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Many researchers have studied the use of game-based learning. Game-based learning takes many forms, including virtual reality, role playing, and performing tasks. For students to learn specific course content, it is important that the selected game be suited to the course. Thus far, no studies have investigated the use of game-based cooperative learning in an operating systems course. For this study, an online game was developed to enable students to learn cooperatively. The findings indicate that students' desire to win the game motivates them to learn from online course materials before they play, which in turn can enable them to achieve better learning outcomes.
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Using Game-Based Cooperative Learning to Improve
Learning Motivation: A Study of Online Game Use
in an Operating Systems Course
Bin-Shyan Jong, Chien-Hung Lai, Yen-Teh Hsia, Tsong-Wuu Lin, and Cheng-Yu Lu
Abstract—Many researchers have studied the use of game-based
learning. Game-based learning takes many forms, including vir-
tual reality, role playing, and performing tasks. For students to
learn specic course content, it is important that the selected game
be suited to the course. Thus far, no studies have investigated the
use of game-based cooperative learning in an operating systems
course. For this study, an online game was developed to enable
students to learn cooperatively. The ndings indicate that stu-
dents’ desire to win the game motivates them to learn from online
course materials before they play, which in turn can enable them
to achieve better learning outcomes.
Index Terms—Cooperative learning, game-based learning, game
questionnaire, learning achievement, learning motivation.
TRADITIONAL classroom teaching tends to be didactic.
Therefore, when students do not nd course materials
interesting, they become less motivated to learn. In order to
resolve this problem, many instructors employ teaching aids
to augment the impact of the classroom period; game-based
learning is one such tool. When instructors integrate course
materials with the content of a game, and then allow students to
play the game in class, the students acquire important knowl-
edge through their gaming experience [1]–[3]. With advances
in computer and network technology, many courses can now
be held or supplemented online, and students can use their own
computers to access course content on the Web. This makes
it possible to use game-based learning in the development of
learning technology [2]–[4] such that students are no longer
conned to a classroom setting when learning. For example,
it is possible to stimulate students’ algorithmic thinking by
asking them to program simulations in a game; in this way,
they develop their ability to write efcient program code [5].
Some researchers also combine game-performing tasks with
Manuscript received February 24, 2012; revised May 10, 2012; accepted June
25, 2012. Date of publication July 18, 2012; date of current version May 01,
of Information and Computer Engineering, Chung Yuan Christian University,
Taoyuan, Taiwan (e-mail:;;;
T.-W. Lin is with the Department of Computer Science and In-
formation Management, Soochow University, Taipei, Taiwan (e-mail:
Color versions of one or more of the gures in this paper are available online
Digital Object Identier 10.1109/TE.2012.2207959
course content; by performing such tasks in a game setting,
students acquire course-related knowledge step by step [2].
The work reported in this paper is based on such research.
This study experiments with the use of games as a teaching
aid in an Operating Systems course taught to juniors in the
Department of Information and Computer Engineering, Chung
Yuan Christian University, Taiwan. The purpose of the study
is to improve student motivation, thereby helping students to
achieve better learning outcomes.
The various units of the Operating Systems course are the
following: computer system architecture, operating system ar-
chitecture, processing unit, synchronization, CPU scheduling,
deadlock, memory management, and le system management.
Students in the course must also complete several course-related
projects. Most nd it difcult to master the course; in addition to
memorizing essential course materials, they must tackle difcult
concepts in computer system architecture, operating system ar-
chitecture, memory management, and le system management.
They also need to understand topics such as processing units,
synchronization, and deadlock. Perhaps their most difcult task
is to complete the course projects [6], which are related to CPU
scheduling, memory management, and processing units. As a
result of all these factors, students can become frustrated in
their learning and often lose motivation as the course proceeds,
causing many to give up the course. Therefore, in this study,
an online learning game was developed and integrated with the
Operating Systems course contents. Students’ desire to win the
game motivates them to study course-related materials before
playing. When they win rounds of the game, they become even
more motivated and, as a result, they achieve better learning
A. Game-Based Learning
In game-based learning, course content is presented to
learners while they are engaged in game playing. The primary
goal of this approach is to improve learner motivation [4].
tself is not the main focus of the course; its use is
only part of the teaching strategy. For example, educational
games can be integrated with cooperative learning [7]. When
students are shown an abundance of colorful screen designs
coupled with sound effects and instructional materials, they
are motivated to learn, and they learn better. Researchers
have applied game-based learning in a variety of educational
settings [2], [8], [9]. For example, “Re-Mission” is used to help
0018-9359/$31.00 © 2012 IEEE
patients understand cancers in medical therapy [10], the “Chief
Knowledge Ofcer (CKO)” is used to teach students about
knowledge management [11], and “River City” is used to teach
environmental science [12].
