computers (Mitra, 1998). 

Previous experience with a game interface should also lead to the development of 

strategies and heuristics that smooth a trainee’s navigation in a similar environment. Prior 

research has found that training programs in which the learner is primarily responsible for his/her 

own learning, as is often the case in e-learning and game-based learning environments, are more 

successful for trainees who have greater levels of prior knowledge on the relevant topics (Lee & 

Lee, 1991; Gay, 1986). We suggest that a trainee’s prior knowledge of videogames (e.g., 

knowledge of videogame interfaces obtained from prior experiences playing videogames) will 

enable the trainee to feel more at ease when presented with a similar training environment. 

Similarly, we suggest that trainees with little prior experience working with others and building 

positive relationships in collaborative virtual learning environments are likely less equipped with 

the knowledge of how to interact effectively in such environments. Thus, trainees with less prior 

collaborative videogame experience will have more difficulty forming cohesive relationships in 

future videogame-based training environments that require virtual collaboration. 

In addition, we suggest that trainees’ perceived cohesion with their team members, ease 

in using the game’s interface, and training satisfaction will partially explain the relationship 

between prior general videogame experience and motivation to continue training with the 

videogame (Hypothesis 2). A conceptual model for these proposed mediated relationships is 

shown in Figure 1. 

Training Satisfaction

Team Cohesion 

Ease Using Interface Motivation to

Continue Training 

Previous 

Videogame

Experience

Figure 1. Conceptual model of training motivation 

5
In terms of team cohesion as a mediator, prior research suggests that cohesive 

environments facilitate an individual’s motivation to continue engaging in a team-based 

distance-learning environment. Team cohesion has been found to be positively related to group 

functioning in that more socially cohesive teams tend to possess more motivation to work 

together as a collective on a given task (Evans & Dion, 1991; Mullen et al., 1993; Mullen & 

Copper, 1994). Further, as mentioned previously, those with little experience working 

collaboratively in virtual learning environments may be less equipped with the knowledge of 

how to interact effectively in such environments. Therefore, they will have more difficulty 

forming cohesive relationships in similar future training environments. As such, trainees’ 

perceptions of cohesion among their team members will mediate, in part, the extent to which 

prior videogame experience influences motivation to continue training with the videogame. 

The extent to which trainees find it easy to use the game’s user interface and overall 

enjoy the training experience (i.e., their satisfaction with the training) may also mediate the 

relationship between prior experience and training motivation. As aforementioned, if a training 

program is difficult to use and frustrating, a trainee will likely be less motivated to continue 

engaging in the training (Park & Tennyson, 1980; Tennyson, 1980). Moreover, trainees with 

greater levels of experience (e.g., those who frequently play videogames for personal enjoyment 

purposes) are likely to perceive the user interface of a given videogame-based training 

environment easier to use and should find the overall training experience more satisfying. 

Multidimensional videogame experience. Similar to the acknowledgement of the 

multidimensional nature of computer experience, we suggest that previous videogame

experience should be examined at a more specific level of analysis rather than only a 

unidimensional, global view of videogame experience. It is important to consider specific 

videogame experiences (i.e., an individual’s experiences with particular types or genres of 

videogames) as well. Based on prior research on computer experience (e.g., Polman & Fishman, 

1995; Woodrow, 1991), we propose that the impact of prior videogame experience on 

subsequent learner outcomes in a given game-based training environment will depend on the 

type of prior game experience one has acquired. Specifically, we hypothesize that only prior 

game experiences that share similar game characteristics to the given training game environment 

will influence learner outcomes; while experience with unrelated games (i.e., games do not share 

similar characteristics) will not predict learner outcomes (Hypothesis 3). 

Demonstrating that the relationships between videogame experience and various learner 

outcomes are dependent on the specific types of experience amassed is valuable in furthering our 

understanding of game-based learning contexts. However, there have been several recent calls in 

the literature to go beyond the examination of bivariate correlations (e.g., Avis, Kudisch, & 

Fortunato, 2002; Clevenger, Pereira, Wiechmann, Schmitt, & Harvey, 2001; Cortina, Goldstein, 

Payne, Davison, & Gilliland, 2000). Accordingly, we suggest that additional information is 

gained by demonstrating incremental validity of the specific game experiences above and beyond 

more general videogame experience. The primary issue is whether relevant specific game

experiences (for example, first-person-perspective videogames) account for variance in learner 

outcomes beyond that accounted for by a general measure of videogame experience. If an 

individual’s report of his/her specific game experiences do not significantly contribute beyond 

the report of his/her overall game experience, there would be less utility in operationalizing 

6
videogame experience as a multidimensional construct. We hypothesize that prior videogame

experience with specific games that share similar characteristics with the training game will 

provide incremental validity over general videogame experience in the prediction of learner 

outcomes (Hypothesis 4). 

Computer Self-Efficacy 

In general, self-efficacy is a judgment of one’s capability to successfully perform a 

specific task (Bandura, 1977). Self-efficacy judgments influence an individual’s tendency to 

engage in a task as well as level of exertion and endurance exhibited (Bandura, 1995; Muira, 

1987). Self-efficacy is situation specific or domain-specific construct in that it can vary across 

kinds of activities and tasks (Bandura, 1977). As such, computer self-efficacy has most 

frequently been examined as the type of self-efficacy beliefs relevant for computer-based 

training environments. Computer self-efficacy is a judgment of one’s capability to use a 

computer to successfully perform a computer-based task (Compeau & Higgins, 1995). 

