Debriefing’s Influence on Learning in Business Game: An Experimental Design

Abstract

This paper studies the influence of debriefing in the learning of the participants of business games. Through quasi-experimental study we examined the self-declarations of 112 undergraduate Business Management
students undertaking the 8th term, divided into two groups: experimental, exposed to debriefing; and control, not exposed to the debriefing. MannWhitney´s tests revealed that the quantum of learning perceived by the
members of the experimental group was statistically significantly higher than the members of the control group in seven out of nine learning variables assessed (p < 0.05). The average effect size (d = 0.45) shows an average improvement of 18%. These results suggested that the debriefing positively influence on experiential learning cycle promoted by business games. In the perspective of Kolb’s experiential learning cycle (Kolb, 1984), our findings suggest that Reflective observation and Abstract conceptualization stages can be reinforced by subsequent debriefing activities to the simulation rounds, in order to enhance continuous processes of action and reflection of the participants, according to the spiral experiential learning cycle.

Full text



Adonai Jose Lacruz †
IFES - Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo
Bruno Luiz Américo Ω
UFES - Universidade Federal do Espírito Santo

With the support of computer science and theories of learning,
business games have become educational alternatives in the teaching-
learning process. Specically in Brazil, the use of business games
is present in almost half of the courses of Business Management,
according to Araújo, Brito, Correia, Paiva and Santos (2015).
Several studies have demonstrated that business games can
contribute to the learning of its participants, many of which are based
on the experiential learning theory as theoretical approach, markedly
from the experiential learning cycle (e.g. Ben-Zvi & Carton, 2008,
Crookall & Thornagate, 2009, Meij, Leemkuil & Li, 2013, Dias, Sauaia
& Yoshizaki, 2013, Araújo et al., 2015). The experiential learning
cycle considers learning as a spiral quadric cycle where people learn
through experience, which supports the translation of experiences
into concepts, allowing their application in new experiences: concrete
experience, abstract conceptualization, reexive observation and active
experimentation (Kolb, 1984).
This article has a Creative Commons License - Attribution 3.0 Not Adapted.
Corresponding author:
† IFES - Instituto Federal de Educação,
Ciência e Tecnologia do Espírito Santo
E-mail: adonai.lacruz@ifes.edu.br
Ω UFES - Universidade Federal do Espírito
Santo
E-mail: brunolaa@hotmail.com
Received: 04/28/2016.
Revised: 05/31/2016.
Accepted: 03/21/2017.
Published Online: 02/15/2018.
DOI: http://dx.doi.org/10.15728/bbr.2018.15.2.6
ABSTRACT
is paper studies the inuence of debrieng in the learning of the
participants of business games. rough quasi-experimental study we
examined the self-declarations of 112 undergraduate Business Management
students undertaking the 8th term, divided into two groups: experimental,
exposed to debrieng; and control, not exposed to the debrieng. Mann-
Whitney´s tests revealed that the quantum of learning perceived by the
members of the experimental group was statistically signicantly higher
than the members of the control group in seven out of nine learning
variables assessed (p < 0.05). e average eect size (d = 0.45) shows an
average improvement of 18%. ese results suggested that the debrieng
positively inuence on experiential learning cycle promoted by business
games. In the perspective of Kolb’s experiential learning cycle (Kolb,
1984), our ndings suggest that Reective observation and Abstract
conceptualization stages can be reinforced by subsequent debrieng
activities to the simulation rounds, in order to enhance continuous
processes of action and reection of the participants, according to the
spiral experiential learning cycle.
Keywords: Business game; Moderation; Experiential learning; Experiment.

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Research that evaluates the contributions of business games in learning for business
administration students (focus of this study) used variables operationalized in terms of
management training as a proxy for learning. These variables can be grouped into three
dimensions: knowledge, skills and attitudes (e.g. Sauaia, 1995, Lacruz & Villela, 2006,
Dias, Moreira & Stosick, 2013, Fitó-Bertran, Hernández-Lara, Serradell-López, 2015).
Studies suggest a broad set of variables that can aect the perception of the participants
regarding their learning, such as gender, cognitive style, complexity of business game,
duration of the simulation, previous contact with another business game, method to evaluate
the performance of business game etc. In this perspective, there are authors who advocate
debrieng (also termed as after-action reviews) as a critical stage of business games in
relation to participants’ learning (Peters &Vissers, 2004, Ben-Zvi &Carton, 2008, Kriz,
2010, Meij et al., 2013). The central argument is that during debrieng the participants
promote after-action reections in the quest to understand what happened and the reason
why, so that they could learn from the ex post reection. Although there is also abundant
literature on debrieng (e.g. Meij et al., 2013, Tannenbaum & Cerasoli, 2013), no empirical
research on the moderating role of debrieng in business games was identied in previous
studies, so little is known, objectively, about its inuence. From what we can question: When
adopting games with and without debrieng, can we expect asymmetry in participants’
learning? Would there be asymmetry in relation to the learning dimensions perceived by the
participants and/or in relation to the stages of the experiential learning cycle? Can business
games participants, without debrieng, not close the experiential learning cycle due to lack
of reective activities? Or, in the opposite direction, would the elements present in business
games lead the participants to promote reections during the decision-making process and
in the monitoring of results that would make the eect of after-action reection during
the debrieng into a marginal eect? The observation of this research gap motivated the
accomplishment of this study, in the search for the improvement of the learning process
with business games.
In this connection, we seek to contribute with the advancement of this knowledge,
exploring the inuence of debrieng on business games, more specically when applied to
undergraduates in Business Administration. We clarify that the teaching-learning strategies
are not considered as mutually exclusive, advocating in favor of business games to the
detriment of other approaches, since business games are considered as an alternative of
teaching-learning that, along with other teaching-learning techniques and tools (expository
classes, case studies, junior enterprise, extension activities etc.), can collaborate so that
learning is more eective and that students have greater satisfaction during the process.
The results of this study bring important advances to the eld. Although many studies
suggest relationships between debrieng and learning (e.g. Gentry, 1990, Peters & Vissers,
2004, Ben-Zvi & Carton, 2008, Kriz, 2010, Meij et al., 2013), we identied no empirical
study that objectively evaluated the possible inuences. Meij et al. (2013), in comparing
two conditions (individual and collaborative self-debrieng) from the application of a set of
individual business game with high school students in Taiwan, evidenced that the individual
performance in the participants’ game in individual self-debrieng increased more than that
of the participants in the condition of collaborative self-debrieng.
This study expands the scope when analyzing the inuences considering dierent
learning dimensions in conditions with and without debrieng. To our knowledge, these
relationships have not yet been examined, so this study advances in the discussions of the
eect of debrieng on learning in business games.