Several characteristics of game-based learning have been
identied [13].
By participating in games, students are motivated to re-
view the knowledge they have just acquired.
— The instant feedback provided by the gaming environment
allows instructors to see the progress of individual students
and give suitable suggestions in a timely manner.
— Through game playing, students can exchange knowledge
with one another.
— Game playing enables students to learn in an informal way,
so that they do not feel bored.
Game playing is often accompanied by discussions and
social activities.
B. Cooperative Learning
Cooperative learning emphasizes mutual dependency and
cooperation; in performing each learning task, group members
work together to achieve the same learning goal. There are
different notions of cooperative learning; cooperative learning
groups were have been formed in various ways. Despite this,
the general consensus is one of group discussion, member
interaction, and peer assistance [14]. Compared to individual
learning and competitive learning, cooperative learning is
better in raising the level of learning achievement for students;
it also helps to improve both the learning motivation and the co-
operation skills of students [15]. In addition, group discussion
stimulates deep thinking [16]. To make cooperative learning
more effective, there are important elements to consider [17].
To start with, students should realize the importance of co-
operatively achieving the learning goals. Second, assessment
should include how students divide their tasks, share resources,
take responsibilities, and work together. Third, students should
engage in discussion with, and provide assistance to, each
other. By fullling their roles, they gain a sense of responsi-
bility. Finally, the instructor should always provide appropriate
assistance when needed.
C. Game-Based Learning by Digital Design
Motivation is crucial for learning. When learners have low
motivation, they may not learn at all despite participating in
learning activities. Researchers can add the element of game
playing to a course to increase learners’ motivation and attract
their attention, thereby helping them focus [18]. It is not easy
to design a game that is both integrated with existing course
contents and interesting. Echeverria et al. [19] propose a design
methodology for integrating the characteristics of a game with
the various elements of a course. They identify the various ele-
ments of games and course contents: a Ludic Dimension is the
set of elements of a game, whereas an Educational Dimension
is the set of elements of a course [19]. The integration of the
Ludic and Educational Dimensions combines mechanics with
cognitive processes, type of knowledge, pedagogical model, and
To include game playing in learning activities, instructors
should consider the nature and content of the course and who
their students are. For example, students of different age levels
have different game preferences. Primary school students may
like single-player games. For them, playing simple task-per-
forming games and performing better than their classmates can
bring about a sense of achievement [20], [21]. High school
students prefer games with an abundance of video images and
sound effects. Apart from their requirement for systematic
scenarios, they also have higher expectations for software
quality [2]. College students, on the other hand, prefer multi-
player online games in which they can interact with others.
The content of such games evolves according to the manner
in which the players interact [22]. Past works on game-based
learning have focused mainly on primary and high school
courses [23], but rarely on college courses. For college stu-
dents, a game has to have a reasonable degree of sophistication
to be “playable.” Therefore, the principal issue here is how
game-based learning can be designed to improve college
students’ learning motivation, thereby helping them achieve
better learning outcomes. This study develops a peer interac-
tion game with a competitive cooperative learning style and
integrates the game with the course content. By playing the
game, students participate in a group process; members of
the same group coordinate, discuss, and share their thoughts,
whereas different groups compete with one another. From the
perspective of course nature and content, the Operating Systems
course requires programming practices, along with concept
understanding and memorization. It is generally considered a
boring course, and many of the students who enroll have low
motivation. Therefore, there is a strong incentive to include
game-based learning in the teaching of this course.
A. Game Method
The study described here develops a peer interaction game
for six players. The players are divided into two competing
three-person teams. A team size of three persons was selected
so that every team member can be fully involved. It also makes
it possible for skills to be used at appropriate times and ensures
that the game does not take too long to complete. This design
accords with Lou et al. [24], who suggest that the best arrange-
ment is to have three to four persons per team. This also ensures
that the game-playing system provides adequate room for all
players to participate.
Students log in to the game online. Once they are logged in,
each team of three must decide who will play which role, with
each player taking one role. When all six players have chosen
their roles, the game automatically begins. Different roles corre-
spond to different professions, and each profession has its own
set of attributes and skills. For example, the main skill of a war-
rior is to attack. The design of this role emphasizes the amount
of blood loss for each attack, as Fig. 1 shows. In contrast, the
wizard’s role emphasizes assisting team members, as Fig. 2
shows. Lastly, the main emphasis of the archer is on helping
team members attack opponents more effectively. Therefore, in
the design of this role, emphasis is placed on controlling the time
Fig. 1. Warrior skills.
Fig. 2. Wizard skills.