Trainee self-efficacy beliefs have been found to be an important predictor of motivation 

to learn (Colquitt et al., 2000), trainee reactions to a training program (Mathieu, Martineau, & 

Tannenbaum, 1993), participation in learning activities (Maurer & Tarulli, 1994; Noe & Wilk, 

1993; Zimmerman, 2000), amount of time spent practicing new skills (Bouffard-Bouchard, 

1990), and learning and performance (Gist, Schwoerer, & Rosen, 1989; Martocchio & Judge, 

1997; Martocchio & Webster, 1992) in various training contexts, including computer-based 

training contexts. In general, this research suggests that individuals with high self-efficacy tend 

to have more positive learner outcomes because of the persistence and effort demonstrated while 

completing a training program. Accordingly, trainee computer self-efficacy should be a 

significant predictor of learner outcomes in videogame-based training environments as well.

Further, research on computer-based training has demonstrated that computer selfefficacy is positively related to prior computer experience (e.g., Cassidy & Eachus, 2002; Dyck 

& Smither, 1996; Houle, 1996; Levine & Donitsa-Schmidt, 1997). As such, an important 

question is whether trainees’ computer self-efficacy uniquely explains variance in the learner 

outcomes of a given videogame-based training program beyond that accounted for by videogame

experience. In other words, is prior experience the significant driver of learner outcomes while 

self-efficacy is simply related to prior experience, or is computer self-efficacy a unique driver of 

the learner outcomes as well? Demonstrating the incremental validity of trainees’ computer selfefficacy on learner outcomes would provide additional avenues by which instructors could 

enhance the effectiveness of game-based training environments. We hypothesize that computer 

self-efficacy will provide incremental validity over general videogame experience in the 

prediction of learner outcomes (Hypothesis 5).

Lastly, as an exploratory analysis, the current research will investigate whether prior 

general videogame experience and computer self-efficacy interact in the prediction of the four 

learner outcomes. Prior research has demonstrated that individual characteristics interact with 

one another to predict a variety of criteria such as job performance, counterproductive behaviors, 

and interview performance (Witt, 2002a; Witt, 2002b; Witt, Burke, Barrick, & Mount, 2002). 

For example, Witt et al. (2002) found that the relationship between conscientiousness and job 

7
performance is stronger for individuals high in agreeableness than those low in agreeableness. 

We believe a similar case may be made in regards to the learner outcomes examined in the 

current research. Thus, we will explore whether the interaction among trainee computer selfefficacy and prior experience rather than their main effects alone predict the learner outcomes. 

Method 

Participants

Participants were 413 first-year U. S. Military Academy cadets taking part in a four-day 

inter-semester game-based tactics training exercise. The mean age of participants was 18.71 

years (SD = .94 years). Following the four-day training exercise, cadets were given the 

opportunity to complete an online questionnaire for the current research. Completion of the 

research questionnaire, while encouraged by tactics instructors, was voluntary. Approximately 

1100 cadets participated in the training exercise of which 414 of these cadets voluntarily 

completed the follow-up questionnaire. 

Game 

The game used as the training exercise was America’s Army, an online, first-person 

perspective game with both single-player and multi-player sections. America’s Army, created by 

the Office of Economic and Manpower Analysis at the U. S. Military Academy, was originally 

developed to serve as a recruiting tool in order to inform potential recruits about what to expect 

during basic training and about Army core values, history, and Army background. To date, over 

four million individuals have registered to play the game online (Petermeyer, 2004). This game

was chosen for this exercise because of its ability to allow for the virtual simulation of small 

team maneuvers. Additional information regarding America’s Army is available at

www.americasarmy.com. 

Procedure 

During the four-day training exercise, cadets played the computer game online during 

their own time, at a location of their own preference. First, the cadets completed a “basic 

training” single-player section, where they learned how to play the game. This section contains 

four segments: a) marksmanship training, b) an obstacle course, c) weapons familiarization, and 

d) a MOUT (military operations in urban terrain) training mission. In the marksmanship 

segment, cadets practiced using a computer mouse to shoot a rifle. Practice and qualification 

rounds were repeated until the cadet qualified with his/her weapon (at least 23 out of 40 targets 

with 40 rounds). In the second segment, the obstacle course, cadets completed a course which 

includes obstacles such as climbing over a wall, running over a balance beam, and low crawling 

under barbwire. Cadets repeated the obstacle course until they bettered the time requirement of 

90 seconds. In the weapons familiarization segment, cadets practiced using a computer mouse to 

operate four different weapons including a machine gun, rifle with a grenade launcher, 

fragmentation grenade, and smoke grenade. Cadets were not required to meet qualification 

standards with these weapons. In the final segment, MOUT training, cadets navigated through a 

building and several tunnels while being introduced to and practicing basic “rules of 

8
engagement” (i.e., shooting at stationary silhouettes of “hostile” targets while not firing at the 

silhouettes of “noncombatant” targets). This section required the use of shooting and movement 

skills introduced in the prior three sections. 

Once the basic training section had been completed, cadets were eligible to play the 

multi-player section of the game. In the multi-player section, cadets were placed into small 

teams and engaged in collaborative missions. They were required to play a minimum of three 

collaborative missions over the course of four days, with no maximum limit of missions set. 

Team membership was not fixed; instead, membership could vary across collaborative missions 

depending which cadets were currently online engaging in the game. In the mission, a team’s 

goal was either to attack or to defend a radio tower. Regardless of the team’s goal within a given

mission, cadets took the perspective of a U. S. Soldier, while the opposing team was depicted as 

the enemy. 

The multi-player section of America’s Army represents a distributed, online environment 

because all team members engage in the same mission during “real” time. However, each team

member plays the game on an individual computer, in a different physical location. Team

members interact in terms of observing each other’s actions during the “real time” mission and 

via written communication using an online chat feature built into the game interface. 

