ArticlePDF Available

Abstract and Figures

The authors explored the factors contributing to student learning in the context of business simulation. Our results suggest that social interaction and psychological safety had a positive impact on knowledge development in student groups, and that this synergistic knowledge development enabled students to form complex mental models. Implications of the findings are discussed.
Content may be subject to copyright.
Copyright C
Taylor & Francis Group, LLC
ISSN: 0883-2323
DOI: 10.1080/08832320903449469
Student Learning in Business Simulation: An
Empirical Investigation
Yang Xu
Penn State University, New Kensington, Pennsylvania, USA
Yi Yang
University of Massachusetts, Lowell, Massachusetts, USA
The authors explored the factors contributing to student learning in the context of businesssimu-
lation. Our results suggest that social interaction and psychological safety had a positive impact
on knowledge development in student groups, and that this synergistic knowledge development
enabled students to form complex mental models. Implications of the findings are discussed.
Keywords: business simulation, knowledge development, mental model, social interaction,
student learning
Business simulations have become an increasingly popular
teaching method in business courses (Faria, 1998, 2001; Ke-
effe, Dyson, & Edwards, 1993), such as business strategy
(Stephen, Parente, & Brown, 2002), business ethics (Wolfe &
Fritzsche, 1998), and courses on cultural differences (Chat-
man & Barsade, 1995). In contrast to traditional teaching
methods, business simulations bridge the gap between the
classroom and the world of real-life business decision mak-
ing through experiential learning experiences in which stu-
dents design, implement, and control business strategies. In
sophisticated simulations, students think in strategic ways,
solve complex problems, and integrate knowledge across
business functions. In the microworlds created by business
simulations, students can better understand the interactive ef-
fects of environment, competitors, and employees (Romme,
In previous studies of business simulations, game per-
formance is generally considered the dependent variable of
interest (Anderson, 2005; Hornaday & Curran, 1996; Schoe-
necker, Martell, & Michlitsch, 1997). Our research attempts
to explore the factors contributing to the formation of stu-
dents’ mental models. A mental model represents an in-
dividual’s knowledge structure of a specific domain (Car-
ley & Palmquist, 1992; Lyles & Schwenk, 1992; Wilson &
Rutherford, 1989). Scholars have recognized the importance
Correspondence should be addressed to Yang Xu, Penn State University,
Department of Business and Economics, 3550 Seventh Street Road, New
Kensington, PA 15068, USA. E-mail:
of mental models for student learning in management edu-
cation (Dehler, 1996; Resnick & Klopfer, 1989). A critical
task of business education is helping students develop knowl-
edge structures of specific domains. People digest informa-
tion and transform it to structured knowledge (Weick, 1995).
However, few empirical studies have used mental models as
learning outcomes in the business education literature (Nad-
karni, 2003). This study addresses this research gap. Specifi-
cally, we examine two questions regarding learning outcomes
of complex computer-based simulations: First, what factors
influence knowledge development in student groups, and,
second, to what extent does this knowledge development in-
fluence the complexity of students’ mental models? Next we
present the conceptual model and research hypotheses, fol-
lowed by the methods and results. Finally, we discuss the
limitations and implications of our findings.
Drawing on theoretical perspectives in social cognition,
group processes, and organizational learning (Baldwin, Be-
dell, & Johnson, 1997; Kasl, Marsick, & Dechant, 1997; Non-
aka, 1994; Walsh, 1995), we developed a conceptual frame-
work indicating that two factors—social interaction and psy-
chological safety—are positively related to the development
of synergistic knowledge (Figure 1). Furthermore, the devel-
opment of synergistic knowledge enhances the complexity
of the student’s mental model.
Team Psychological Safety
Social Interaction +
Complexity of mental model
FIGURE 1 A conceptual model of student learning in business simulation
Synergistic knowledge development refers to the process by
which a group integrates individual members’ perspectives
(Mu & Gnyawali, 2003). According to theories of organi-
zational learning and social cognition, collective knowledge
develops through the discussion and integration of the indi-
vidual perspectives of a specific information domain (Non-
aka; Senge, 1990; Walsh). A collective body of knowledge
consists of representation, development, and use of spe-
cific knowledge (Walsh). In business simulations, individual
members interpret tasks with their own knowledge structure.
Next, group members discuss and integrate their individ-
ual knowledge and use this collective body of knowledge to
manage the simulated company.