Fig. 3. Archer skills.
for answering questions, as shown in Fig. 3. Assigning different
attributes to each role means that students can not only hold dis-
cussions via the Web, but also make use of the different skills
to dramatically increase their interest in playing the game. This
results in a better learning effect.
Fig. 4 presents a snapshot of the gaming interface. The two
participating teams are labeled as the Union and the Tribe. As
the game starts, the system randomly decides whether it is the
Union’s or the Tribe’s turn to attack. The game is played round
by round. Assume that it is the Union that attacks and the Tribe
that defends. Then, one Union team member chooses a ques-
tion for a Tribe team member to answer. Subsequently, a Tribe
team member chooses a question for a Union team member to
answer. Fig. 5 presents this question and answer sequence. The
questions used are multiple-choice, and each has its own time
limit. Each player can use the skills associated with his/her role
Fig. 4. Game interface.
Fig. 5. Game sequence.
to improve the effect of attack or defense for his/her team. The
use of a skill by a player always costs some magic point (MP)
As they play, all players can see the full set of available game
questions listed in the Candidate Question Area of the center
of Fig. 4. Within a prespecied time limit, the attack team can
discuss which question they want to use for their attack, and
the defense team can discuss which one they will select in the
next round. They do this in the area titled “Discussion with the
group” (Fig. 4, lower left). Once the attack team has selected
the “attack question,” members of the defense team can see it in
their Question-to-Answer areas, and the answer choices will ap-
pear in their Answers-to-Question areas. However, only the des-
ignated defender can answer the question. The other two mem-
bers of the defense team can only discuss the answer choice with
the designated defender. Once the designated defender has se-
lected an answer, the system checks it for correctness. If the an-
swer is correct, the blood level of the attack team is lowered. If
the answer is incorrect, the blood level [health point (HP) value]
of the defense team is lowered. If the blood level of a player
reaches zero, that player is forced to retire from the game and
he/she will no longer be able to use his/her skills or participate
in the discussions. When the blood levels of all three players on
a team reach zero, the game is over.
The peer interaction game used in this research encourages
team members to cooperate with one another when competing
with another team. By incorporating competition, the game mo-
tivates participants to win. Moreover, by providing a means for
team members to discuss a question posed to any one of them,
the game allows the other two team members to provide timely
assistance. These factors—cooperation, competition, and dif-
ferent skills attributed to different roles—are what make the
game appealing to students.
The peer interaction game used in this study is specically
designed for students in the Operating Systems course. Its most
important characteristic is peer interaction, followed by the de-
sign of skill sets assigned to different player roles and the ef-
fects of using these skills in game playing. Consider peer inter-
action, for example. Teammates discuss which attack questions
to choose, as well as answers to questions assigned to them by
the opponent; they also discuss which skills they should use and
when, according to whether they believe their answer to a ques-
tion is correct and whether their opponent will encounter dif-
culties in answering an attack question. When players use a skill
at the appropriate time, their likelihood of winning the game in-
creases. For example, when a player attacks the opposing team’s
wizard, the player’s teammate who is playing the warrior role
can use his/her “No Match” skill to decrease the blood level of
the wizard to zero. In this manner, the wizard will not be able
to use his/her skill to supply more blood to his/her team. Thus,
using the different skills provided in the game allows for var-
ious ways of playing, which makes the game much more fun
for learners.
B. Design Rationale of the Peer Interaction Game
In this study, the design rationale of the game is based on the
architecture proposed by Echeverria et al. [19], which combines
elements of the game with those of the course. Table I contrasts
the game design with the design principles proposed by Echev-
erria et al. Table II explains the various characteristics of the
peer interaction game.
A. Participants
In this experiment, the participants were 128 students
enrolled in the Department of Information and Computer En-
gineering, Chung Yuan Christian University. The participants
took the Operating Systems course in the Spring semester
of 2011. The two classes of this course naturally became the
experimental group and the control group, with 63 participants
in the experimental group and 65 in the control group. The par-
ticipants’ learning motivation, process, and achievement were
evaluated both before and after the experiment. A learning
motivation questionnaire was used to assess the change in
motivation. The MSLQ used by Pintrich et al. [25] assesses
three dimensions of learner attitude and includes 31 questions.
Wilke [26] indicates that only the rst dimension of attitude
pertains to learner motivation. Therefore, only 14 questions
relevant to the assessment of learner motivation were included
in the questionnaire used in this study. It was very difcult to
obtain ofine learning records. Therefore, a learning feedback
form (Table III) was used to ask the participants about their
learning processes. From this feedback form, and by retrieving
learning portfolios recorded online, it was possible to assess the
learning processes of the participants. Pretest and post-test were
performed to assess the participants’ learning achievements.