At the end of the tactics training exercise, the instructor provided the website address of 

the online questionnaire and informed the cadets of their opportunity to participate in this 

research. Cadets were provided with a brief introduction to the questionnaire and promised 

confidentially of their responses. The questionnaire included both multiple-choice and openended questions. Interested cadets completed this questionnaire on their own time. Some cadets 

did not provide a response for all questionnaire items, but as long as the majority of items (at 

least 70 %) were completed a cadet’s responses were included. 

Measures 

General game experience. General game experience was assessed using one item,

“Based on the past year, how frequently have you played videogames (for example, PC-based, 

Nintendo, Playstation, arcade)?” Possible responses ranged from 1 (none) to 5 (much more than 

average). 

Specific game experience. Prior game experience with specific games was assessed using 

a seven-item scale. Using a yes/no response (e.g., 0 or 1), cadets were asked to note whether they 

had frequently played a specific type of videogame. The seven types of specific game

experience assessed were: a) first-person-shooter (e.g., Battlefield 1942, James Bond 007, Medal 

of Honor); b) simulation (e.g., Falcon, Microsoft Flight Simulator, Lock On:Modern Air); c) 

online multi-player games (e.g., EverQuest, Planetside); d) action (e.g., Grand Theft Auto, NBA, 

Car Racing); e) command/strategy (e.g., Risk, Chess); f) creative development (e.g., Sims, 

Tycoon, Civilization); and g) puzzle (e.g., Minesweeper). In addition, participants were asked to 

indicate the extent to which they had previously played America’s Army. Possible responses for 

this item ranged from 1 (none) to 5 (much more than average). 

9
Computer self-efficacy. Computer self-efficacy was assessed using one item, “What is 

your level of confidence using computers?” Possible responses ranged from 1 (low) to 5 (high). 

Satisfaction with training. Satisfaction with the training experience was assessed using a 

six-item scale. Sample items include “I was satisfied with the experience of using the America’s 

Army game” and “Using the America’s Army game allowed me to better understand combat 

related cognitive skills and decision-making.” Possible responses ranged from 1 (strongly 

disagree) to 5 (strongly agree)1

. The coefficient alpha for this scale was deemed acceptable at 

.86. All items of this scale are provided in Appendix A. 

Ease in using user interface. Ease in using the game’s user interface was assessed with 

three items consisting of “How easy/difficult was it to learn how to use America’s Army game?,” 

“How easy/difficult was it to use the menu system?” (1 = very difficult to 5 = very easy), and 

“How comfortable did you feel using the system?” (1 = very uncomfortable to 5 = very 

comfortable)1

. The coefficient alpha for this scale was deemed acceptable at .81. 

 

Team cohesion. Trainee’s perception of the cohesion among his/her team members was 

assessed using a nine-item scale adapted from Craig and Kelly (1999). Items were augmented 

slightly to fit the game environment. Sample items include “To what extent was your team

engaged in the multi-player missions of the America’s Army game?” and “To what extent did 

members of your team like being a part of this team?” Possible responses ranged from 1 (not at 

all) to 5 (great extent). The coefficient alpha for this scale was deemed acceptable at .95. All 

items of this scale are provided in Appendix A. 

Training motivation. To assess motivation to continue training, an indirect measure 

(versus a more explicit, self-report measure of training motivation, e.g., Noe & Schmitt, 1986) 

was utilized. Cadets were asked to indicate the total number of hours spent playing the game

during the four days allotted for this training exercise. Possible responses ranged from 1 (1-5 

hours) to 4 (more than 15 hours). We believe that this is a reasonable means for assessing 

training motivation as videogame-based training represents a self-regulated voluntary training 

environment. 

Prior game experience influence on military skills. To enhance our understanding of the 

influence of prior videogame experience, cadets were posed several open-ended questions. First, 

cadets were asked to address how their prior videogame experiences helped or hindered their 

acquisition/learning of military-related knowledge or skills. Comments were provided by 135 

cadets. A post hoc organization of these comments was conducted. The majority of comments 

could be organized into four knowledge/skill areas. The areas of mission-related skills, teamrelated skills, functional and combat realism, and familiarity with weapons were selected as the 

areas in which to focus our discussion because they received the highest frequency of comments 

from participants. The remaining comments either did not address the question or represented 

over 13 different areas, none of which had a frequency of more than five participants providing a 

particular response. For sake of a concise description of findings, these areas will not be 

discussed. 

 

1 These items were reverse coded for the statistical analyses so that higher values reflected greater satisfaction with 

the training and greater ease in using the interface. 

10
In addition, cadets were asked if their prior experiences with videogames affected their 

military-related skills in regards to seven specific areas: a) decision making; b) building 

situational awareness; c) creating a common operating picture; d) multi-tasking; e) parallel 

processing of information; f) human understanding; and g) operating at a distance. Comments 

were provided by 174 cadets. A majority of the comments were classified into the seven areas. 

Participants also provided comments that could not be classified into these seven areas; these 

comments represented over 28 different areas, most of which had a frequency of five or less 

participants providing a particular response (or the comment did not address the question). For 

sake of a concise description of findings, these areas will not be discussed. 

Interrater agreement for the coding was computed on a random selection of 25 percent of 

the comments. An Intra Class Correlation of .93 was obtained suggesting high interrater 

agreement. Discrepancies in coding were resolved by having the first and fourth authors discuss 

the comments until both authors came to an agreement regarding the correct coding. 

Results 

Descriptive Statistics 

Means, standard deviations, and correlations of the relevant variables are displayed in

Table 1. Results indicate that there is a wide range of prior videogame experience across the 

participants in this sample, with 17% of cadets reporting they have no experience playing 

videogames and 44% reporting they have limited videogame experience. The majority of 

participants reported possessing average to high computer self-efficacy, with 42% of cadets 

indicating an average level of confidence in using computers and 49% indicating above average 

confidence levels. 

