SERIOUS GAMES ON MULTI TOUCH TABLES
FOR COMPUTER SCIENCE STUDENTS
Jan Holz, Nadine Bergner, Andreas Schäfer and Ulrik Schroeder
Computer-Supported Learning Research Group, RWTH Aachen University, Ahornstr. 55, 52074 Aachen, Germany
Keywords: Computer Science Education, Higher Education, Serious Games, Multi Touch Table, Algorithms.
Abstract: Within the project IGaDtools4MINT one of our goals is a pedagogical redesign of the introductory phase of
CS studies. This paper describes an approach to develop and use serious games on multi touch tables to
support collaborative learning processes at university. After giving a short overview over the context of the
project, we briefly describe the educational and technological concepts behind the development process. As
an example a multi touch application for learning resolution in propositional logic through collaboration and
competition is introduced.
1 INTRODUCTION
The goal of IGaDtools4MINT is the development of
a concept which contributes to the increase of the
percentage of women as well as to a reduction of the
drop-out rate in STEM subjects. The concept is
based on the analysis of existing best practice
measures and is supposed to lead to a
comprehensive catalogue of measures. By this
means gender-equal didactics and an opening of the
faculty culture for diverse women and men is
intended.
To take concrete measures a pedagogical concept
with four steps was developed, which should
gradually guide students from school to university:
1. Foster interest in CS for school students by
providing a students’ lab for CS
2. A preliminary CS course for freshmen
3. Supporting students with problems during
CS courses at university
4. Integrating gender and diversity aspects
during regular teaching at university
Within this, the development and use of serious
games is located in step one and three. The
presented multi touch application about resolution in
propositional logic for example targets at university
students with problems during the corresponding
lecture.
2 MOTIVATION
2.1 Games in Education
While regular university courses might tend to fulfil
the cliché of boring learning environments, there is a
plethora of pedagogical approaches, which aim at
making learning more interesting, more personally
relevant and more fun. One way to achieve this is
based on the usage of games.
Combining learning with gaming results in the
concept of serious games, which aim at more than
mere entertainment: They have an educational
purpose, including teaching, training and informing
its players, wrapped up in an entertaining
environment (Michael and Chen, 2005).
Generally games have several aspects that make
them suitable for educational purposes. Depending
on the game design, serious games offer great
possibilities for motivating students, promoting
collaborative learning or arousing enthusiasm by
using competitive elements (Hakulinen, 2011).
Nevertheless it has to be kept in mind, that games,
just as any other concept for motivation, are not an
all-round solution and not all students can be
motivated by using games, though their attitude
generally is positive (Whitton, 2007).
2.2 Using Educational Games in CS
Concerning the field of computer science education
the interactive learning style invites to use serious
519
Holz J., Bergner N., Schäfer A. and Schroeder U..
SERIOUS GAMES ON MULTI TOUCH TABLES FOR COMPUTER SCIENCE STUDENTS.
DOI: 10.5220/0003965405190524
In Proceedings of the 4th International Conference on Computer Supported Education (SGoCSL-2012), pages 519-524
ISBN: 978-989-8565-07-5
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)
games for algorithm teaching. Algorithms are often
complicated and abstract concepts. Ergo, working
with algorithms is a very challenging task for
lecturers and students (Shabanah and Chen, 2010).
To support the process of algorithm learning
algorithm visualization is an established measure
(Shaffer et al., 2007). Based on the theoretical
findings of this learning approach, which is often
rather passive, serious games can be used for
interactive algorithm learning in computer science.
Shabanah and Chen specifically highlight the
benefits of using serious computer games for
algorithm learning: Computer games are popular,
interactive and competitive and they utilize
entertainment and simplify assessment (Shabanah
and Chen, 2009).
Yet, there are several different ways of using
serious games in computer science education
(Wallace et al., 2010):
Playing games
Implementing (certain aspects of) games
Implementing a computer player for a game
While the first point is applicable for serious games
in all fields, it is often neglected by computer
science education as it focusses on the remaining
two points. Nevertheless there are also games in
which the student is the player and not the
programmer.
Subsequently this paper focusses on serious
computer games for computer science education
where the learning of algorithms is supported by
playing multi touch games.
3 RELATED WORK
3.1 Educational Background
3.1.1 Learning Models and Taxonomies
When developing games for educational purposes,
several different theories can be used as guidelines
for designing the learning environment:
Blooms revised Taxonomy
Gagnes nine events of instruction
The Felder-Silverman learning model
The Engagement Taxonomy
Blooms revised Taxonomy provides us with a
hierarchical system for classifying learning
objectives in six categories (Bloom, 1984).
With the instructional design theory “Nine steps
of Instruction”, Gagne provides a scheme to
purposefully pursue the formulated learning
objectives within the learning process (Gagne et al.,
1988).
Furthermore the Felder-Silverman learning
model helps us to design these steps with respect to
different learning styles. This certainly has its limits
within learning environments which are designed for
collaborative learning, but the model helps to avoid
neglecting any of these styles. One of the findings of
Felder and Silverman was that most people
comprehend graphical representations of certain
information better than textual representations
(Felder and Silverman, 1988).