Business simulations focus on interactive problem solv-
ing and complex trade-offs. Teamwork is usually required
because of the complexity of the simulation. In this ac-
tive learning process, students develop a collective body of
knowledge by synthesizing the unique perspectives of the in-
dividual members (Lang & Dittrich, 1982; Mu & Gnyawali,
2003). Building on previous studies, we hypothesized that
two factors would contribute to synergistic knowledge de-
velopment in student groups—social interaction and team
psychological safety.
Social interaction refers to the process of communication in
a group (Barker & Camarata, 1998). In business simulations,
students need to understand, inform, and persuade their team-
mates concerning various issues. They frequently discuss and
debate because of the complexity and interconnectedness of
the various elements of decision making. This high level of
social interaction enhances the extent of discussion and dia-
logue among group members (Mu & Gnyawali, 2003). First,
social interaction drives the creation of collective meaning
(Thompson & Fine, 1999). As students communicate and
collaborate repeatedly with their peers, they tend to develop
a sophisticated understanding of the simulation and iden-
tify effective strategies and tactics. Second, social interac-
tion facilitates a feedback process that helps group members
understand their performance and specific responsibilities,
examine member actions, and decide future actions (John-
son, Johnson, Stanne, & Garibaldi, 1990). In the feedback
sessions, students’ discussions may create a process of so-
cial discovery, clarifying individual members’ opinions and
centralizing their preferences (Eisenhardt, Kahwajy, & Bour-
geois, 1997). Third, high social interaction enables people to
exchange tacit knowledge necessary for complex problem
solving (Nonaka, 1994). Learning is enhanced through ex-
tensive communication among the group members (Baldwin
et al., 1997); and knowledge is developed in this interactive
process (Barker & Camarata). Consequently, we hypothe-
sized that social interaction would play a positive role in
synergistic knowledge development.
Hypothesis 1 (H1): In business simulations, the level of social
interaction among group members would be positively
related to the development of synergistic knowledge.
Team psychological safety refers to the group members’ be-
liefs that members of their group are open and receptive to
different perspectives and that the other members would not
reject or punish someone for bringing a different viewpoint
(Edmondson, 1999). This mutual respect and trust provides
psychosocial support (Ibarra, 1995). At the same time, peo-
ple in a psychologically safe environment display higher lev-
els of self-efficacy and develop better mechanisms to deal
with conflicts (Campion, Medsker, & Higgs, 1993). Mem-
bers need to be open to others’ ideas to create productive
group work (Kasl et al., 1997). The appreciation of oth-
ers’ views enables the group members to integrate multiple
views and develop synergistic knowledge (Mu & Gnyawali,
2003). Consequently, learning behavior is enhanced in the
psychologically safe environment. Further, silent members
are more likely to contribute to the discussion when the
group members encourage group learning behavior and con-
structive critique of different views. This group learning en-
riches the individual member’s understanding of the busi-
ness simulation. The constructive critique of diverse views
sharpens the individual member’s knowledge of this domain.
Therefore, we hypothesized that team psychological safety
would positively impact the development of synergistic
H2: In business simulations, the team psychological safety
among group members would be positively related to
the development of synergistic knowledge.
Mental models represent the stock of knowledge developed
by students in a knowledge domain (Nadkarni, 2003). They
capture an individual’s understanding of a specific domain
and reflect how the domain knowledge is arranged, con-
nected, or situated in their minds (Carley & Palmquist, 1992;
Lyles & Schwenk, 1992; Nadkarni; Schneider & Schmitt,
1992; Wilson & Rutherford, 1989). In problem-solving situ-
ations, individuals make sense of complex problems and en-
gage in intensive mental processing (Hong & O’Neil, 1992).
The complexity of a mental model reflects the breadth of a
student’s understanding of the specific knowledge domain
(Nadkarni; Wilson & Rutherford). Complexity is measured
by the number of concepts and linkages between concepts
in a mental model (Carley & Palmquist; Eden, Ackermann,
& Cropper, 1992). The student with more complex mental
models is more likely to identify key concepts and link these
concepts in solving problems (Nadkarni).
In a business simulation, we would expect that the de-
velopment of synergistic knowledge has an impact on the
complexity of students’ mental models for the following rea-
sons. First, when students analyze a problem from different
perspectives and identify multiple alternatives, they are less
likely to miss important variables relating to the problem sit-
uation (Lyles & Schwenk, 1992). In addition, in diagnosing
an ambiguous and uncertain problem situation, the syner-
gistic knowledge development enables students to establish
more cause–effect relations between these variables. Finally,
communication and leadership skills are enhanced during
the process of integrating different perspectives (Colbeck,
Campbell, & Bjorklund, 2000). These improved communi-
cation and leadership skills help students understand their
peers’ opinions and enrich their own domain knowledge. To
conclude, we proposed that the development of synergistic
knowledge would have a positive impact on the complexity
of students’ mental models.