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
From the 1950s, with the development of micro-computing, simulators for didactic
support emerged that allowed the development of teaching-learning experiences termed
as business games. Its use as a teaching tool in Higher Education Institutions (HEI) dates
back to 1956, with the launch of Top Management Decision Simulation in the United States
(Keys& Wolfe, 1990). Since then, the use of business games as a teaching-learning tool
in business schools and as a research theme has been increasing. Its usage as a teaching-
learning tool with students in the business area has been growing progressively around
the world and the main reason for its popularity seems to be associated with the view that
business games are tools that allow students to learn from the playful experiences that turn
participants into central actors of the teaching-learning process (Sauaia, 1995,Gentry, 1990,
Peach & Hornyak, 2000).
Business games, such as educational technique, are designed to provide participants
with a learning experience, serving as a bridge between academia, past experience and
the business environment, from the representation of reality (specic situations in the
business area), by means of simulation techniques (portraying laboratory conditions of a
given reality, not just a simulation of the company, but the market) and through experience
with game participants (bringing interactivity and teamwork) in decision-making processes
(Lacruz, 2004). In other words, in business games business environments are simulated in
which several groups manage dierent virtual companies competing in the same industry,
allowing participants to learn from their own experience.
There are many studies on business games and from dierent perspectives. Faria (2001),
based on articles published in the Association for Business Simulation and Experiential
Learning between 1975 and 2001, identied that research on business game are focused
on the factors that lead to good performance in business games; on the eectiveness and
eciency of business games; on the skills that can be learned through the adoption of
business games; and on the study of how this learning occurs.
Several studies have supported the experiential learning cycle proposed by Kolb
(1984) as support for the use of business games as a teaching-learning tool (e.g. Ben-Zvi
&Carton, 2008, Crookall &Thornagate, 2009, Meij et al., 2013, Dias et al, 2013, Araújo
et al., 2015). In Kolb’s (1984, p.38) words, “Learning is the process whereby knowledge
is created through the transformation of experience”. At the core of this conceptualization
is the tension between dialectical dimensions (concrete/abstract and active/reective)
which is solved by mental operations of experience prehension and its transformation, by
considering learning as a spiral quadric cycle in which people learn through experience,
that support the translation of experiences into concepts, allowing their application in new
experiences: concrete experience, abstract conceptualization, reexive observation and
active experimentation (Figure 1).
Kolb (1984) explains that in the process of holding people grasp (apprehension) and seize
(understanding) the experience through concrete experience and abstract conceptualization.
- concrete experience: refers to the experiences that occurred during simulation that
lead to the immediate knowledge (apprehension) for the search of solutions to the
dilemmas proposed in the experience.
- abstract conceptualization: characterized by the formation of concepts derived from
the analysis of life experiences (comprehension), from the organization of knowledge
obtained and/or rescued through experience to form a generalizable conceptual
framework.

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Source: Adapted from Kolb (1984, 42).
Figure 1. Experiential Learning Cycle.
And that the process of transformation leads to the creation of meaning for living,
through reective observation and active experimentation.
- reective observation: in regards to the personal examination, and in the context of
ideas, life experiences (faced dilemmas, possibilities of choices, performed tasks,
results obtained etc.), in order to transform the knowledge resulting from prehension.
- active experimentation: it deals with the connections with what is real, in an external
movement, from analogies and comparisons with the aspects of the experience
projected in other situations, in order to bring meaning to what has already been
understood.
In short, in the experiential learning cycle, apprehension and transformation are combined
by the comprehension and transformation of experience, in which people exercise the role
of actor (action) and observer (reection).
In this connection, Crookall and Thorngate (2009) advocate that the simulation is a means
capable of linking tacit knowledge to explicit and harmonizing action and knowledge, in a
cycle in which action (experience) leads to knowledge (conceptualization) and knowledge
enables and perfects action, according to experiential learning. Ben-Zvi and Carton (2008)
evaluated the approximation between business games and experiential learning. For the
authors, participation in business games would promote learning, in line with the theoretical
lens of experiential learning, provided that certain important operational parameters
are assured, such as prior guidance, debrieng and the adoption of a passive role by the
teacher. The process would have the following dynamics: initially the professor’s prior