An additional questionnaire was used to ask the participants
whether they considered the game attractive and how they
evaluated it. There were 12 questions in this questionnaire
(Table IV).
B. Procedure
The experiment lasted eight weeks. The 63 participants in the
experimental group were randomly divided into 21 groups, with
three participants in each group, and the 65 participants of the
control group were randomly divided into 22 groups, with one
group containing only two participants.
There were three kinds of learning activities for the experi-
mental group: didactic teaching, asynchronous e-learning, and
peer interaction games. The control group did not participate in
the peer interaction game; they went through traditional coop-
erative learning instead. Figs. 6 and 7 present the experimental
procedure for the experimental and control groups, respectively.
The procedure comprised six stages. Stage 1 was the pretest:
Both groups took an exam and answered the learning motivation
questionnaire. No signicant differences were found between
the two groups. Stage 2 consisted of cooperative learning. The
experimental group engaged in cooperative learning by playing
the peer interaction game, whereas the control group did so in
the more traditional way, that is, face-to-face. Both groups used
the same set of questions designed by the instructor. All ques-
tions were multiple-choice. In Stage 3, the same learning mo-
tivation questionnaire was administered to determine whether
Fig. 6. Experiment procedure for the experimental group.
Fig. 7. Experiment procedure for the control group.
there was a signicant difference in learner motivation. Stage 4
was the post-test. Both groups retook the exam that they had
taken in Stage 1 as a measure of their learning achievements.
The set of questions used in the pretest was redesigned for the
post-test, so that members of the experimental group could not
benet from viewing more of the questions used in Stage 2. In
the test, there were multiple-choice questions as well as prob-
lems that required answers. In Stage 5, all the participants com-
pleted a learning feedback form, and their online learning per-
formances were calculated. In Stage 6, only the experimental
group lled out a questionnaire for the game.
As a result, the following data were collected: learning mo-
tivation questionnaire results from Stages 1 and 3, pretest and
post-test scores, online performance scores, learner feedback,
and questionnaire results for the game. After participants who
dropped out of the course or who did not participate in some
of the tests or questionnaires were excluded, 41 participants re-
mained in the experimental group and 40 in the control group.
The data collected for these 81 participants were subsequently
C. Data Analysis
Table V presents the ANOVA of learning motivation ques-
tionnaire results. In Stage 1, the F-value is no greater than the
critical value. This means that before the cooperative learning
activities, there was no signicant difference in learning mo-
tivation between the two groups. In Stage 3, the F-value is
greater than the critical value. This means that after members of
the experimental group participated in game-based cooperative
learning, their learning motivation signicantly increased; as a
result, there was a signicant difference in learning motivation
between the groups. This nding indicates that the game-based
cooperative learning used in the study is more effective than
traditional face-to-face cooperative learning for improving
learning motivation.
Table VI presents the ANOVA of pretest and post-test results.
For the pretest result, the F-value is not greater than the crit-
ical value, which means that there was no signicant difference
in learning achievement between the experimental and control
groups. For the post-test result, the F-value is greater than the
critical value, which means that there was a signicant differ-
ence in learning achievement. This, in turn, means that students
who participated in game-based cooperative learning achieved
more when compared to those who participated in traditional
face-to-face cooperative learning.
When students learn online, their learning activities can be
recorded in portfolios [27]. Translating these learner records
into overall online performance scores can help instructors un-
derstand how individual students perform online. In the past,
instructors have had to dene a weight for each item of online
behavior period. However, the resulting scoring scheme may be
too objective and may not correspond to real learner situations.
Li [27] suggests a method for computing overall online
performance scores based on Principal component anal-
ysis [28], [29]. Principal component analysis redistributes the
weights of all attributes and makes the attributes as independent
as possible. It is therefore suitable for revealing differences
between the attributes.
In this study, eight online behavior items were considered:
total number of logins, number of days logins occur, number of
course discussion posts, number of special topic posts, number
of clicks as related to course materials, hours spent studying
course materials, number of clicks related to course discussions,
and number of clicks related to special topic discussions. These
items were automatically recorded by the system when students
accessed the e-learning platform. Li’s method is used to trans-
form each student’s online behaviors into an overall online per-
formance score. Table VII presents the weights for these eight
The students’ online performance scores were computed and
analyzed to see whether they performed better in learning activi-
ties when they participated in game-based cooperative learning.
First, the students’ overall online performance scores were com-
puted for System Programming (a required course taught by the
same instructor during the Fall of 2010); these scores served as
the pretest. Then, the overall online performance scores from
the experiment were computed; these served as the post-test.