H3: In business simulation, the development of synergistic
knowledge in student groups would be positively related
to the complexity of students’ mental models.
Research Setting
Data were collected from 140 senior business students en-
rolled in six sections of an undergraduate strategic manage-
ment course at two large northeastern public universities. The
Capstone ( business simulation was
used as an ongoing hands-on experience for these students.
The two coauthors taught all six sections of the course dur-
ing two semesters, using the same teaching approach. Partici-
pants were randomly assigned to four- or five-member teams.
Each team acted as an executive committee responsible for
running a company that manufactured an electronic sensor
device in a competitive environment. The simulation was de-
signed to emphasize integration across business functions,
such as research and development, marketing, production,
human resources, total quality management, and finance.
Each team developed a competitive strategy (e.g., cost or
differentiation) and used decision-support software to deter-
mine product positioning, price, sales, promotion, research
and development budgets, production levels, and financing
requirements. Team decisions were processed and then re-
leased to teams in the form of a report containing information
about the industry and the competitors’ performance.
We requested students to complete a three-page survey re-
garding their group processes and understanding of the Cap-
stone simulation after they had completed a specific simu-
lation year. Out of 180 questionnaires sent to the students,
140 were completed for a response rate of 78%. On the basis
of previous research literature, the survey items were mea-
sured by use of a 7-point Likert-type scale ranging from 1
(strongly disagree)to7(strongly agree), with several reverse-
coded items. Table 1 presents the results of factor analy-
sis, and questionnaire items for social interaction, psycho-
logical safety, and synergistic knowledge development. The
exploratory factor analysis with varimax rotation generated
three factors.
Mental models are typically represented as cognitive maps
(Carley & Palmquist, 1992; Ford & Hegarty, 1984). They fo-
cus on the concepts and the causal linkages between those
concepts in individuals’ belief systems (Finkelstein & Ham-
brick, 1996). To construct a student’s cognitive map on busi-
ness simulation, we first developed a pool of constructs by
analyzing the functional areas in the Capstone business sim-
ulation. The questionnaire items on cognitions were finalized
based on the analysis and a pilot test. In the second step, we
had each student select a fixed number of constructs by iden-
tifying items from a constant pool of constructs. Finally, we
constructed the causal map of each student by having each
one assess the influence of each selected construct on the
other selected constructs.
We input each causal map matrix into the UCINET soft-
ware (Borgatti, Everett, & Freeman, 2002) to compute the
complexity measure. Complexity of the mental model is mea-
sured by the density of a cognitive map. The density of a
cognitive map refers to the ratio of causal links to the total
number of constructs in the causal map (Eden et al., 1992).
A higher ratio indicates that the student’s cognitive map is
densely connected and presumably higher in cognitive com-
Ccomplexity =links
const r uct s
The questionnaire asked the students to report their in-
dividual effort (the average weekly hours the student spent
individually on the decisions for the past two years), time
(the average time the student group spent on making deci-
sions for the present year), and the simulation year the group
has finished the decisions. Because numerous studies have
Results of Exploratory Factor Analysis (Principal Component Analysis)
knowledge Team psychological
Item development Social interaction safety
1. The unique skills and talents of all the members of my group were fully valued
and utilized.
.869 .263 .072
2. My group’s work integrated all the different opinions of the group members. .771 .376 .120
3. Compared with other teams, our team was better in terms of the way people got
along together.
.832 .136 .219
4. Compared with other teams, our team was better in terms of the way people
helped each other on the job.
.893 .203 .204
5. We regularly took time to figure out ways to improve our work processes and
.436 .673 .150
6. My group had a feedback session to evaluate our group processes and discuss
how to improve our group work.
.223 .859 .083
7. Members of our team asked each other for feedback on their work. .306 .730 .302
8. The members of my team sometimes rejected others for being different. (reverse
.187 .019 .850
9. The members of my group had a hard time listening to an opposing point or
perspective. (reverse scored)
.249 .153 .685
Eigenvalue 3.493 2.261 1.899
Percentage of variance explained by each factor 26.900 17.400 14.600
shown that gender plays a significant role in student learn-
ing (Clifton, Perry, Roberts, & Peter, 2008; Crombie, Pyke,
Silverthorn, Jones, & Piccinin, 2003; Kaenzig, Hyatt, & An-
derson, 2007), gender was a control variable. In addition, we
added three dummy variables to control for the differences
in terms of instructor, section, and major.