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guidance (game moderator) teaches the terminology. Then, the students progress through
integrating knowledge from several disciplines and the activities of the game promote their
internalization. As students need to engage in decision-making without greater support
from the teacher, they are forced to rely on self-knowledge. They have to analyze various
situations and evaluate the outcome of their decisions based on their knowledge. Finally,
at a more abstract level, the dynamics lead to self-questioning by students on how and why
they made such decisions, allowing them to identify their weaknesses and strengths and
thus to be equipped with metacognitive knowledge.
In business games, the experiential learning cycle begins with concrete experience,
which unfolds in eects with which the participants make contact in the simulation that
lead to apprehension of the conditions of the immediate experience. Then, from reection
on the example arising from immediate experience, it is possible to examine and select
actions that can be taken in similar circumstances by projecting plausible outcomes of these
actions, which leads to comprehension and general understanding of the life experience of
a generalized nature, in which explanatory hypotheses emerge not only for the particular
example of that experience. Finally, when the general principle is understood, learning
outcomes can be tested, with active experimentation, within the possibilities oered by
generalization, from which the learning cycle is continuously renewed. Dias et al.(2013)
argue that in this process there is a risk that participants will not close the learning cycle
due to lack of reective activities; in view of the above, they suggest the adoption of steps
that stimulate the analysis of the results of the game rounds so that reective observations
are made that contribute to the closing of the experiential learning cycle.
Many studies have shown that participants in business games point to them as being
the method that provides learning with greater involvement and participation (e.g. Peach
& Hornyak, 2003) and that contributed greatly to learning in management training (e.g.
Sauaia, 1995, Lacruz & Villela, 2006, Dias et al., 2013, Fitó-Bertran et al.2015). From
this we assume that participation in business games contributes to learning in terms of
management training.
And in much of the research the quantum of learning resulting from participation in
business games was measured by the participants’ self-declaration, in accordance with the
suggestion by Gentry (1990) that, from the perspective of the experiential learning theory,
the evaluation of learning is done by the participants themselves, as an integrated part of
the learning process; from which it is assumed that the quantum of learning resulting from
participation in business games can be measured by the participants’ self-declaration.
It should be noted that, despite agreeing with such assumptions, the complexity involved
in dening and measuring learning is not ignored – which in business games has been
dened in most studies based on Bloom’s et al. (1956) taxonomy and the experiential
learning cycle by Kolb (1984) – and measured by participants’ self-declaration. On the
other hand, there are sucient numbers of studies that allow arguing that business games
are a valid method to teach management.
We also add that we acknowledge the existence of a wide set of variables that can aect
the participants’ perception regarding the simulation, their performance and their learning,
some of which have been empirically tested: as gender (e.g. Florea et al., 2003, Apesteguia,
Azmat & Iriberri, 2012), cognitive style (e.g. Peters & Vissers, 2004), previous academic
performance (e.g. Gosen & Washbush, 1999, Sauaia, 2006), complexity of the simulator
(e.g. Teach & Mur, 2008, Hall &Cox, 1994). However, for other variables, we did not
identify empirical studies that veried its inuence on the perception of participants in

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business games: related to the subject-participant, as prior contact with another business
game; and the dynamics of the exercise, such as the duration of the game, the method to
evaluate participants’ performance, and the debrieng stage.
There are authors who advocate debrieng as a critical stage in business games in
relation to participants’ learning (e.g. Gentry, 1990, Peters & Vissers, 2004, Ben-Zvi &
Carton, 2008, Kriz, 2010, Meij et al., 2013). Tannenbaum and Cerasoli (2013) conducted
a meta-analysis research, considering its application in several areas (medical, educational,
psychological, military, organizational etc.), to examine the empirical support for the
eectiveness claimed for debrieng. The search in the literature resulted a total of 31
studies (with 29 being published and 2 unpublished), with 46 samples (n = 2,136), the
majority of whom were involved in comparisons between the same group and a sample
physicians (61%). Their analysis showed that debrieng produces a signicant advantage
over conditions without debrieng. An average improvement of approximately 25% (d
= 0.67) in the learning outcomes was found. However, since most of the data came from
quasi-experimental designs, causal inferences must be elaborated carefully. We emphasize
that we did not identify in this study evaluation involving business games.
It should be noted that there are several ways to promote debrieng: expert-led or self-
debrieng; oral or written; individual or collaborative; after the completion of the game
or at the end of each round; either guided or not by the facilitator; with or without the
participation of external observers as an additional feedback element (Kriz, 2010, Meij
et al., 2013,Tannenbaum & Cerasoli, 2013). The abundant diversity of debrieng studies
reveals that there may be subtle but relevant, dierences in how debrieng is dened.
In this article, in harmony with most of the business game applications, and based on
the description by Fanning and Gaba (2007), the debrieng set-up is characterized as a
facilitated or guided reection in the experiential learning cycle, structured around a set of
questions that invites participants to reect on their experience in business games, in order
to involve them in an analytical process that revolves around the review and analysis of
the events that occurred during the business game; which can be characterized as an oral,
collaborative self-debrieng, guided by the moderator, carried out at the end of each round
of the business game and without the participation of external observers.
In spite of numerous studies that evidenced the contributions of business games to the
learning of their participants, however, the inuence of debrieng on this process is unclear.
Can we expect asymmetry in relation to the learning dimensions, or in relation to the stages
of the experiential learning cycle, when games with and without debrieng are adopted?
As a result, there is a need for more research to identify the real benets of debrieng in
business games, in terms of student learning development. The incipient empirical evidence
regarding the inuence of debrieng on business games motivated this research.
So, considering the motivation for this study and that participation in business games
contributes to learning in terms of management training of their participants, and the quantum
of learning resulting from participation in business games can be measured by participants’
self-declaration, the research problem can be summarized by means of a question: Does the
debrieng stage in business games applied to undergraduates in Business Administration
inuence the learning of their participants?
Due to the research problem, and the ndings of other debrieng studies, we propose the
following guiding hypothesis: - the quantum of perceived learning as coming from the stake
in business game with debrieng is greater than that of business games without debrieng.

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
We use in this descriptive study, characterized by the quantitative approach, a cross-
sectional study to investigate the inuence of debrieng on the learning perception of
participants in business games and can be characterized as a quasi-experiment.
For Campbell and Stanley (1979), experiment is a type of research in which a variable
(independent) is manipulated by the researcher and its eects on another (dependent)
variable are observed, with all other factors constant. This research can be classied as a
quasi-experiment, with two groups, one that was exposed to treatment (debrieng stage)
and another control group (which was not exposed to treatment), whereby both measures
were performed only after treatment. We clarify that the pairing of the test units was
conducted in order to guarantee greater similarity between the groups in relation to age and
gender, for we acknowledge that these variables can aect the participants’ perception of
their learning. Figure 2 illustrates the research project from Campbell and Stanley’s (1979)
classic notation system.
Note: Exposure to an event is represented by “X” and the record of
measurement by “O”. e continuous line represents the temporal order.
Source: Authors own elaboration
Figure 2. Research Project.

In order to select the business game, we excluded non-computerized business games,
assuming that the complexity and interactivity of these types of business games would not
satisfy those sought in the study; non-interactive, i.e., those which the decisions of each
team did not inuence or were inuenced by the others; applied at a distance, without the
direct assistance of the teacher, who would establish limitations to debrieng (as dened
in this study); functional, i.e., that they focused only on one area of the company; who did
not have a manual; and where the investment necessary for its acquisition or use were an
impediment.
We selected the GI-MICRO business game (version 6 demo - limited to four rounds
processing) because it is a game of medium complexity, and has been used in several studies
(e.g. Mecheln, 2003, Lacruz & Vilella, 2006, Gerber, 2006, Souza &Cardoso, 2012).

the support on which this study is developed is the teaching-learning process in the
Administration area, more specically under the theoretical perspective of the experiential
learning theory. In similar research with business games as a teaching-learning instrument
in Business Administration courses, and under the same theoretical approach, we used
questionnaires of data collection instruments that sought to identify the main dimensions
present in business games and learning levels of participants (e.g. Sauaia, 1995, Peach
&Hornyak, 2003). From these references, and the experience with the application of
business games, we developed the data collection instrument that comprised aspects as
seen in Table 1.