Table VIII presents the two ANOVA results of these scores. As
the table shows, there is no signicant difference in the pretest
scores between the groups. However, the post-test scores show
a signicant difference, suggesting that the use of game-based
cooperative learning is superior to traditional face-to-face co-
operative learning with regard to stimulating students’ online
learning activities.
In Stage 5 of the experiment, students lled out feedback
forms. Table IX presents a summary of the results. Table III
gives an explanation of the results.
Table IX shows that members of the experimental group spent
more time on learning activities as compared to their control
group counterparts. This suggests that game-based cooperative
learning provides further stimulus for learning. As it happened,
the instructor of this course also gave students the chance to
make up their homework at the end of Spring 2011. Table IX
shows that members of the experimental group were much more
aggressive than their control group counterparts in taking ad-
vantage of this chance.
In addition, when asked to describe how they learned for
the course, members of the two groups gave different answers.
Table X shows that members of the experimental group dis-
played a more positive learning attitude. In contrast, members of
the control group were not so uniform in terms of their learning
attitudes. Some learned actively, some passively, and some even
failed to keep up with the course. Overall, the ndings indicate
that game-based cooperative learning provides a better stim-
ulus for learning than does traditional face-to-face cooperative
After the experiment concluded, members of the experi-
mental group were given a questionnaire. A total of 46 ques-
tionnaire results were collected. A reliability analysis of these
46 questionnaire results found a Cronbach’s alpha value of
0.900. Table IV presents the results of the game questionnaire.
It shows that students had good interactions with their peers
during the game and were satised with these interactions.
The students also agreed that their interactions with the game
helped them to learn. This suggests that the game motivated
them to learn more. Overall, the students were interested in
the game and indicated that they would recommend it to other
students in the department. Moreover, students highly agreed
that they found it pleasant to win. This means that winning the
game can give students a sense of condence and achievement,
and it motivates them to learn more about operating systems.
The students also expressed that they were not satised with
the visual and sound effects of the game, but were otherwise
satised with how the questions were presented.
The goals of this research were to do the following.
— Develop a game integrated with the course content of, and
use it in teaching, the Operating Systems course. In playing
this game, team members cooperate with one another to
compete with another team.
Evaluate whether the use of peer interaction games im-
proves student learning motivation, performance, and/or
learning outcomes.
— Analyze the extent to which students are satised with this
To that end, this study investigated the differences in motiva-
tion, achievement, and activities between game-based coopera-
tive learning and traditional face-to-face cooperative learning.
It was found that game-based cooperative learning excels in
all these aspects. Therefore, the kind of online, multiplayer,
game-based cooperative learning used in this research is effec-
tive for improving learning achievement, and it has a positive
effect on the learning process as well.
The following qualitative observations were made regarding
the process of cooperative learning in the two groups. Driven
by the desire to win (Table IV, Item 10) students participating
in game-based cooperative learning try to nd answers through
online group discussions whenever they are being “attacked”
by questions with which they are unfamiliar; they also carefully
plan the use of the skills to maximize their chances of win-
ning. Even if the answers they give are wrong, they continue
playing the game, and they are more likely to study unfamiliar
course content afterwards. In contrast, students participating in
the traditional face-to-face cooperative learning tend to rely on
the more capable students in answering the given questions.
The activity easily becomes centralized learning, with only the
more capable students actually participating. Those who rely on
the more capable students tend not to realize that they lack the
necessary knowledge, and they are less likely to study more in
This seems to be the reason why members of the experi-
mental group spent more time on various learning activities
(Tables VIII and X). It also explains why they learned more in
general (Table VI).
There are also some conclusions that can be drawn from
the participant feedback. Since members of the experimental
group were more willing to spend time on learning activities,
this shows that game-based cooperative learning can stimulate
active learning. Many control group members relied on others
to answer questions. Therefore, it is only natural for these
students to be less active in learning.
In the future, the goal is to apply game-based cooperative
learning in different courses and for various types of participants
in order to gain a broader understanding of the applicability of
this pedagogy.
Future versions of the game should improve the visual and
sound effects. More dynamic pictures and skills can be added
as well to further motivate the students to play.
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Bin-Shyan Jong received the B.S. degree in electronic engineering from
Chung Yuan Christian University, Taoyuan, Taiwan, in 1978, and the M.S.
and Ph.D. degrees in computer science from National Tsing Hua University,
Hsinchu, Taiwan, in 1983 and 1989, respectively.
He is a Professor with the Department of Information and Computer Engi-
neering, Chung Yuan Christian University. His research interests include com-
puter graphics and computer-aided education.
Chien-Hung Lai received the B.S. and M.S. degrees in information and com-
puter engineering from Chung Yuan Christian University, Taoyuan, Taiwan, in
2008 and 2010, respectively, and is currently pursuing the Ph.D. degree in elec-
tronic engineering at Chung Yuan Christian University.