Table 1. Means, Standard Deviations, and Correlations of Variables 

Variable M SD 1 2 3 4 5 6 7

1. General videogame experience 2.44 1.05 -- 

2. Computer self-efficacy 3.55 .92 .33** --

3. America’s Army experience 1.59 .89 .35** .21** --

4. First-person-shooter experience .63 .48 .45** .27** .24** --

5. Training satisfaction 3.40 .72 .33** .14** .32** .25** --

6. Team cohesion 2.96 .98 .33** .22** .32** .23** .45** --

7. Ease in using interface 3.63 .76 .37** .30** .26** .36** .38** .42** -- 

8. Training motivation 1.55 .78 .20** .19** .19** .10+ .21** .22** .11*

Note. Across variables, N ranged from 246 to 413. All variables were measured on a 1-5 scale 

except first-person-shooter experience (measured on a 0-1 scale) and training motivation 

(measured on 1-4 scale). + p < .10. * p < .05. ** p < .01 (two-tailed). 

11
Role of General Videogame Experience 

The first two hypotheses examined the role of prior general videogame experience on 

learner outcomes. In support of Hypothesis 1, a general measure of prior videogame experience 

significantly predicted the learner outcomes. Specifically, frequency in playing videogames was 

positively related to perceptions of ease in using the game’s interface (r = .37, p < 01), cohesion 

with one’s team members (r = .33, p < .01), satisfaction with the training game experience (r = 

.33, p < .01), and motivation to continue training with the game (r = .20, p < .01). This indicates 

that the more experience individuals have playing videogames, the more comfortable and 

satisfied they are using the training videogame, the more cohesive they feel with their 

teammates, and the more motivated they are to continue using the game for training purposes. 

Hypotheses 2 proposed a conceptual model in which the influence of prior general 

videogame experience on motivation to continue training is mediated by training satisfaction, 

ease in using the game’s interface, and team cohesion. Using the mediated regression steps 

outlined by Baron and Kenny (1986), reported cohesion with one’s teammates appeared to be the 

only mediator of the relationship between general videogame experience and training motivation. 

Ease in using the game’s interface and training satisfaction did not mediate this relationship. The 

results are presented in Table 2. 

Table 2. Regression Analyses for Training Satisfaction, Team Cohesion, and Ease in Using the 

Interface Mediating the Relationship Between General Videogame Experience and Training 

Motivation.

Analysis/Variable B SE B β R2 ∆R2

DV = Training satisfaction 

General videogame experience .22 .03 .33** .11** .11**

DV = Team cohesion 

General videogame experience .30 .06 .33** .11** .11**

DV = Ease in using interface 

General videogame experience .27 .04 .37** .14** .14**

DV = Training motivation 

Step 1 .03** .03**

 General videogame experience .14 .05 .18**

Step 2 .06** .03*

 General videogame experience .08 .06 .11 

 Training satisfaction .08 .08 .07 

 Team cohesion .13 .06 .15*

 Ease in using interface .00 .09 .00 

Note. N = 363, 244, 357, and 227, for each aforementioned DV, respectively. *p < .05. **p < .01. 

A follow-up analysis was conducted examining team cohesion as the sole mediator of the 

general videogame experience - training motivation relationship. The results, as reported in 

Table 3, suggest that reported cohesion with one’s teammates significantly mediated this 

relationship. Videogame experience significantly predicted training motivation in Step 1. 

However, after accounting for the influence of team cohesion in Step 2, videogame experience 

no longer had a significant effect (at the p < .05 level). Finally, as recommended by Baron and 

Kenny (1986), the Sobel test, a statistical test of the mediation effect, was conducted to provide 

12
additional support. The Sobel test demonstrates that cohesion was a statistically significant 

mediator for this relationship (z = 2.32, p < .05). It is important to note, that the three proposed 

mediators were intercorrelated. Thus, although ease in using the game’s interface and training 

satisfaction did not demonstrate a significant mediational effect, these variables are relevant to 

trainees’ motivation to continue training. 

Table 3. Regression Analyses for Team Cohesion Mediating the Relationship Between General 

Videogame Experience and Training Motivation. 

Analysis/Variable B SE B β R2 ∆R2

DV = Team cohesion 

General videogame experience .30 .06 .33** .11** .11**

DV = Training motivation 

Step 1 .03** .03**

General videogame experience .14 .05 .17**

Step 2 .06** .03**

General videogame experience .09 .05 .12+

 Team cohesion .15 .06 .18**

Note. N = 244 and 228, for each aforementioned DV, respectively. +p < .10. *p < .05. **p < .01. 

Role of Specific Videogame Experience 

Hypotheses 3 and 4 examined the role of prior videogame experience with specific games 

on learner outcomes. To test Hypothesis 3, four regression analyses were conducted, where each 

of the four learner outcomes (team cohesion, training satisfaction, ease in using the game’s 

interface, and training motivation) were regressed onto the eight specific types of game

experiences. Results indicate that generally only prior experiences related to the videogame used 

in the training were significant predictors. Specifically, previous experience with the America’s

Army game was a unique predictor for all four learner outcome variables. Prior experience with 

other first-person-shooter games was also a significant predictor of training satisfaction and ease 

in using the game’s interface; it approached significance for team cohesion. As expected, 

experience using other types of specific games which did not share several similar characteristics 

to the current training game, such as puzzles and creative development games, were not 

predictive of these four outcomes. An unexpected result is that prior simulation experience 

predicted training motivation. We revisit this unexpected finding in the discussion section. 

Results are presented in Table 4. 