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Table 1. Operationalization of Variables
Variable eoretical background
Control
Age range vDem_1 Ordinal -
Gender vDem_2 Nominal
Florea et al. (2003).
Apesteguia. Azmat and
Iriberri (2012)
Learning
Knowledge
Acquiring new knowledge vOp_1
Ordinal
Sauaia (1995). Lacruz
and Villela (2006).
Dias et. al. (2013).
Fitó-Bertran et al.
(2015)
Integrating knowledge from various areas of
business administration vOp_2
Updating already existing knowledge vOp_3
Skills
Identifying problems. Evaluating alternatives.
Formulating and implementing solutions and
evaluating their results
vOp_4
Developing a systemic view (holistic) vOp_5
Attitudes
Adapting to new situations (exibility) vOp_6
Encouraging teamwork vOp_7
Developing/Improving leadership vOp_8
Resolving conicts vOp_9
Source: Authors own elaboration.
The learning perception was measured using a Likert scale, adopting it with intervals,
under the premise that respondents will treat the dierences between adjacent categories as
equals and their adequacy for self-perception measurement (Malhotra, 2006).

By using the experiential learning cycle (Kolb, 1984), we designed a semi-structured
debrieng script based on a model proposed by Sims (2002), which is guided by four
stages: the rst phase (concrete experience) involves questions that ask participants to
describe their perceptions and feelings during business games. In the second phase (reexive
observation), participants are invited to consider these experiences from dierent points of
view (e.g., in relation to values and cultures). Subsequently, in the third phase (abstract
conceptualization), the participants are encouraged to reect on concepts and models. And
nally, in the last phase (active experimentation), participants are asked to come up with
some guidelines that can be considered in future actions. For each topic, we formulated
guiding debrieng questions so that participants could reconstruct their experiences,
valuing their own perspectives.

The GI-MICRO business game was applied to undergraduates of the 8th term of the
Business Administration course of two private HEIs in Minas Gerais (Brazil). We emphasize
that the test units were matched so that the groups’ proles were similar in relation to age
and gender. Moreover, that after the pairing we randomly selected the test units, using the
SPSS software.
We collected the data through a structured self-completion questionnaire using the
Survey Monkey online platform. We applied the questionnaire at the end of the business
game, with the presence and supervision of the game’s moderator. All 112 respondents
answered the questionnaire online. After the analysis of missing data, the nal sample
consisted of 108 cases (96% of the total), with 55 from the game with debrieng and 53
from the game without debrieng (Table 2).

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We clarify that a pre-test of the questionnaire was performed, through a protocol
analysis, in which the respondent “thinks out loud” (Malhotra, 2006), in order to identify
misunderstandings in the data collection instrument more clearly. Eight students participated
in the pre-test (divided into 2 groups of 4 students) of one of the HEI composing the sample
after having participated in 4 rounds of the same set of business game. We elucidate that
these participants were exclusively involved in the pre-test. The research universe for the
pre-test was constituted by a sample that consisted of 7% of the predicted population (112).
We reinforce that the groups’ prole in relation to gender and age was similar (which
was guaranteed by the pairing process), as seen in Table 3.

The GI-MICRO business game was applied in two dierent ways in each of the HEIs:
with and without debrieng. Both applications were conducted by the same moderator,
to dierent groups of students, and circumscribed 4 rounds of the business game in the
second half of 2015. 112 students participated in the business game (64 from HEI_1 and 48
from HEI_2), equally distributed in the business game with and without debrieng. In both
cases, only students who stated that they did not have previous experience with business
games participated and were organized in groups composed of 4 students (as indicated
in the GI-MICRO manual, in order for each student to take up position in the board of
directors: general, marketing, nancial and production).
We chose to use the same set of business game, with the same duration, for students with
no previous experience with business games, of the last term of the Business Administration
course, in the same HEI (experimental group x control group), with similar proles in
relation to gender and age, and with the same moderator, to reduce inuences of extraneous
variables that could interfere in the results.
One of the authors of this study was the moderator of all the games (pre-test, business
game with debrieng and business game without debrieng), assuring uniformity and
consistency both in the preparation and in the implementation of the business game and also
in the procedures for collecting data. We also assured the use of the operational parameters
in all business games, as indicated by Ben-Zvi and Carton (2008) as important for the
approximation between business games and the experiential learning cycle on providing
learning of their participants: prior guidance, debrieng (only for the experimental group)
and adoption of a passive role by the moderator.
The moderator initially made the presentation of the GI-MICRO business game,
emphasizing the rules and scenario of the simulation, as well as the dynamics of the activity.
He claried that participants received the director’s manual in advance. Then each group
Table 2. Sample Description
Groups Simulated
Companies Participants Respondents Valid
Questionnaires Response rate
Experimental (with debrieng) 14 56 56 55 98%
Control (without debrieng) 14 56 56 53 95%
Total 28 112 112 108 96%
Source: Authors own elaboration.
Table 3. Distribution of Groups by Age and Gender.
Groups Size Age Gender
Mean Standard Deviation Women Men
Experimental (exposed to debrieng) 55 24.62 3.19 64% 36%
Control (not exposed to debrieng) 53 22.89 1.93 68% 34%
Source: Authors own elaboration.

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prepared the planning for their simulated company, and the decision rounds were started.
In each of the four rounds, after decisions are processed by the business game software,
the groups received feedback on the results of the decisions through reports and market
information by the newspaper and a partial ranking. With the fourth round concluded,
we dened the nal ranking, with the accumulated prot as criterion. When applying the
business game to the experimental group, debrieng was conducted at the end of each
round. At the end, the questionnaire was applied to the participants.