Table 2 presents the descriptive statistics and correlation ma-
trix of all variables. We performed hierarchical regression
analysis to test the hypotheses. First, we regressed the control
variables on each dependent variable. Next we regressed the
control variables and independent variables on each depen-
dent variable. This two-step hierarchical regression analysis
allows the effects of each independent variable to account
for variance explained beyond that of the control variables.
Results for the dependent variable synergistic knowledge de-
velopment are presented in Table 3. Results for the dependent
variable mental model complexity are presented in Table 4.
H1and H2referred to the relationship between both so-
cial interaction and team psychological safety and syner-
gistic knowledge development. As shown in Table 3, social
Descriptive Statistics and Correlations (
Variable 1234567891011MSD
1. Instructor 0.79 0.41
2. Section .01 — 0.36 0.48
3. Major .04 .50∗∗ — 0.31 0.46
4. Complexity .20.09 .14 — 0.24 0.14
5. Year .10 .80∗∗ .08 .04 — 3.48 1.72
6. Individual
.23∗∗ .11 .03 .16 .06 — 2.88 0.58
7. Time .25∗∗ .10 .06 .13 .09 .15 — 2.91 0.55
8. Gender .18.01 .03 .26∗∗ .04 .12 .09 — 0.41 0.49
9. Synergy .41∗∗ .11 .08 .23∗∗ .11 .04 .19.12 — 5.96 1.16
10. Social
.46∗∗ .20.09 .17.26∗∗ .06 .27∗∗ .08 .62∗∗ —5.56 1.27
11. Psycholog-
.05 .10 .04 .22∗∗ .04 .17.03 .14 .42∗∗ .40∗∗ —6.51 0.82
p<.05. ∗∗p<.01.
Results of Hierarchical Regression: Synergistic
Knowledge Development as Dependent Variable
Model 1 Model 2 Model 3
Variable βpβpβp
Instructor .398 .000 160 .040 .251 .001
Section .192 .032 .024 .764 .040 .608
Major .165 .066 .045 .574 .073 .338
Gender .049 .532 .047 .489 .002 .981
.532 .000 .377 .000
.280 .000
R2.204 .000 .406 .000 .464 .000
R2.201 .000 .058 .000
interaction (β=.377, p=.000) and team psychological
safety (β=.280,p=.000) positively correlated with syner-
gistic knowledge development. The entire regression equa-
tion explained 46.4% of the variance in synergistic knowl-
edge development (p <.001). The results supported H1and
H3referred to the relationship between synergistic knowl-
edge development and mental model complexity. As shown
in Table 4, synergistic knowledge development positively
correlated with mental model complexity (β=.213,p=
.027). The entire regression equation explained 16.2% of the
variance in synergistic knowledge development (p <.005).
The results supported H3.
This research extends the literature on the factors that en-
hance student learning in business simulations. The results
Results of Hierarchical Regression: Mental Model
Complexity as Dependent Variable (
Model 1 Model 2
Variable βpβp
Instructor .141 .131 .052 .604
Section .042 .831 .060 .764
Major .122 .304 .177 .140
Gender .226 .010 .212 .015
Year .029 .869 .037 .830
Individual effort .080 .362 .113 .197
Time .040 .650 .023 .794
.213 .027
R2.128 .016 .162 .004
R2.034 .027
of the analysis suggest that social interaction and a psycho-
logically safe team environment help students to develop syn-
ergistic knowledge, which enriches students’ mental models
of business simulation. Students develop high-order knowl-
edge and problem-solving skills by synthesizing diverse per-
spectives. Our findings have the following implications for
teaching and research.
For teaching, instructors need to provide students with
systematic guidance of team-based business simulations in
order to foster a psychologically safe group environment.
Early in the semester, instructors should help students to
develop a set of group norms that promote open exchange
of ideas (Bolton, 1999) and emphasize group processes to
facilitate interactions among students. During the semester,
instructors need to continuously monitor the groups, remind
them of their group norms, and emphasize various ways of de-
veloping synergistic knowledge. Adequate class time needs
to be allocated to help students to understand the mechanisms
necessary for constructive discussion. In addition, instructors
should represent learning outcomes as mental models to eval-
uate student learning in a specific knowledge domain so that
students are aware of what they know and consequently im-
prove their knowledge or skills. This might have resulted in
a higher level of student learning.
For further research, researchers should examine the re-
lationship between synergistic knowledge development and
the objective simulation performance. Second, an interesting
research topic would be an examination of the student group’s
mental model by having the group as a whole construct the
cognitive map, so as to study the effects of individual- and
group-level variables on synergistic knowledge development
and mental models. Third, a related issue to study is the
effects of varying group sizes on student learning in busi-
ness simulations. Bigger groups experience intensified cog-
nitive conflict (Amason & Sapienza, 1997); however, group
members are more likely to bring diverse perspectives to dis-
cussion (Bantel & Jackson, 1989). Fourth, because various
instructional methods contribute to student learning differ-
ently, scholars should also use mental models to assess the
level of student learning in various instructional contexts.