To test Hypothesis 4, whether prior specific videogame experience provides incremental 

validity over general videogame experience in the prediction of the four learner outcomes, a 

separate regression analysis was performed for each learner outcome. For each regression 

analysis, general videogame experience was entered first, followed by a block of variables in 

Step 2 consisting of the genre specific videogame experiences of prior America’s Army

experience and first-person-shooter videogame experience. Results indicate that prior America’s 

Army experience and first-person-shooter experience predicted unique variance above and 

beyond general videogame experience for two of the four dependent variables, training 

satisfaction and ease in using the game’s interface. For the other two dependent variables, prior 

America’s Army experience significantly contributed above and beyond general videogame 

13
experience for team cohesion and approached significance (p = .06) for motivation to continue 

training with the game. In short, genre-specific game experience predicts the learner outcomes 

of interest beyond what is explained by globally reported videogame experience alone. As such, 

there is value to measuring trainees’ prior specific game experiences as well as their general 

videogame experience. Results are presented in Table 5. 

Table 4. Regression Analyses for Specific Videogame Experiences Predicting Team Cohesion, 

Training Satisfaction, Ease in Using the Interface, and Training Motivation. 

Cohesion Satisfaction Ease Using Interface Motivation

Variable B SE B β B SE B β B SE B Β B SE B β

America’s 

Army

 .29 .07 .27** .21 .04 .26** .12 .04 .14** .11 .05 .12*

First-personshooter  .25 .14 .12+ .24 .09 .16** .38 .09 .24** -.01 .10 -.01

Simulation -.03 .18 -.01 .02 .11 .01 .10 .11 .04 .35 .13 .16**

Online 

multi-player 

-.02 .18 -.01 -.01 .11 -.01 .20 .11 .09+ .20 .13 .09 

Action .18 .13 .09 .08 .08 .05 .07 .08 .04 -.03 .09 -.02 

Command/ 

strategy

 .09 .14 .05 .13 .08 .09 .13 .09 .09 .04 .10 .02 

Creative 

development 

.04 .15 .02 -.12 .09 -.07 .10 .10 .06 .17 .10 .09

Puzzles -.02 .12 -.01 .09 .07 .06 -.06 .08 -.04 -.06 .09 -.04

Note. R2 = .14**, .14**, .20**, and .09**, for team cohesion, training satisfaction, ease in using interface, 

and training motivation, respectively. N = 244, 362, 356, and 336, for each DV, respectively. +

p < .10. *

p < .05. **p < .01. 

Table 5. Incremental Validity Results of Specific Videogame Experiences Over General 

Videogame Experience.

Cohesion Satisfaction Ease Using Interface Motivation

Regression step B SE B β B SE B β B SE B β B SE B β

Step 1

 General game 

 experience 

.30 .06 .33** .22 .03 .33** .27 .04 .37** .15 .04 .20**

Step 2

 General game 

 experience 

.20 .06 .21** .14 .04 .20** .16 .04 .23** .11 .05 .15*

 AA experience .24 .07 .23** .17 .04 .21** .10 .04 .11* .12 .05 .13*

 First person 

 shooter experience 

.19 .13 .09 .16 .08 .11* .38 .08 .24** .01 .10 .01

Note. R2 = .11** for Step 1; ∆R2 = .06** for Step 2, for team cohesion. R2 = .11** for Step 1; ∆R2 = .05**

for Step 2, for training satisfaction. R2

 = .14** for Step 1; ∆R2 = .06** for Step 2, for ease in using 

interface. R2

 = .04** for Step 1; ∆R2 = .02+ for Step 2, for training motivation. N = 244, 363, 357, and 

337, for team cohesion, training satisfaction, ease in using interface, and training motivation, respectively. +

p < .10. *p < .05. **p < .01.

14
To identify whether the observed mediation effect of team cohesion on the relationship 

between videogame experience and motivation would generalize to specific videogame

experiences, a post-hoc exploratory mediated regression analysis was conducted. Prior 

America’s Army experience was chosen as the independent variable because it was a significant 

predictor of training motivation. Similar to the findings for general videogame experience, 

cohesion with one’s teammates was found to partially mediate the relationship between prior 

America’s Army experience and training motivation using the mediated regression steps outlined 

by Baron and Kenny (1986). Results are presented in Table 6. Further, the Sobel test 

demonstrates that team cohesion was a statistically significant partial mediator for this 

relationship (z = 2.17, p < .05). 

Table 6. Regression Analyses for Team Cohesion Mediating the Relationship Between Prior 

America’s Army Videogame Experience and Training Motivation. 

Analysis/Variable B S.E. β R2 ∆R2

DV = Team cohesion 

America’s Army experience .34 .06 .32** .10** .10**

DV = Training motivation 

Step 1 .05** .05**

 America’s Army experience .20 .06 .23**

Step 2 .08** .02*

 America’s Army experience .16 .06 .18**

 Team cohesion .14 .06 .16*

Note. N = 244 and 228, for each aforementioned DV, respectively. *p < .05. **p < .01. 

Role of Computer Self-Efficacy 

The final research question examined the role of computer self-efficacy on learner 

outcomes. Hypothesis 5, that computer self-efficacy will provide incremental validity over 

general videogame experience in the prediction of the four learner outcomes, was tested using a 

separate regression analysis for each learner outcome. For each regression analysis, general 

videogame experience was entered first, followed by computer self-efficacy in Step 2. The 

results of the regression analyses indicate that computer self-efficacy explained statistically 

significant variance above and beyond general videogame experience for the criteria of team

cohesion, ease in using the interface, and training motivation. However, computer self-efficacy 

did not account for additional variance in training satisfaction beyond that accounted for by 

general videogame experience. In short, computer self-efficacy contributed to the prediction of 

three of the learner outcomes beyond what was explained by globally reported videogame

experience alone. Results are presented in Table 7. 

Lastly, an exploratory analysis to examine whether prior general videogame experience 

and computer self-efficacy interact in the prediction of the four learner outcomes was conducted. 

Using a separate regression analysis for each of the four outcomes, general videogame

experience and computer self-efficacy were entered into the equation in Step 1. In Step 2, the 

interaction term between videogame experience and computer self-efficacy was entered. 