We used the Cronbach’s alpha coecient to estimate the reliability of the scale used in
the applied questionnaire. And to verify if the data of each item could come from a variable
with normal distribution we applied Shapiro-Wilk test.
We describe the opinion variables in terms of mean, standard deviation, minimum and
maximum. We used Spearman’s correlation coecient to evaluate the strength of the
relationship between opinion variables and control variables (age and gender), in order to
verify if age and gender could inuence in a relevant way the perception of learning, even
though the groups were composed in a very similar way (Table 3).
Through the Mann-Whitney test we veried whether the quantum of learning perceived
by the members of the experimental group was higher than that of the members of the
control group; and by Cohen’s d, Cohen’s and CL (common language eect size statistic),
the eect size. We assumed the level of signicance of 0.05 and we used the SPSS software
(Cronbach’s alpha, Shapiro-Wilk test, Spearman correlation coecient and Mann-Whitney
U test) and GPower 3.1 (statistical power of Cohen’s d test). We calculated Cohen’s and
CL indices manually.
In order to clarify the problem of the research, a schematic drawing of the study is shown,
which summarizes the relationships analyzed in this study: (i) we assume that business
games contribute to participants’ learning, (ii) the moderating role of the debrieng step in
this relationship is evaluated, and (iii) the inuence of age and gender (control variables) of
participants in their learning (Figure 3).
Source: Authors own elaboration.
Figure 3. Conceptual Structure of the Study.

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
Prior to initiating the measurement extraction procedures, we estimated the reliability of
the scale used in the questionnaire using Cronbach’s alpha coecient. The result obtained
for both samples (experimental group = 0.81 and control group = 0.65) indicates that the
scale used to measure participants’ perception was considered adequate, because it is above
the threshold (> 0.6) from which the value is considered appropriate for non-causal studies
(Hair et al. 2009). Then, the variables of opinion were characterized (Table 4).
Both the group exposed to debrieng and the non-exposed pointed to participation
in the business game with a strong contribution to learning (lowest mean = 3.92) and
homogeneously (higher standard deviation = 0.98). We observed that the mean of the
experimental group in all variables was higher than the mean of the control group, in
line with literature that debrieng contributes to learning. Also, with the exception of
the variables Adapting to new situations (vOp_6) and Resolving Conicts (vOp_9), the
perception of the members of the experimental group is more uniform (lower standard
deviations); insinuating that debrieng contributes so that learning in business games also
occurs in a more homogeneous manner among the participants.
The highest mean of perceived learning by the group exposed to the debrieng in relation
to the non-exposed one (Table 4) is in line with the ndings of other debrieng studies –
although not as an element of the formative cycle with business games – taking into account
the recent meta-analysis by Tannenbaum and Cerasoli (2013). In the course of business
games, participants need to make use of a variety of generic and specic management
skills, and debrieng seems to contribute triggering this process by promoting a reection
of the results in view of the actions taken. It is possible that the experience with business
games will unfold without the activity of evaluating decisions and results actually taking
place and with debrieng the reection begins to compose the cycle of formation of the
participants.
Then, we veried by the Shapiro-Wilk test that the null hypothesis (which assumes that
the sample was extracted from a normally distributed population) could be refuted (p-value
0.000) in all nine items, so that it should not be assumed that there is normality in the data
source variable.
Then, we veried the association between control variables (age and gender) and
opinion. By the Spearman’s ρ correlation coecients, it was evidenced that the few
statistically signicant correlations are classied as weak (0.2 < ρ < 0.4), and from this we
can assume that the statistically signicant dierences between the conditions of age and
gender between the groups (experimental and control) did not have a relevant inuence on
the participants’ perception of learning.
Table 4. Descriptive Statistics of Opinion Variables.
Variable
Experimental group Control group
Mean Standard
Deviation Minimum Maximum Mean Standard
Deviation Minimum Maximum
vOp_1 4.56 5.00 0.69 3.00 5.00 4.34 4.00 0.73
vOp_2 4.53 5.00 0.63 3.00 5.00 4.25 4.00 0.85
vOp_3 4.49 5.00 0.69 3.00 5.00 4.17 4.00 0.85
vOp_4 4.62 5.00 0.56 3.00 5.00 4.21 4.00 0.79
vOp_5 4.49 5.00 0.54 3.00 5.00 4.08 4.00 0.70
vOp_6 4.47 5.00 0.72 3.00 5.00 4.30 4.00 0.70
vOp_7 4.45 5.00 0.69 3.00 5.00 4.42 5.00 0.84
vOp_8 4.27 4.00 0.76 2.00 5.00 3.92 4.00 0.98
vOp_9 4.45 5.00 0.81 3.00 5.00 4.15 4.00 0.69
Source: Authors own elaboration.