Fifth, the present study focused on undergraduate students
with low learning maturity; future researchers should exam-
ine the level of learning of MBA students with higher learn-
ing maturity. Finally, a limitation of the present study was
that all the measures were based on students’ self-reports.
Researchers should develop and test objective measures of
student learning in business simulations and other knowledge
Amason, A. C., & Sapienza, H. J. (1997). The effects of top management
team size and interaction norms on cognitive and affective conflict. Jour-
nal of Management,23, 495–516.
Anderson, J. R. (2005). The relationship between student perceptions of team
dynamics and simulation game outcomes: an individual-level analysis.
Journal of Education for Business,81, 85–90.
Baldwin, T. T., Bedell, M. D., & Johnson, J. L. (1997). The social fabric of
a team-based MBA program: Network effects on student satisfaction and
performance. Academy of Management Journal,40, 1369–1397.
Bantel, K. A., & Jackson, S. E. (1989). Top management and innovations
in banking—Does the composition of the top team make a difference?
Strategic Management Journal,10, 107–124.
Barker, R., & Camarata, M. (1998). The role of communication in creating
and maintaining a learning organization: Preconditions, indicators, and
disciplines. The Journal of Business Communication,35, 443–467.
Bolton, M. (1999). The role of coaching in student teams: A just-in-time
approach to learning. Journal of Management Education,23, 233–250.
Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). Ucinet for Windows:
Software for social network analysis: Harvard, MA: Analytic Technolo-
Campion, M. A., Medsker, G. J., & Higgs, A. C. (1993). Relations between
work group characteristics and effectiveness—Implications for designing
effective work groups. Personnel Psychology,46, 823–850.
Carley, K., & Palmquist, M. (1992). Extracting, representing and analyzing
mental models. Social Forces,70, 601–636.
Chatman, J. A., & Barsade, S. G. (1995). Personality, organizational culture,
and cooperation: Evidence from a business simulation. Administrative
Science Quarterly,40, 423–443.
Clifton, R. A., Perry, R. P., Roberts, L. W., & Peter, T. (2008). Gender, psy-
chosocial dispositions, and the academic achievement of college students.
Research in Higher Education,49, 684–703.
Colbeck, C. L., Campbell, S. E., & Bjorklund, S. A. (2000). Grouping in
the dark—What college students learn from group projects. Journal of
Higher Education,71, 60–83.
Crombie, G., Pyke, S. W., Silverthorn, N., Jones, A., & Piccinin, S. (2003).
Students’ perceptions of their classroom participation and instructor as a
function of gender and context. Journal of Higher Education,74, 51–76.
Dehler, G. E. (1996). Management education as intentional learning: a
knowledge-transforming approach to written composition. Journal of
Management Education,20, 221–235.
Eden, C., Ackermann, F., & Cropper, S. (1992).The analysis of cause maps.
The Journal of Management Studies,29, 309–324.
Edmondson, A. (1999). Psychological safety and learning behavior in work
teams. Administrative Science Quarterly,44, 350–383.
Eisenhardt, K. M., Kahwajy, J. L., & Bourgeois, L. J. (1997). How man-
agement teams can have a good fight. Harvard Business Review,75(4),
Faria, A. J. (1998). Business simulation games: Current usage levels—An
update. Simulation & Gaming,29, 295–308.
Faria, A. J. (2001). The changing nature of business simulation/gaming
research: A brief history. Simulation & Gaming,32, 97–110.
Finkelstein, S., & Hambrick, D. (1996). Strategic leadership: Top executives
and their effects on organizations. Minneapolis, MN: West Publishing
Ford, J., & Hegarty, H. (1984). Decision makers’ beliefs about the causes
and effects of structure: An exploratory study. Academy of Management
Journal,27, 271–291.
Hong, E., & O’Neil, H. F. (1992). Instructional strategies to help learners
build relevant mental models in inferential statistics. Journal of Educa-
tional Psychology,84, 150–159.
Hornaday, R. W., & Curran, K. E. (1996). Formal planning and the perfor-
mance of business simulation teams. Simulation & Gaming,27, 206–222.
Ibarra, H. (1995). Race, opportunity, and diversity of social circles in man-
agerial networks. Academy of Management Journal,38, 673–703.