Interaction terms generally correlate with the variables from which they are created; therefore, to 

reduce multicollinearity, the independent variables were centered around zero by subtracting 

15
each value from its respective mean before creating the interaction terms (Aiken & West, 1991; 

Cronbach, 1987). This transformation does not affect the correlations among the variables, yet it 

allows for better estimates of the interaction terms. 

The results, reported in Table 8, demonstrate that computer self-efficacy moderated the 

relationship between general videogame experience and training motivation (β = .15, p < .01). 

As shown in Figure 2, similar to our previously reported results, trainees with higher levels of 

computer self-efficacy report greater motivation to continue training with the game than those 

with lower levels of computer self-efficacy. Further, trainees with higher levels of prior 

videogame experience report greater motivation to continue training than those with lower levels 

of videogame experience. Most importantly, these results suggest that trainees who possess both 

a high level of computer self-efficacy and prior experience report the highest levels of training 

motivation. The interactions between computer self-efficacy and general videogame experience 

for training satisfaction, ease in using game’s interface, and team cohesion were not significant. 

Table 7. Incremental Validity Results of Computer Self-Efficacy Over General Videogame 

Experience. 

Cohesion Satisfaction Ease Using Interface Motivation

Regression step B SE B β B SE B β B SE B β B SE B β

Step 1

General game 

 experience 

.30 .06 .33** .22 .03 .33** .27 .04 .37** .15 .04 .20**

Step 2

General game 

experience 

.27 .06 .28** .21 .04 .31** .22 .04 .31** .12 .04 .16**

Computer 

self-efficacy

.15 .07 .14* .03 .04 .04 .16 .04 .20** .12 .05 .14**

Note. R2 = .11** for Step 1; ∆R2 = .02* for Step 2, for team cohesion. R2 = .11** for Step 1; ∆R2 = .00 for 

Step 2, for satisfaction. R2

 = .14** for Step 1; ∆R2 = .04** for Step 2, for ease in using interface. R2 = .04**

for Step 1; ∆R2

 = .02** for Step 2, for training motivation. N = 244, 363, 357, and 337, for team cohesion, 

training satisfaction, ease in using interface, and training motivation, respectively. *

p < .05. **p < .01. 

Table 8. Interaction Between General Videogame Experience and Computer Self-Efficacy on 

Training Motivation 

Regression step B SE B β

Step 1 

General videogame experience .12 .04 .16**

Computer self-efficacy .12 .05 .14**

Step 2 

General videogame experience .11 .04 .14**

Computer self-efficacy .15 .05 .17**

Experience X Self-efficacy .12 .04 .15**

Note. R2 = .06** for Step 1; ∆R2 = .02** for Step 2; N = 337. **p < .01.

16
1

2

3

4

-1 SD (1.39) Mean (2.44) +1 SD (3.49)

General Videogame Experience

Training M

otiv

ation

(measured on 1-4 scale)

Low Self-Efficacy (-1 SD)

Average Self-Efficacy (X)

High Self-Efficacy (+1 SD)

Figure 2. Significant interaction between general videogame experience and computer self-efficacy on 

training motivation. 

Influence of Prior Game Experience on Military Skills 

As a means for further enhancing our understanding of the influence of prior videogame

experience, participants were asked several open-ended questions. First, cadets were asked how 

their prior videogame experience (or any other digital-related experience) helped or hindered any 

of their military-related knowledge or skills. Of the 135 cadets who provided responses, 

mission-related skills, such as problem solving and attention to detail, was the most commonly 

mentioned skill area enhanced by prior videogame experiences (19% of responses). Cadets 

reported that their gaming experience allowed them to practice and become more adept at 

various skills related to the execution of tactical maneuvers. For instance, one cadet stated, “My 

attention to detail when under stress has increased, and my target-acquisition skills have 

increased.” The enhancement of team-related skills, such as communication and learning to stay 

organized as a combat team, was the second most common advantage reported (16% of 

responses). 

With respect to whether prior videogame experience hindered any military-related 

knowledge or skills, the most common disadvantage reported was the lack of functional and 

combat realism (16% and 11% of responses, respectively) when learning military-related skills 

in a gaming environment. As one cadet responded, “A person cannot learn to fire a weapon 

efficiently by learning from a videogame, [and] an individual ought to actually experience the 

pain and other emotions that actually come with combat.” Cadets often reported they engaged in 

reckless, careless or otherwise ill-advised behaviors during game play due to the availability of a 

restart option. Cadets also mentioned the potential of this behavior to create bad habits that may 

carry over to real combat situations. 

17
In addition, cadets were asked if their prior experiences with videogames and other 

digital technologies affected their military-related skills in regards to seven specific areas: a) 

decision making; b) building situational awareness; c) creating a common operating picture; d) 

multi-tasking; e) parallel processing of information; f) human understanding; and g) operating at 

a distance. Of the 174 cadets who provided responses, two common themes were identified 

which suggest that prior experience enhances military-related skills. Cadets indicated that their 

decision-making skills were aided by prior videogame experience (29% of responses), either by 

making a general reference this skill area (16%) or a specific statement, such as videogames 

enhancing their ability to make more decisive or faster decisions (13%). Cadets also commonly 

reported their prior experience aided their ability to multitask by keeping track of multiple 

situational variables (20% of responses). 

Discussion 

This research extends the current research by demonstrating the importance of prior 

videogame experience and computer self-efficacy for the prediction and explanation of learner 

outcomes in videogame-based training. Our findings in relation to trainees’ general videogame

experience, specific game experiences, and computer self-efficacy are discussed respectively 

below. In addition, the relevance of prior videogame experience to military skills is discussed. 

Finally, practical implications of the current research and future research directions are provided. 