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Lastly, we processed the non-parametric Mann-Whitney U test to test the general
hypothesis of this study. Table 5 summarizes Mann-Whitney U-tests for independent
samples, along with the eect size (Cohen’s d, Cohen’s and CL) and the statistical power
of the test.
The results refute the hypothesis of equality (p-value< 0.05) perceived learning between
groups from 7 to 9 variables (vOp_1-5 and vOp_8-9). Except for the variable vOp_1, the
statistical power of the test was higher than the threshold (1 - β > 0.5) from which value
is considered appropriate in social science (Hill & Hill, 2000, Murphy & Myors, 1988).
In relation to the variable vOp_1, given the level of signicance adopted in the study (α
= 0.05), the low power of statistics is related to the sample size and the eect size. Eect
size was determined by Cohen’s d (since the size of the two groups is similar and the
standard deviations are similar), and may be considered small for the variables vOp_1-3
and vOp_8-9, according to the classication criterion proposed by Cohen (1998) for testing
the dierence between means of independent groups. As a result, the results in relation to
acquiring new knowledge (vOp_1) show that although there is evidence to reject the null
hypothesis that there is no dierence in the quantum of perceived learning by participants
in business games with and without debrieng, the probability of correctly rejecting the
null hypothesis when the alternative hypothesis is true (1 - β) is low, which makes the
results inconclusive (Cohen, 1988). On the other hand, this result allows estimating the
sample size needed for other studies to obtain statistical power from the appropriate test
given a small eect size. Considered d = 0.30, 0.35 and 0.40, the minimum sample size
would be, respectively, 290, 214 and 164 observations, and this evidences the sensitivity of
sample size in face of variations in eect size.
Table 5. Summary of Results.
Variable Description
Mann-
Whitney’s
U test
p-valuea
Eect size Test
power Decision
Cohen’s d Cohen’s
U3
CLb
vOp_l Acquiring new knowledge 1182.0 0.026 0.31 Small 62.4 58.7 0.47 Inconclusive
vOp_2
Integrating knowledge from
various areas of business
administration
1212.5 0.046 0.37 Small 65.0 60.5 0.60 H0 Rejected
vOp_3 Updating already existing
knowledge 1154.0 0.021 0.41 Small 66.5 61.6 0.67 H0 Rejected
vOp_4
Identifying problems.
Evaluating alternatives.
Formulating and
implementing solutions and
evaluating their results
1043.5 0.002 0.60 Medium 74.0 66.8 0.92 H0 Rejected
vOp_5 Developing a systemic view
(holistic) 998.5 0.001 0.66 Medium 76.2 68.4 0.95 H0 Rejected
vOp_6 Adapting to new situations
(exibility) 1243.5 0.080 0.24 Small 59.6 56.7 0.33 H0 Not rejected
vOp_7 Encouraging teamwork 1438.0 0.457 0.04 Insignicant 51.6 51.0 0.07 H0 Not rejected
vOp_8 Developing/Improving
leadership 1171.5 0.030 0.40 Small 66.0 61.2 0.64 H0 Rejected
vOp_9 Resolving conicts 1038.5 0.006 0.40 Small 65.9 61.2 0.64 H0 Rejected
Note: Experimental Group (n = 55), control group (n = 53) and α = 0.05.
a Corrected for ties (one-tailed)
b Common language eect size statistic
Source: Authors own elaboration.

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It should also be noted that for the variables Op_4 and vOp_5 we accepted the alternative
hypothesis that the quantum of perceived learning by the participants of business games
with debrieng (experimental group) is superior to that of those who participated in games
without debrieng (control group) and that the eect size was considered medium (0.49 <
d < 0.8 = medium). Regarding the eect size, caution should be exercised in interpreting
the classication. We adopted the Cohen’s (1998) classication, because particularly new
results are explored and could not be compared with other ndings in the literature, except to
a limited extent, with the studies by Tannenbaum and Cerasoli (2013), whose meta-analysis
returned a d = 0.67, and Lipsey et al. (2012), for which intervention studies in education
rarely have an eect size above 0.3. In this respect, by interpreting the eects in the light of
the research area, the average ecacy of the studies analyzed by Tannenbaum and Cerasoli
(2013) was similar to that obtained in this study regarding variables vOp_4 (d = 0.60) and
vOp_5 (d = 0.66), which in turn had eects above the threshold proposed by Lipsey et al.
(2012) for educational studies. However, the comparison is limited by dierent contexts. In
view of this, we need to ask: what are the practical meanings of these results?
It should be noted that in relation to the contribution of business games to the development
of systemic view (vOp_5), which was the variable with the largest eect size (d = 0.66),
76% of participants in business games with debrieng perceived this aspect in a superior
way to the participants in business games without debrieng. That is, the average of the
participants exposed to the debrieng position is in the 76th percentile of the group not
exposed to debrieng (Cohen’s ). Or, from another perspective, in relation to this dimension,
the probability of participants in business games with debrieng perceiving learning in
a superior way than the participants in business games without debrieng is of 69%, as
shown by the CL. Equally relevant was the result in relation to the variable Practicing
decision making (vOp_4), with d = 0.60, Cohen’s = 74 and CL = 66.8. In the business game
dynamics, the participants nd themselves as problem situations that require capacity for
interpretation and critical analysis, which involve concepts related to various disciplines
and links with the areas of the company and its social environment, which contributes to
the development of a holistic vision, as solutions require the simultaneous application of
concepts and tools from various areas in the process of problem identifying, evaluating
alternatives, formulating and implementing solutions and evaluating their results. It can be
proposed that debrieng will contribute to participants’ understanding of the connections
between dierent contents and functional areas, reinforcing the systemic and complex
nature of the simulated activity, because promoting ex post reection contributes to the
need to simultaneously apply various concepts and tools, either by their self-reection,
or by the sharing of reections of other participants. In addition, in debrieng there is the
opportunity to promote self-criticism on the extent to which it was able to instrumentalize
knowledge that was available or that were acquired during the simulation in the situations
experienced.
In analyzing only from the point of view of the size of the eect, considering the lowest
result (d = 0.31) between the variables with p < 0.05 (vOp_1), 62% of participants in
business games with debrieng found that they acquired new knowledge in the simulated
activity in a way superior to the participants in business games without debrieng (Cohen’s
); and the probability of participants in business games with debrieng perceiving learning
in a superior way than the participants in business games without debrieng was of 59%
(CL). Therefore, even in considering the smallest size of the eect, it seems to us that the
cost of including debrieng in business games (more time in the preparation and execution
of the activity) is of little relevance in the face of potential benets for participants’ learning.
In this study the average improvement of debrieng in learning perception was 18% (Cohen
medium = 68).