Johnson, D. W., Johnson, R. T., Stanne, M. B., & Garibaldi, A. (1990). Im-
pact of group processing on achievement in cooperative groups. Journal
of Social Psychology,130, 507–516.
Kaenzig, R., Hyatt, E., & Anderson, S. (2007). Gender differences in college
of business educational experiences. Journal of Education for Business,
83, 95–100.
Kasl, E., Marsick, V., & Dechant, K. (1997). Teams as learners: A research-
based model of team learning. Journal of Applied Behavioral Science,
33, 227–246.
Keeffe, M. J., Dyson, D. A., & Edwards, R. R. (1993). Strategic management
simulations: A current assessment. Simulation & Gaming,24, 363–368.
Lang, J., & Dittrich, J. (1982). Information, skill building, and the devel-
opment of competence: an educational framework for teaching business
policy. Academy of Management Review,7, 269–279.
Lyles, M. A., & Schwenk, C. R. (1992). Top management, strategy and
organizational knowledge structures. Journal of Management Studies,
29, 155–174.
Mu, S. H., & Gnyawali, D. R. (2003). Developing synergistic knowledge in
student groups. Journal of Higher Education,74, 689–711.
Nadkarni, S. (2003). Instructional methods and mental models of students:
An empirical investigation. Academy of Management Learning and Edu-
cation,2, 335–351.
Nonaka, I. (1994). A dynamic theory of organizational knowledge creation.
Organization Science,5, 14–37.
Resnick, L. B., & Klopfer, L. E. (1989). Toward the thinking curriculum:
an overview. In L. B. Resnick & L. E. Klopfer (Eds.), Toward the think-
ing curriculum: Current cognitive research (pp. 1–18). Alexandria, VA:
Association for Supervision and Curriculum Development.
Romme, A. G. L. (2003). Learning outcomes of microworlds for manage-
ment education. Management Learning,34, 51–61.
Schneider, B., & Schmitt, N. (1992). Staffing organizations (2nd ed.). Long
Grove, IL: Waveland Press.
Schoenecker, T. S., Martell, K. D., & Michlitsch, J. F. (1997). Diversity,
performance, and satisfaction in student group projects: An empirical
study. Research in Higher Education,38, 479–495.
Senge, P. M. (1990). The fifth discipline: The art and practice of the learning
organization. New York: Doubleday.
Stephen, J., Parente, D. H., & Brown, R. C. (2002). Seeing the forest and the
trees: Balancing functional and integrative knowledge using large-scale
simulations in capstone business strategy classes. Journal of Management
Education,26, 164–193.
Thompson, L., & Fine, G. (1999). Socially shared cognition, affect, and
behavior: A review and integration. Personality and Social Psychology
Review,3, 278–302.
Walsh, J. P. (1995). Managerial and organizational cognition—Notes from
a trip down memory lane. Organization Science,6, 280–321.
Weick, K. E. (1995). Sensemaking in organizations. Thousand Oaks, CA:
Wilson, J. R., & Rutherford, A. (1989). Mental models: Theory and appli-
cation in human factors. Human Factors,31, 617–634.
Wolfe, J., & Fritzsche, D. J. (1998). Teaching business ethics with
management and marketing games. Simulation & Gaming,29, 44–
... Though psychological safety is well researched in the workplace, little attention has been given to the educational context. Mu and Gnyawali's (2003) survey of enablers of student team effectiveness found that task conflict had a negative impact on knowledge development and that this was moderated by psychological safety (see also Xu & Yang, 2010). Additional studies have suggested psychological safety increases when there is greater perceived peer and tutor support (Schepers et al., 2008) or when educators use smiley ☺ emojis in communication with HE students (Marder et al., 2019). ...
... Our second contribution, further extends knowledge of psychological safety in HE by evidencing a greater breadth of positive outcomes, which until now has been mostly limited to knowledge development (Mu & Gnyawali, 2003;Xu & Yang, 2010). Specifically, our findings imply that psychological safety also increases; team-performance, team learning, interpersonal communication and creativity Fig. 2. Summarises contributions arises from triangulation of the findings. ...
While psychological safety is widely acknowledged to be a crucial factor in determining how well teams function, little attention has been paid to this phenomenon in management education and HE more broadly. This highlights an important gap, given the ‘thorny’ nature, and pervasive use, of group work. We contribute the first examination of an HE intervention to increase psychological safety. Specifically, through a two-phase mixed methods approach (pre/post surveys and focus groups, student diaries), we examine the implementation of Agile project management principles in both an undergraduate and postgraduate digital marketing course (total n = 131). The findings illustrate that the intervention increased psychological safety along with team-performance, group learning, interpersonal communication and creativity, whilst also reducing the free-rider problem. The study provides three contributions. First, we extend knowledge of psychological safety by showing it can be fostered through interventions providing two core antecedents (supporting facilitation and a cohesive framework). Second, we build knowledge of psychological safety in education by evidencing a greater breadth of positive outcomes, which until now has been mostly limited to knowledge development. Third, we expand understanding of implementing group work interventions in management, providing five important considerations for educational practitioners.