General Videogame Experience 

The results of this research suggest that trainees’ prior experience has implications for 

several learner outcomes in a videogame-based training environment. Specifically, more 

experienced trainees reported greater ease using the training game’s interface, higher levels of 

training satisfaction, and increased motivation to continue training with the game. This supports 

past research indicating that the exposure to computers and videogames is meaningful to a 

learner’s experience in a game-based learning environment (Gagnon, 1985; Greenfield, 

deWinstanley, Kilpatrick, & Kaye, 1996; Subrahmanyam & Greenfield, 1996; Young et al., 

1997). 

The results also demonstrate that previous videogame experience has implications for 

videogame-based training environments which require trainee collaboration. In the current 

research, trainees with higher levels of experience more easily formed cohesive relationships 

with team members in the collaborative components of the training game, as compared to 

trainees who had less prior experience. Moreover, perceived team cohesion was found to be a 

significant mediator of the relationship between prior experience and motivation to continue 

engaging in the game, such that trainees with greater prior game experience perceived greater 

team cohesion and consequently spent more time engaging in the game. This finding intuitively 

makes sense given that our measure of training motivation primarily captures a trainee’s 

motivation to continue using the multi-player component of America’s Army. Accordingly, a 

trainee’s perceived cohesion among his/her team members should be particularly influential on 

the length of time spent playing the multi-player component. These findings corroborate prior 

cohesion research which suggests that higher levels of cohesion improve a team’s functioning 

18
and collective motivation to engage in a collaborative task (Evans & Dion, 1991; Mullen et al., 

1993; Mullen & Copper, 1994). 

Specific Videogame Experience 

The results suggest that the specificity of a trainee’s prior experience predicts learner 

outcomes. Trainees with greater experience in playing games related to the current training 

game environment, such as America’s Army and other first-person-shooter games, reported 

greater ease in using the game’s interface, higher levels of training satisfaction, and greater team

cohesion. Prior experience with America’s Army also predicted motivation to continue engaging 

in the training game. In contrast, prior experiences with specific games that do not share similar 

characteristics with the current game-based training environment were generally not related to 

learner outcomes. 

At first glance, one might have expected that online multi-player games would share 

several similarities with the multi-player component of America’s Army; and thus should have 

significantly predicted learner outcomes, particularly team cohesion. While other multi-player 

videogames developed and popularized in the private sector (e.g., Ultima Online, Everquest) do 

simultaneously engage multiple individuals in game play, such games represent a very different 

game playing experience than America’s Army. First, the number of players interacting within 

the game at any one time is vastly different. For this research, participants playing America’s

Army were formed into teams composed of a maximum of 16 players. Then, each team 

interacted with one opposing team of a similar size. Thus, only a relatively small number of 

individuals were interacting in the game environment at any one time. Games such as Everquest

are termed massively multi-player games because thousands of individuals are simultaneously 

involved in game play and the number of teams that can exist is not limited. Another distinction 

is that in the current training exercise with America’s Army, individuals were randomly assigned 

to a team and membership in those teams varied regularly; while in most online multi-player 

games, team membership is emergent and more consistent over time. Individual’s prior 

experience collaborating with specific players based on one’s own selection is likely to be a 

different experience than that of collaboration with other individuals assigned as one’s team

members.

One unexpected finding was that prior simulation game experience (e.g., with Falcon, 

Microsoft Flight Simulator, Lock On: Modern Air) was positively related to training motivation 

for the America’s Army game. A possible explanation is that simulation games are more closely 

associated to training well-defined skills (versus solely providing entertainment) as compared to 

other types of videogames. Another explanation may be that America’s Army and simulations 

share some common game features or characteristics (e.g., fast-paced game environment) that 

are critical to game success. 

The results indicate that specific prior game experiences that share similar characteristics 

with the intended training environment provide incremental validity over general videogame

experience in the prediction of learner outcomes. In other words, knowledge of both trainees’ 

general and specific videogame experiences is valuable in predicting their future experiences 

with and reactions to a given game-based training environment. 

19
Computer Self-Efficacy 

Trainees’ computer self-efficacy was also influential in predicting trainees’ learner 

outcomes such that trainees with higher computer self-efficacy beliefs reported less difficulty

using the game’s interface and higher levels of perceived team cohesion, training satisfaction, 

and training motivation than trainees with lower computer self-efficacy beliefs. Trainees’ 

computer self-efficacy also demonstrated incremental validity over general videogame 

experience in the prediction of all of the learner outcomes except training satisfaction. In other 

words, knowledge of both an individual’s prior experience and his/her level of self-efficacy 

provide unique information to the prediction of the individual’s reactions to and experiences with 

the forthcoming game-based training. This aligns with prior research suggesting that selfefficacy and experience are important predictors of various training criteria (Dyck & Smither, 

1996; Martocchio & Webster, 1992; Mathieu, Martineau, & Tannenbaum, 1993; Woodrow, 

1991). Further, the results suggest that trainees who had both a high level of computer selfefficacy and videogame experience possessed the highest levels of training motivation. Thus, 

trainee motivation is highest not only when trainees have experience with games, but also when 

they feel confident that they can work well in that environment. 

Influence of Prior Game Experience on Military Skills 

The results of the open-ended questions indicate that prior videogame experience can

both help and hinder trainees’ military-related knowledge or skills. Specifically, cadets reported 

that prior gaming experience enhance mission-related skills (including decision-making/problem

solving, multi-tasking, and attention to detail) and team-related skills (including communication 

and team organization). In contrast, first-year cadets reported that prior videogame experience 

has the potential to hinder performance in real combat situations. Reckless or careless combat 

behaviors demonstrated during game play, due to the lack of functional and combat realism of a 

gaming environment, have the potential to carry over to real combat situations. 