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It is important to emphasize, in analyzing only in relation to eect size, that in relation to
the variable Adapting to new situations (vOp_6), the average improvement in the perception
of learning in relation to this dimension was 10% (Cohen = 59.6). We recognize, therefore,
that even if the dierence was not statistically signicant and the power of statistics was
small (at the level of the adopted statistical signicance), debrieng contributed in a relevant
way in the perception of learning in relation to this factor, with the cost-benet being
evaluated. The same cannot be assumed, however, in relation to the variable Encouraging
teamwork (vOp_7), whose eect size was insignicant (d = 0.04). That is, business games
contribute to stimulating teamwork (mean = 4.45 [experimental] and 4.42 [control]), but
debrieng does not inuence signicantly statistically speaking, nor in any relevant way,
in this process. This, perhaps, due to the way debrieng was operationalized, in which the
participants discussed their personal impressions about the simulation.
And, nally, there is evidence that debrieng reinforces elements characteristic of
business games, especially those related to the abilities of the participants to apply in
concrete-hypothetical cases knowledge that they already had or that were acquired or
updated in the simulation. On the other hand, in relation to eective teamwork among group
participants, the insights of a personal nature regarding the way the group interacted and the
posture of how to be a better listener and member of a group (vOp_7) were not inuenced
by debrieng, whereas the posture as a mentor and seller of ideas (vOp_8) seems to have
been inuenced, since the eect size was relevant d = 0.40, Cohen’s = 66 and CL = 61.2.
In summary, we suggest that participants in business games may not reect during the
simulation about the challenges experienced, the decisions taken and the eects arising from
their action in an in-depth manner, often due to the pressure on the time limits established
for the delivery of decisions, to the involvement with the character of competition between
the teams, so that the debrieng marks the moment for reection on the actions taken
and feelings experienced, contributing to the achievement of insights and generalizations
resulting from the simulation.

The objective of this study was to verify the moderating role of debrieng in the
learning of participants in business games, using as lens the experiential learning theory.
The proposed analytical framework suggests that debrieng reinforces elements present
in business games, since the participants promote ex-reections in the decision-making
process, monitor the implementation of the proposed solutions ex cursum and debrieng
reinforces the evaluation of ex post results, contributing to the formation of a virtuous
learning cycle. The reexive observation and abstract conceptualization stages are planned
in the perspective of experiential learning, which in relation to business games can be
reinforced by debrieng activities after the rounds of the simulation, in order to potentiate
continuous processes of action and reection of the participants, depending on the spiral
experiential learning cycle.
In business games we have on one side the desirable creativity of thinking and on
the other the need of doing, in complementary relations, according to other studies that
highlight business games as a tool that favors the learning of doing. We propose, from the
ndings of the study, that the debrieng implies reections that lead to learning to learn, at
the abstract level of the experiential learning cycle, in which the dynamics of the debrieng
contributes to the participants’ questioning on why and how they made the decisions, as
well as the reasons for the results, allowing them to identify fragilities and forces in a kind
of “autophagy” of the processes that allows them to go through the experiential learning
cycle.

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Thus, the results bring two important advances to the area. First, although many studies
suggest relationships between debrieng and learning (e.g. Gentry, 1990, Peters & Vissers,
2004, Ben-Zvi & Carton, 2008, Kriz, 2010, Meij et al., 2013), the evaluation of possible
inuences in conditions with and without debrieng constituted a research gap. This article
analyzes the inuences considering dierent dimensions of learning in conditions with
and without debrieng, advancing the discussions of the eect of debrieng on learning
in business games, revealing the inuence of debrieng on the Reective observation and
abstract Conceptualization stages of Kolb’s (1984) experiential learning cycle. Second,
the results being presented with eect size and statistical power allow other studies to
compare the average eectiveness of the model developed in this study in the light of their
area of research, conferring practical signicance to the eect size. This is particularly
unusual in studies on business games in Brazil, in which even in the experimental studies
the size of the eect and the power of statistics is not presented or the power of statistics
is presented from an arbitrary average eect size. This compromises the interpretation of
results because one does not know the probability of correctly rejecting the null hypothesis
when the alternative hypothesis is true.
However, this study, like most, has limitations. Whereas the reliability of the scale used
seems to be acceptable for non-causal studies (Cronbach’s alpha of > 0.6), its validity must
be determined. In addition, comparisons were made of groups of students assumed to be
similar, but which may not present similarities in terms of previous training, experiência
prossional, cognitive styles and cultural traits (aspects that were not considered as control
variables in this study).
Another limitation relates to the way of measuring participants learning in the business
game by self-declaration. We acknowledge its limitation as a tool for measuring learning,
because the perception of learning may be associated with the emotional dimension that the
game triggers by placing participants as active and central elements of the learning process,
causing a “good feeling” of what a halo eect may elicit in terms of measuring perceived
learning (Gentry et al., 1998). On the other hand, ndings from attribution theory suggest
that perceptions of behavior may result in actual behaviors (Kelly, 1971, Martinko, 1995).
Finally, the results apply to the observations of students from two higher education
institutions and only one set of business game in particular, as in other studies (e.g. Dias,
Sauaia & Yoshizaki, 2013, Meij et al., 2013, Mayer et al., 2011), of which we can not
refute that their results are dependent on that particular game, there is no possibility of
generalization for business games. On the other hand, the results suggest relationships that
can be used in future studies.
Thus, to reach a wider range of conclusions, we suggest replicating this research in order
to compare the results, both in relation to the hypotheses and the eect size. Investigations
could also be conducted to explore the implications of debrieng on dierent educational
arrangements, such as distance learning, and levels of education, MBA for example. In
addition, researchers could examine the dierences between participants with dierent
learning styles, for example, from the inventory of learning styles of Kolb (2011), elaborated
on the experiential learning theory by Kolb (1984), and in business games that promoted
debrieng of dierent forms, like guided and not guided by the moderator. Finally, we
hope that this study will collaborate with future researches and the construction of lesson
plans with business games that take into account debrieng in the process of management
qualication.

Apesteguia, J., Azmat, G.,& Iriberri, N. (2012). The impact of gender composition on team performance and
decision-making: evidence from the eld. Management Science, 58(1), 78-93.