His research interests include computer-aided education.
Yen - Te h H s i a received the B.S. degree in navigation technology and marine en-
gineering from National Chiao Tung University, Hsinchu, Taiwan, in 1978, and
the M.S and Ph.D. degrees in computer science from the University of Kansas,
Lawrence, in 1986 and 1989, respectively.
He is now an Associate Professor with the Department of Information
and Computer Engineering, Chung Yuan Christian University, Taoyuan,
Taiwan. His research interests include computer-aided education and articial
Tsong-Wuu Lin received the B.S. degree from Tamkang University, Taiwan,
in 1985, and the M.S. and Ph.D. degrees from National Tsing Hua University,
Hsinchu, Taiwan, in 1987 and 1991, respectively, all in computer science.
He is now a Professor with the Department of Computer and Information Sci-
ence, Soochow University, Taipei, Taiwan. His research interests include com-
puter graphics and computer-aided education.
Cheng-Yu Lu received the B.S. and the M.S. degrees in information and com-
puter engineering from Chung Yuan Christian University, Taoyuan, Taiwan, in
2009 and 2011, respectively.
His research interests include computer-aided education.
... Games had been used in many areas (such as learning [1] and business [2]) to promote entertainment. Among the mechanisms used to increase enjoyment involves usage of game elements [2], competition [1], and psycho-physiology [3]. ...
... Games had been used in many areas (such as learning [1] and business [2]) to promote entertainment. Among the mechanisms used to increase enjoyment involves usage of game elements [2], competition [1], and psycho-physiology [3]. Since rewards played an integral part in gamified interventions [4], the underlying mechanisms of in-game rewards are relatively limited and understudied. ...
... A. GAME PROGRESS MODEL A game progress model by [11] involves modeling the amount of solved uncertainty of the game as a function of x(t) based on an increasing function of time t. A realistic formulation of game progress with the known outcome is given as (1). The parameter n (1 ≤ n ∈ R) is the number of possible options and x(t) is normalized within the range of 0 ≤ x(t) ≤ 1. Deriving x(t) twice at t ∈ [0, T ], given by (2), it indicates the change velocity or rate of acquired information (acceleration) of the solved uncertainty of a game. ...
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Game refinement theory has been studied to derive a measurement of game sophistication. Recently, it has been developed as physics in mind, which may relate to the state of player's feelings such as satisfaction and comfort in mind. This article explores a link between game refinement theory and reinforcement schedule. A notion of winning hardness to achieve the goal (m) of a gamified activity, relative to the reinforcement schedules (N), is proposed through the physics in mind measures, which is utilized to quantify an activity's enjoyment. By applying these new measurements to various gaming activities, the sense of player satisfaction and sophistication in game-playing is induced. Indicators for cultural changes and their implications to game-playing landscapes and experiences were established based on evidence from various well-known games. From such findings, the link between game refinement theory and reinforcement schedule may imply that classifying the games according to our mind's psychological activities is vital in design decisions that largely influences people's quality of life. INDEX TERMS Reinforcement schedule, game refinement theory, physics in mind, gaming activity, cultural drive.
... Flip chart medium is simple, economical, easily obtained materials, can convey summaries, able to overcome the space and time limitation without requiring special equipment and easy placement. Some strategies that have been successfully implemented in the learning process are e-learning [10], web based learning [11], Moodle [12], animation [13], audiovisual [14], and games [15]. Edward et al. (2019) using Moodle as a medium to improve student competencies especially oriental music at Senior Secondary Level in Sri Lanka [12]. ...
... Bin Shyan Jong et al. (2013) uses games as a strategy in classroom learning. Game-based learning takes many forms, including virtual reality, role-playing, and doing assignments [15]. The research investigates the implementation of game-based cooperative learning in the operating system. ...
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This study aims at improving student learning achievement using flip chart medium design based on cooperative learning method. To prove this goal, this study is focused on (1) knowing the effectiveness of learning media (flip chart) applied to thematic subjects for grade 2 elementary schools in Rejotangan District on student learning outcomes; (2) finding out whether there is an influence of the use of flip chart learning medium on the thematic subjects learning outcomes of grade 2 elementary school students in Rejotangan Districts. The population of this study was 12 elementary school institutions in Rejotangan, Tulungagung subdistrict, by setting 4 schools as samples which were divided into 2 schools as experimental classes (flip chart learning design) and 2 schools as control classes (conventional learning). The sample selection is done using a simple random sampling technique and the data analysis techniques carried out descriptively and inferentially. The results of this study indicate that flip chart learning medium based on cooperative learning method can be said to be quite effective in improving student learning outcomes. This is evidenced by using the N-Gain Score test with a significance level of 62%, while conventional media is not effectively applied to thematic subjects with a percentage of 8%. Furthermore, Mann Whitney test results show that the significance score is 0.00. Therefore, it can be seen that there is a positive influence on the use of flip chart learning medium on learning outcomes in thematic subject of grade 2 elementary school in Tulungagung subdistrict. The results recommend that using cooperative learning with flip chart as a medium is very effective in improving student learning outcomes on thematic subjects of elementary schools lower graders.