Implications and Conclusions 

Based on the current research findings, we suggest some practical implications for 

instructors and training games developers, as well as some future research directions. First, for 

instructors utilizing training games, we provide support for the value of assessing trainees’ 

specific types of game experience. It seems intuitive that if one has prior general videogame 

experience, he/she should have more positive experiences in any videogame-based training 

environment. However, based on the current research, this is not the case. Experience with one 

type of gaming environment does not necessarily enhance the training outcomes in a different 

type of training game environment. 

The good news is that learner experience is a malleable trainee characteristic that can be 

compensated for fairly easily. By assessing the amount and types of previous gaming 

experiences trainees possess, instructors will be able to identify those who lack the prerequisite 

game experience. In turn, instructors can then provide these trainees with targeted opportunities 

to gain such beneficial experiences prior to training. For example, if learners are to engage in a 

first-person-shooter game-based training program and some learners have little prior experience 

20
with this type of game, then the instructor would know to give them ample practice time before 

the learning segment of the training (i.e., when learners are acquiring the new skills or

knowledge taught in the game). To facilitate instructors in providing the appropriate amount of 

preparatory practice for a given learner’s needs, training game developers should incorporate a 

feature within the game that enables the instructor to select the desired amount and content of 

trainee orientation and practice. 

Further, it may be assumed that most junior Soldiers who grew up in the digital age 

would have a great deal of experience with videogames. However, this assumption does not 

seem warranted given the experience levels of the military academy cadets sampled. In the 

current sample, 17% of cadets reported they had no experience playing videogames and 44% 

reported they had limited videogame experience. Given the number of cadets with little to no 

experience, providing an orientation or additional practice with relevant games would likely be 

valuable. Doing so may improve a host of learner outcomes including training satisfaction, 

perceived team cohesion, ease in using the game’s user interface, and the length of time devoted 

to training. 

This research also suggests that a Soldier’s level of computer self-efficacy is positively 

related to trainee learner outcomes. As such, it may also be valuable for instructors to assess 

trainees’ computer and videogame related self-efficacy beliefs. Instructors could bolster the selfefficacy of those learners who question their current capability to successfully train in a gamebased learning environment. One may argue that “providing” trainees with greater self-efficacy 

is more difficult to achieve than influencing trainees’ videogame experience levels. However, 

prior research demonstrates that there is a positive relationship between experience and selfefficacy (Dyck & Smither, 1996; Henderson et al., 1995; Levine & Donitsa-Schmidt, 1997). 

When instructors are providing additional experiences with a relevant type of videogame, it is 

also likely that trainees will feel more confident using such games. Another way to enhance 

trainee self-efficacy may be to provide positive feedback and encouragement while trainees are 

beginning to maneuver through the training game. Such feedback could be provided by the 

instructor or could be built into the videogame content and delivered during game play or a pretraining/familiarization exercise. These suggestions are supported by Bandura (1997) who 

proposed that obtaining experiences resulting in successful performance or receiving feedback 

on one’s capabilities are two ways in which to develop positive self-efficacy beliefs. 

We suggest that future research investigate the impact of additional practice with 

videogames and of feedback regarding one’s game performance on a trainee’s self-efficacy and 

learner outcomes of videogame-based training environments. Future research should also 

examine the influence of self-efficacy as it relates to videogames versus the more general 

measure of self-efficacy in using computers. It is likely that self-efficacy beliefs related to 

general gaming environments, and specific types or genres of videogames, will account for 

unique variance in learner outcomes of game-based training programs beyond that of general 

computer self-efficacy. This would parallel the current research which demonstrated that the 

measurement of specific game experience is valuable beyond general game experience in 

predicting learner outcomes. 

21
Finally, future research should examine the role of trainee preference for videogames on 

learner outcomes. In the real world, videogame preference and prior experience should be 

positively correlated, such that the more one enjoys a type of videogame, the more frequently 

he/she plays this kind of game. An important question is whether it is one’s prior experience 

with videogames that influences subsequent learner outcomes or whether these relationships are 

a function of the individual’s preference for playing these games. It is possible that actual 

enjoyment or preference for game playing may be driving the relationships between game

experience and learner outcomes of the training. 

In conclusion, the way the Army conducts its training is transforming. Desktop 

simulations and gaming technology are being incorporated into a broad range of training 

environments. The current research has implications for our Soldiers’ training motivation and 

other important learner outcomes in videogame-based training environments. Maximizing these 

proximal learner outcomes should influence Soldiers’ overall training performance and 

ultimately enhance their operational capabilities.

22
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30
Appendix A 

Satisfaction with Training scale 

Response options: 1 (strongly agree) to 5 (strongly disagree)

1. Using America’s Army game allowed me to better understand combat-related cognitive skills 

and decision-making. 

2. Using America’s Army game allowed me to become more comfortable with being a member 

of a combat team. 

3. Using America’s Army game allowed me to better understand how the members of a combat 

team must work together to be successful. 

4. My performance while using America’s Army game accurately reflects my knowledge of 

small team combat tactics. 

5. I was satisfied with the experience of using America’s Army game. 

6. I was satisfied with my personal performance during America’s Army game. 

Team Cohesion scale 

Response options: 1 (not at all) to 5 (great extent)

1. To what extent was your team engaged in the multiplayer missions of the America’s Army

game?

2. To what extent did your team enjoy working on the America’s Army game?

3. To what extent did your team treat the exercise using America’s Army game as meaningful 

and important?

4. To what extent did you expect your team to derive benefits from a successful team

performance during America’s Army game?

5. To what extent did the members of your team like each other?

6. To what extent was it important that the members of your team got along with one another?

7. To what extent did the members of your team feel similar to one another?

8. To what extent was it important for members of your team to communicate during the 

mission?

9. To what extent did members of your team like being a part of this team?

A-1