... If those role-play exercises are employed before participants learn about underlying mechanisms, principles etc., they encourage error making and reflecting about those errors in hindsight. They provide a safe background (Xu & Yang, 2010) to try out new behaviors and gain feedback from many sides, without eventually endangering a substantive agreement or relationship in reality (Lewicki, 1986). ...
For a couple of years, customer firms have been inviting shortlisted suppliers to so-called ‘supplier days’, where they negotiate potential deal proposals in parallel with the competing suppliers. We describe these parallel, competitive order negotiations (PCONs) and thereby introduce them to the academic B2B community. Supplier salespeople are regularly overwhelmed by these practices and require more and more specific training. We review the literature on effective salespersons' skills training with a focus on sales negotiation and then present a role-play simulation of PCONs for training purposes, called “Lithium Ion Battery”, developed in close cooperation between the academic and practitioner authors. We discuss learning objectives of the simulation, closely linked to the characteristics of PCONs, and then present the simulation set-up including the cover story, negotiable issues, involved parties, and simulation procedures. We disclose our simulation development, testing, and application, and discuss challenges encountered on the way. Running the simulation in corporate and Executive MBA trainings shows a high degree of external validity and participant buy-in. Preliminary evidence of training evaluation is also positive. We conclude that the presented simulation is a valuable and suitable training device.
... They can portray authentic characters, improvise responses, and encourage the participants' engagement (Rudd & Churchouse, 2007). Their ability to turn attention to meaningful issues elicits focused, relevant, and effective participant and audience learning and transference of the acquired practices to classroom instruction (Xu & Yang, 2010). Moreover, the actors are specifically trained for each scenario to direct the participant towards student-centred teaching. ...
One of the required 21st-century skills necessary to cope with challenging tasks in teaching is nurturing active independent learners who can perform self-regulated learning (SRL). To support teachers in attaining and transferring their newly acquired knowledge and practices to real-time teaching in the classroom, an effective professional development programme should include authentic environments that enhance autonomous learners. We introduce a theoretical-practical model that integrates simulations with professional actors (SIM) with SRL principles (SIM-SRL). The current study aims to examine the contributions of the integrated SIM-SRL model, to leverage training with a unique simulative environment supported by metacognitive SRL questions and to nurture student-centred practices. In a quasi-experimental study, we examined the environmental effects on 113 primary school teachers by comparing three groups: SIM-SRL, SIM only, and a control exposed to a meaningful learning programme. Video-recorded lessons and self-reflections after the lesson revealed four student-centred teaching practices that support SRL: knowledge construction, meta-cognitive questions, think-time and collaboration. Results indicated that teachers in the SIM-SRL group had significantly higher performance scores, followed by the SIM group, which in turn outper-formed the control group. Implications for professional development programmes are discussed. ARTICLE HISTORY
More and more educators are adopting simulations for teaching students and training individuals.A more comprehensive model proposing key simulation features is needed for simulation designers and educators. The aim of the study is to propose a theoretical model for examining simulation features in digital-based learning and the impact of simulation features on higher-order thinking. Data was collected from 301 business management students from two universities. Study One focused on a university in the U.S. (North America) and Study Two focused on a university in Peru (South America). The findings; confirm that the three key components comprising simulation features are: simulation design, simulation; interactivity, and simulation realism. The results also support the operationalization and conceptualization of simulation features as a multi-factor, higher-order construct. Lastly, simulation features have an impact on higher order thinking skills, including critical thinking and reflective thinking. Educators and content developers should ensure they consider the specific simulation features discussed in this research when designing and selecting simulations.