... Boredom and reduced motivation for learning are caused by boring training in vocabulary learning (e.g., vocabulary recitation) [5]. In the learning support method using gamification to improve motivation, user's learning motivation and active learning are increased by incorporating ingenuity into the in-game process (e.g., cooperation, communication, and social interaction between learner groups) [4,25,26]. Gamification has also been used for English vocabulary learning [27,28]. There is a method that uses gamification and appropriate difficulty setting to support continuous learning [3] and a method that uses gamification and automatic speech recognition technology to support learning for English pronunciation [29]. ...
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Memorization is necessary for various fields, such as language learning in the field of education. While memorization learning is often tedious and demotivating due to requiring conscious effort, few support approaches improve memorization unconsciously with low conscious effort. In this study, we propose a method, Mindless Memorization Booster, which improves users’ memorization unconsciously by visual stimuli of modulating the visual interface. This method is based on previous findings that the modulation of perceptual stimuli arouses attention/concentration. When the user looks at the memorization target, the proposed method presents a change in visual interface (e.g., changes in memorization target size, background color, and visual icon movement) to cause a psychological phenomenon of affecting the user’s attention and concentration, aiming at enhancing the memorization unconsciously. A prototype system of the proposed method was implemented for an English vocabulary memorization learning application. The evaluation results showed that the user’s memorization result was affected by the proposed method, and the speed of recall (i.e., outputs of the memorization word from the brain) increased by about 1 s per one memorization word without causing a negative affection on the number of correct answers for memorization. This result indicated the feasibility of the proposed method for memorization learning support. Our findings are helpful for designing visual information interfaces that consider the phenomena affecting the user’s memorization and promote memorization learning unconsciously.
... Game-based learning also explains how the balance between the necessity of covering subject matter and gameplay entertainment is created [21]. Of equal importance to game-based learning lies the assessment of student outcomes such as academic performance [22][23][24], motivation [25,26], and engagement [27], though these things may be personal, i.e., premised on an individual's preferences or perceptions [28,29]. ...
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The use of educational digital games as supplemental tools to course instruction materials has increased over the last several decades and especially since the COVID-19 pandemic. Though these types of instructional games have been employed in the majority of STEM disciplines, less is known about how diverse populations of students interpret and define the value of these games towards achieving academic and professional pursuits. A mixed-method sequential exploratory research design method that was framed on the Technology Acceptance Model, Game-Based Learning Theory and Expectancy Value Theory was used to examine how 201 students perceived the usefulness of an intuitive education game that was designed to teach engineering mechanics used in designing civil structures. We found that students had different expectations of educational digital games than games designed for entertainment used outside of classroom environments. Several students thought that the ability to design their own structures and observe structure failure in real-time was a valuable asset in understanding how truss structures responded to physical loading conditions. However, few students thought the educational game would be useful for exam (14/26) or job interview (19/26) preparation. Students associated more value with engineering games that illustrate course content and mathematical calculations used in STEM courses than those that do not include these elements.
The flipped classroom approach is aimed at improving learning outcomes by promoting learning motivation and engagement. Recommendation systems can also be used to improve learning outcomes. With the rapid development of artificial intelligence (AI) technology, various systems have been developed to facilitate student learning. Accordingly, we applied AI-enabled personalized video recommendations to stimulate students' learning motivation and engagement during a systems programming course in a flipped classroom setting. We assigned students to control and experimental groups comprising 59 and 43 college students, respectively. The students in both groups received flipped classroom instruction, but only those in the experimental group received AI-enabled personalized video recommendations. We quantitatively measured students’ engagement based on their learning profiles in a learning management system. The results revealed that the AI-enabled personalized video recommendations could significantly improve the learning performance and engagement of students with a moderate motivation level.