This leads to using the Engagement Taxonomy
during the development process (Naps et al., 2002).
This taxonomy was proposed to “better
communicate learners’ involvement in an education
situation that includes visualization” (Naps et al.,
2002) and defines “six different forms of learner
engagement with visualization technology” (Naps et
al., 2002). For developing a collaborative serious
game the research by Korhonen et al. is of great
interest, as it has shown, that “the amount of
discussion in collaboration is […] different between
engagement levels, and increases as the engagement
level increases”. This research was based on the
Extended Engagement Theory, which introduces
more fine grained steps (Korhonen et al., 2009).
3.1.2 Intrinsic and Extrinsic Motivation
When trying to motivate students to play a learning
game, two different categories of motivation should
be considered that were described by Malone:
Intrinsic motivation and extrinsic motivation. While
extrinsic motivation is induced by external stimuli,
like additional points for an exam, intrinsic
motivation arises from the activity of playing the
game itself (Malone, 1980). A strong positive
correlation between a learning activity’s potential
for intrinsic motivation and the activity’s learning
effect is assumed (Schiefele and Schreyer, 1994).
Malone describes several heuristics for designing
motivating serious games. Some characteristics are
decisive for individual learning without a group:
curiosity, challenge, control and fantasy. The
interaction of learning in groups is targeted by
different aspects like collaboration, competition and
recognition (Hejdenberg, 2005). These aspects were
considered when designing the different gaming
modes.
3.1.3 Collaboration and Competition
Concerning the aspect of working and learning in
groups, one can find slightly differing definitions for
CSEDU2012-4thInternationalConferenceonComputerSupportedEducation
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collaboration and cooperation, although both terms
are often used synonymic. Subsequently
collaboration is used as the general concept of
“working together”, whereas cooperation
specifically means situations where a division of
labour takes place.
Some important positive effects of collaborative
learning can be summarized as follows (Straub,
2001); (Arvaja et al., 2003):
Being more involved into the topic.
Process the learning content more actively.
Support in joint critical thinking.
Become aware of own thinking processes.
As multi touch tables inherently support
collaborative work (Khaled et al., 2009), there are
plenty of possibilities to use these benefits for learning
processes within serious games. Still it is important to
foster the process of collaboration to promote its
positive effects, as learners do not necessarily interact
with each other, just because the environment provides
the possibility (Krejns et al., 2003).
At this point the aspects and dimensions of
collaboration, identified by Meier et al., help to
structure and address the different components of
collaboration (Meier et al., 2007):
Communication
Joint information processing
Coordination
Interpersonal relationship
Motivation
Opposing this, the motivating concept of
competition can be divided into two categories as
well: Competitive elements and social competition
(Vorderer et al, 2003).
In this context competitive elements refer to
situations within the game in which the player faces
a certain necessity to act in a suitable way. Social
competition refers to the competition between the
learner as a player and an opponent, who can be
either virtual or human. According to Koster, it is
still an open question, whether social competition is
efficient to raise motivation (Koster, 2005).
3.2 Algorithm Visualization
Against the background of the described theories,
algorithm visualization is a promising way of
teaching and learning algorithms in computer
science education.
This approach is being used by many educators
and thus a plethora of different algorithm
visualizations can be found today. As Shaffer et al.
found out, the quality and distribution across the
topics of computer science is highly heterogeneous
(Shaffer et al., 2007). They collected over 350
visualizations and categorized them according to
their subject. The vast majority of algorithm
visualizations (ca. 292) deal with concepts that are
addressed during basic data structures and
algorithms lectures at university. Only a small
fraction of the remaining minority deals with
mathematical algorithms (four examples), so the
algorithm visualization within a serious game about
resolution in propositional logic tackles a relatively
unexplored area.
Yet, visualization of a mathematical algorithm
does not max out the potential for the learning
process. As the analysis by Hundhausen et al.
pointed out, the learners’ activities are of greater
importance for the learning process, than the content
of the visualization itself (Hundhausen, 2002).
Furthermore many studies indicated, that complex
issues are remembered the better the more active
learners participate in the topic (Prince, 2004).
One approach that considers these aspects is
Algorithm Visualization using Serious Games
(AVuSG) by Shabanah et al. With this concept an
algorithm is represented in four forms: as a text, as a
flowchart, as a game demonstration and as a game.
For each of these representation forms the learners
pass through a learning process of three consecutive
steps: the viewing process, the playing process and
the designing process.
Throughout these processes the learner starts
with viewing algorithm text, flowchart and demo,
before becoming active in playing the game.
Subsequently a creative creation process can follow
in which the student develops his or her own
algorithm text, flowchart, demo and game
(Shabanah and Chen, 2009).
The next step in development is to transfer this
concept for serious games to multi touch tables.
3.3 Multi Touch Tables in Education
So far multi touch learning applications can be
found primarily within the K-12 education sector
with focus on elementary schools. Examples for this
are projects like the multi touch learning software
for mathematics called MEL-Vis (Tyng et al., 2011)
or the Multitouch Education Table (MET) by
George et al., which features numerous virtual card
game suites e.g. about geography for elementary
school students or mathematics for class 7 to 12
(George et al., 2011).