Simulation-based learning (SBL) as a learner-centred educational approach fosters students‘ experiential learning by providing authentic tasks in a real-world oriented learning environment. SBL settings are supposed to integrate different dimensions of learning including cognitive, affective and social aspects. Simulation games as a widely used tool in SBL are characterized among others as collaborative, team-based environments fostering learners’ understanding of concepts and improving their ability to apply their theoretical knowledge in practical fields. The use of and research on simulation games has strongly increased throughout the last decades, but the few empirical findings in the literature are ambiguous. The present study contributes to a better understanding of relations between collaborative facets, emotional experience, in-game success as a performance index and learning outcomes during a complex general management simulation. It also focuses on the use of process journals to gather data during the simulation game process in classes of business informatics students in their last semester at a German Cooperative State University. Data of 49 third-year students (m = 36, f = 12, missing = 1; age ranged from 20 to 25) was collected on three occasions: (1) A self-report questionnaire prior to the simulation game. (2) A periodic process journal was administered during the simulation game at the end of each of the six team phases to collect data on participants’ perceived team collaboration and emotional experience. (3) After the simulation game, declarative, conceptual, and procedural knowledge was assessed. Correlation analysis showed medium scores in a range between 0.38 < r < 0.76 when significant, U-test showed results between 0.39 and 0.81 when significant. Our results indicate an association between a cohesive atmosphere including psychological safety and a structured team organization and positive epistemic emotions on the one hand with performance and conceptual as well as procedural knowledge on the other hand. Hence, we argue for the need to organize and support team processes during business simulation games carefully when facilitating such environments with students, whereas we could not find support for a strong connection between learners’ personality with simulation game outcomes.
Full-text available
Zusammenfassung Die Bedeutung von psychologische Sicherheit und Teamidentifikation sowie die Faktoren für deren Entstehung werden im Kontext von New Work und agilem Arbeiten diskutiert. In einer empirischen Studie wurden Teammitglieder nach Merkmalen ihres Teams, der wahrgenommenen psychologischen Sicherheit und der Identifikation mit dem Team befragt. Die Ergebnisse unterscheiden und identifizieren wesentliche Faktoren zur Beschreibung von Arbeitsteam. Weiterhin konnte ein enger Zusammenhang zwischen psychologischer Sicherheit und Teamidentifikation nachgewiesen werden. Unterschiede zwischen beiden Konstrukten liegen auf der Sozialdimension, die als Prädiktor der Teamidentifikation einen Unterschied zur psychologischen Sicherheit markiert.
Full-text available
Great technological leaps in computational capacity and machine autonomy have increased the business community’s expectations of simulators. In joining the conversation on simulators’ ability to reproduce the reality of actual, possible, past, and future worlds, this paper draws on the literature in analytical philosophy on counterfactuals. It identifies three functions of simulations (training, advising, and forecasting) and further inquires into their ontological and epistemological assumptions to show how they limit the quest for reality of higher-performance simulators in each of these three areas. This argument is not only meant to contribute to adjusting scholars’ and practitioners’ expectations and uses of simulations; it also calls for a more in-depth and critical study of the social implications of relying on them.
This chapter examines the experimental use of Cesim™ Global Challenge, a computer-based business simulation, in an undergraduate international business program in Bogota, Colombia. The authors analyzed the data from the simulation through the application of a nonparametric statistical analysis, in addition to the application of an ex-post survey instrument, in order to assess the relevance of using simulations in the acquisition of managerial skills among undergraduate students. Key findings include the observation of positive effects of computer simulations in learning environments, as they occur in the literature. The authors accepted the hypothesis that stated that more time spent in the simulation leads to better results in the default winning criteria. Finally, the survey instrument confirmed that the use of the simulation helped the students develop managerial soft skills.
A developmental approach based on education theory is proposed as a planning model for the business policy course Structured on three levels each of information acquisition, skill building, and the development of competence, the framework integrates a variety of widely accepted pedagogical approaches and techniques—a macro perspective suitable for setting teaching objectives for the policy course.
In this study I explore the differences in the mental models of students exposed to three instructional methods of teaching an organizational behavior course-lecture-discussion, experiential, and hybrid. The lecture-discussion and experiential methods are integrated into a "hybrid method" to exploit the synergy between the best features of the two methods. My results suggest that the students in the hybrid group had more complex mental models than those exposed to either the lecture-discussion or the experiential method. Implications of the findings are discussed.
A developmental approach based on education theory is proposed as a planning model for the business policy course. Structured on three levels each of information acquisition, skill building, and the development of competence, the framework integrates a variety of widely accepted pedagogical approaches and techniques-a macro perspective suitable for setting teaching objectives for the policy course.
There is mounting evidence that effective top management teams engage in cognitive conflict but limit affective conflict. Cognitive conflict is task-oriented disagreement arising from differences in perspective. Affective conflict is individual-oriented disagreement arising from personal disaffection. This study of 48 TMTs found that team size and openness were positively related to cognitive conflict. While team size was also associated with greater affective conflict, when teams had high levels of mutuality, greater openness led to less affective conflict. The findings have implications for improving strategic decision making through the use of conflict.