In the last few decades, different teaching methodologies have been proposed to promote more active learning of students. However, it is still essential to understand the practical implications of the theoretical concepts incorporating additional methodologies, for example, problem‐based learning. This methodology could include practises focused on students' programming or on using appropriate software tools. For more meaningful learning, the use of a graphic tool instead of programming provides more insight into those concepts throughout a simple and practical resource. Taking this into account, a software tool has been developed in addition to theoretical sessions in the context of a subject of the Degree in Computer Science, where the learning objectives are related to the representation and compression of multimedia content. In addition, this tool allows to configure useful exercises for these practical sessions, such that students can experiment and analyse the results from a visual perspective. The results of the surveys show a high degree of satisfaction of students, who highlight that the tool has helped them to better understand the curriculum content. In addition, there are signs of improvement in the academic results corresponding to the evaluation of performance with such software.
This project explored how virtual reality (VR) can be used in artificial intelligence (AI) education. A prototype VR application was developed to give students an introduction to deep learning using the Oculus Quest. The application applied escape room elements as an attempt to let students learn the curriculum in an engaging way by doing 3D-puzzles, calculations, and quizzes based on the course-material. The topics were split into separate rooms to let students progress through the curriculum intuitively. 15 people tested the application and responded to a questionnaire. 26 people evaluated the application’s concepts after watching a video. Based on the evaluation, we believe that using such a VR application in AI education can be a good supplementary tool to introduce students to new topics in an engaging way. The main advantage of using VR in this context is to use interactive 3D-visualizations and hands-on activities that are challenging to experience by other means. The questionnaire’s respondents were very positive to the concept, and it could potentially be beneficial in other types of STEM-education as well.
This book constitutes the refereed proceedings of the First International Conference on Innovative Technologies and Learning, ICITL 2018, held in Portoroz, Slovenia, in August 2018. The 66 revised full papers presented together with 4 short papers were carefully reviewed and selected from 160 submissions. The papers are organized in the following topical sections: Augmented and Virtual Reality in Education; Collaborative Learning; Design and Framework of Learning Systems; Instructional Strategies; Learning Analytics and Education Data Mining; Mind, Brain and Education; Pedagogies to Innovative Technologies; Personalized and Adaptive Learning; Social Media and Online Learning; Technologies Enhanced Language Learning; Application and Design of Innovative Learning Software; Educational Data Analytics Techniques and Adaptive Learning Applications; and Innovative Thinking Education and Future Trend Development.
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This study employs methods of questionnaire and in-depth interview to analyze and integrate factors of creating online game stickiness and causing continuity of using on-line instructional material. The major findings include: (1) Factor clusters of creating online game stickiness and causing on-line instructional material continuity could be grouped into 4 categories including: user psychology, interaction within community, product design, and the company’s services and reputation; (2) Multimedia application, feedback design, trading system, virtual space, playfulness, role-playing, and challenges are the factors belonging to both clusters and could be used in designing game-based learning materials; (3) Competition, virtual treasures, and experience to explore are the factors different from each clusters but still could be applied; (4) In the aspects of operating game-based learning materials, the product price, online quality, crisis management, and network security, are important issues to be taken care of for the industry.
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Research on classroom cooperative learning techniques, in which students work in small groups and receive rewards or recognition based on their group performance, has been increasing in the past few years. This review summarizes the results of 28 primary field projects lasting at least 2 weeks, in which cooperative learning methods were used in elementary or secondary classrooms. The pattern of research findings supports the utility of cooperative learning methods in general for increasing student achievement, positive race relations in desegregated schools, mutual concern among students, student self-esteem, and other positive outcomes. The various cooperative learning methods are contrasted in terms of characteristics and outcomes, and the next steps for research in this area are outlined.
This is the second article in a series of articles published with findings on student perceptions of asynchronous web-based courses (P{\'e}rez Cereijo, Young, & Wilhelm, 2001). This portion of the study examines the independent relationships between various student characteristics and student's perceived advantages and disadvantages of the asynchronous web delivery of the course and seeks to find a predictor that will help determine students most likely to enjoy taking asynchronous courses online. In the asynchronous web delivery format of this course, students had access to the class's lecture videos and textual course materials stored in the school's server, at any time and from anywhere. The data presented in this study provides supporting evidence, which reaffirms universities' commitment to offering online courses to meet students' needs. The study also points to attitude, work schedule, and distance from school as possible predictors of student success in this environment.
The effects of within-class grouping on student achievement and other outcomes were quantitatively integrated using two sets of study findings. The first set included 145 effect sizes and explored the effects of grouping versus no grouping on several outcomes. Overall, the average achievement effect size was +0.17, favoring small-group learning. The second set included 20 effect sizes which directly compared the achievement effects of homogeneous versus heterogeneous ability grouping. Overall, the results favored homogeneous grouping; the average effect size was +0.12. The variability in both sets of study findings was heterogeneous, and the effects were explored further. To be maximally effective, within-class grouping practices require the adaptation of instruction methods and materials for small-group learning.