BBR
15,2
207
Araújo, U. P., Brito, M. J. de, Correia, L. F., Paiva, , F. D.,& Santos, A. de O. (2015).Simulação de negócios no
ensino da administração em centro de educação brasileiro. Revista Iberoamericana sobre calidad, ecacia
y cambio en educación, 13(2), 99-130
Ben-Zvi, T.,& Carton, T. C. (2008).Applying Bloom’s revised taxonomy in business games. Developments in
business simulation and experiential exercises, 35, 265-272.
Bloom, B. S., Engelhart, M. D., Frust, E. J., Hill, W. H.,& Krathwohl, D. R. (1956).Taxonomy of educational
objectives. New York: David McKay.
Campbell, D. T.,& Stanley, J. C. (1979).Delineamentos experimentais e quase experimentais de pesquisa. São
Paulo: EPU.
Cohen, J. A.(1998). Power primer. In: Kazdin, A. E. Methodological issues and strategies in clinical research.
Washington: APA.
Crookall, T.,& Thorngate, W. (2009). Acting, knowing, learning, simulating, gaming. Simulation & Gaming,
40(1), 8-26.
Dias, G. P. P., Sauaia, A. C. A.,& Yoshizaki, H. T. Y. (2013). Estilos de aprendizagem Felder-Silverman e o
aprendizado com jogos de empresas. Revista de administração de empresas,53(5), 469-484.
Dias, C. M. Jr, Moreira, B.,&Stosick, E. (2013). Um estudo sobre o desenvolvimento de competências em
ambiente simulado. Novas Tecnologias na Educação, 11(1), 10-23.
Fanning, R. M.,& Gaba, D. M. (2007). The role of debrieng in simulation-based learning. Simulation in
Healthcare, 2(2), 115-125.
Faria, A. J. (2001). The changing nature of business simulation/gaming research: a brief history. Simulation
& Gaming, 32(1), 97-110.
Fitó-Bertran, A., Hernández-Lara, A. B.,& Serradell-López, E. (2015). The eect of competences on learning
results and educational experience with a business simulator. Computers in human behavior, 51, 910-914.
Florea, N. B.,Boyer, M. A., Brown, S. W., Butler, M. J.,Hernandez, M., Weir, K., Meng, L., Johnson, P. R.,
Lima, C.,& Mayall, H. J. (2003). Negotiating from Mars to Venus: gender in simulated international
negotiations. Simulation & Gaming, 34(2), 226-248.
Gentry, J. W. (1990). What is experiential learning? In: Gentry, J. W. (Coord) Guide to business gaming and
experiential learning. London: Nichols.
Gentry, J.W., Commuri, S. R., Burns, A. C.,& Dickinson, J. R. (1998). The second component to experiential
learning: a look back at how ABSEL has handled the conceptual and operational denitions of learning.
Developments in business simulation and experiential exercises,25, 62-68.
Gerber, J. Z. (2006). Jogo de empresas e a formação de líderes empresariais(Tese de doutorado). Universidade
Federal de Santa Catarina, Florianópolis, SC, Brasil.
Gosen, J.,& Washbush, J. (1999). Perceptions of learning in TE simulations. Developments in business
simulation and experiential exercises, 26, 170-175.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E.,& Tatham, R. L. (2009). Análise multivariada de dados.
Porto Alegre: Bookman.
Hall, J.,& Cox, B. (1994). Complexity: it is really that simple. Developments in business simulations and
experiential exercises, 21, 30-34.
Hill, M. & Hill. (2000). A investigação por questionário. Lisboa: Sílabo.
Kelly, H. H. (1971). Attribution in social interaction. New Jersey: Learning Press.
Keys, J. B.,& Wolfe, J. (1990). The role of management games and simulations for education and research.
Journal of management, 16(2), 307-336.
Kolb, D. A. (1984). Experiential learning: experience as source of learning and development. New Jersey:
Prentice Hall.
Kolb, D. A. (2011). Kolb learning style inventory:version 4.0. Boston: Hay Resources Direct.
Kriz, W. C. (2010). A systemic-constructivist approach to the facilitation and debrieng os mulations and
games. Simulation & Gaming, 41(5), 663-680.
Lacruz, A. J. (2004). Jogos de empresas: considerações teóricas. Caderno de pesquisas em administração,
11(4), 93-109.
Lacruz, A. J.,& Vilella, L. E. (2006). Percepção dos participantes de jogos de empresas quanto às condições
facilitadoras para o aprendizado em programas de simulação empresarial: um estudo exploratório. Anais
do Seminários em Administração, São Paulo, SP, 9.
Lipsey, M. W., Puzzio, K., Yun, C., Hebert, M. A., Steinka-Fry, K., Cole, M. W., Roberts, M., Anthony, K. S.,&
Busick, M. D. (2012). Translating the statistical representation of the eects of education interventions
into more readily interpretable forms. Washington: IES.
Malhotra, N. K. (2006). Pesquisa de marketing. Porto Alegre: Bookman.

BBR
15,2
208
Mayer, B. W., Dale, K. M., Fraccastoro, K. A., & Moss, G. (2011). Improving transfer of learning: relationship
to methods of using business simulation. Simulation and Gaming, 42(1), 64-84.
Martinko, M. (1995). Attribution theory: an organizational perspective. Florida: St. Lucie Press.
Meij, H. van der, Leemkuil, H., & Li, J. (2013). Does individual or collaborative self-debrieng better enhance
learning from game?Computers in human behavior, 29(6), 2471-2479.
Mecheln, P. J. von (2003). Jogo de empresas, ambiente interativo e agentes computacionais mediadores (Tese
de doutorado). Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil.
Murphy, K., & Myors, B. (1998). Statistical power analysis: a simple and general model for traditional and
modern hypothesis tests. New Jersey: Erlbaum.
Peach, B. E.,& Hornyak, M. (2003). What are simulations for? Learning objectives as a simulation device.
Developments in business simulation and experiential learning, 30, 220-224.
Peters, V.,& Vissers, G. (2004). A simple classication model for debrieng simulation games. Simulation &
Gaming, 35(1), 70-84.
Sauaia, A. C. A. (1995). Satisfação e aprendizagem em jogos de empresas: contribuições para a educação
gerencial (Tese de doutorado). Universidade de São Paulo, São Paulo, SP, Brasil.
Sauaia, A. C. A. (2006). Conhecimento versus desempenho das organizações: um estudo empírico com jogos
de empresas. Revista eletrônica de administração, 12(1), 1-17.
Sims, R. R. (2002). Debrieng experiential learning exercises in ethics education. Teaching business ethics,
6(2), 179-197.
Souza, T. M. P. de & Cardoso, A. M. P. (2012). Diretrizes de interface para jogos de empresas. Revista de
informação, 13(6).
Tannenbaum, S. I.,& Cerasoli, C. P. (2013). Do team and individual debriefs enhance performance? A meta-
analysis. Human factors, 55(1), 231-245.
Teach, R.,& Mur, E. (2008). Are the business simulations we play too complex? Developments in business
simulation and experiential learning, 35, 205-211.