But as multi touch tables encourage students to
experiment more with a problem and its solution
(Piper and Hollan, 2009), the technology can be
SERIOUSGAMESONMULTITOUCHTABLESFORCOMPUTERSCIENCESTUDENTS
521
regarded as suitable for learners of all ages,
especially as the usage of tables as interactive
objects additionally promotes collaborative working
by naturally providing space for an ideal group size
of four learners (Schneider et al., 2010).
Besides the, up to now, rather limited target
group, it seems that multi touch tables are used quite
seldom for computer science education. This is
insofar astonishing as the technological development
of multi touch tables or similar equipment is a highly
popular topic in computer science research. But it
seems that computer science education researchers
have paid relatively little attention to this so far.
4 SERIOUS GAME PROTOTYPE
4.1 Circumstances
As a basis for our applications we use the SMART
Table by Smart Technologies. Initially two different
prototypes of serious games about Dijkstra’s
algorithm were developed, which made only limited
use of the multi touch features of the table.
Subsequently the described prototype about
resolution in propositional logic was developed with
respect to the benefits of multi touch user
interaction. Current work in progress concentrates
on developing a multi touch learning environment
about sorting algorithms.
4.2 Game Design
The application was designed with nine different
usage modes, which can be divided into three
categories: Learning, Playing and Creating.
Figure 1: A screenshot of the cooperation mode.
Learning modes are primarily designed for
students who were only briefly introduced into the
topic of resolution or need to brush up their
knowledge. For this, four different learning modes
were designed to form the viewing process:
Animation mode:
Using this mode gives learners a first insight
into the execution of the resolution algorithm.
Feedback mode:
Within this mode learners have the possibility
to execute the resolution algorithm on their
own while receiving feedback to deepen their
understanding of the algorithm.
Quiz mode:
In this mode learners can explore the context
of resolution in propositional logic by facing
questions about the topic.
Formula mode:
This mode gives leaners the opportunity to
construct an equivalent conjunctive normal
form for a given logical formula to discover
the steps that lead from logical formulas to
resolution clause sets.
The playing modes are designed for long-term use of
the serious game. These four modes target at players
who already know the algorithm basics, but can still
profit from further practice:
Collaboration mode:
Round-based score-keeping challenge a team
of players to play against time. This mode can
also be used by a single player.
Cooperation mode:
For this mode players have to split up into
teams with different responsibilities
(execution of the resolution and answering
questions) to score as a group while playing
against time (see figure 1).
Competition mode:
In this mode two opponents play a round-
based duel by working with the same clause
sets.
Tactical mode:
This mode offers the possibility of
competition in duels with a wider tactical
range by introducing a set of bonus actions to
the gameplay (see figure 2).
The ninth mode, the creation mode, was
implemented to realize the designing process. This
allows students to create own clause sets, which can
be saved and used within the game.
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Figure 2: A screenshot of the tactical mode.
4.3 Implementation
The software was developed with respect to
heuristics concerning application design for tabletop
displays (Apted et al., 2009):
Interface elements are rotatable.
Touchable elements are easy to select.
Elements are movable to all areas of the table.
Movable elements can be quickly removed or
rearranged to avoid clutter.
The tabletop space is used efficiently.
Besides this, the aspect of extensibility was
considered as well. The serious game comes with a
predefined set of challenges and tasks, but users are
free to contribute their own clause sets, questions
and formulas. Besides the creation mode, new
content can be integrated directly into the document
structure of the software as XML file.
5 EVALUATION
To obtain first feedback about the prototype an
informal evaluation was conducted with participants
of the e-learning lecture at RWTH Aachen
University. Within this evaluation students had the
possibility to test this and other applications for 90
minutes. During the whole evaluation there were
always several students actively involved with the
game and several more were watching.
Feedback was collected by talking to the students
while they were performing tasks and by collecting
written feedback. The outcomes were directly
integrated into the development process. In general a
positive attitude towards the serious game was stated
and it was seen as a motivating approach on the
subject. Some students explicitly mentioned
cooperation and competition mode as fun to play.
For any further conclusions a formal,
quantitative evaluation of the serious game is
urgently needed.
6 CONCLUSIONS
We described our work of designing a theoretically
profound serious game prototype for multi touch
tables in the area of higher computer science
education. The present outcomes indicate this to be a
motivating and engaging approach to familiar topics
of computer science lectures. Consequently we will
be pursuing this way further.
7 FUTURE WORK
In the long run it is planned to integrate serious
games and other pedagogical approaches that differ
from regular courses into the first semesters of
computer science studies at university. These offers
will be an optional enhancement of the regular
learning methods. Thus it is crucial to design the
future learning environments to be engaging,
motivating and easy to use.
ACKNOWLEDGEMENTS
The project IGaDtoos4MINT is funded by the
Federal Ministry of Education and Research and the
European Social Fund for Germany.
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