Available via license: CC BY-NC-ND 4.0
Content may be subject to copyright.
Emendo – A Toolchain for Creating Gamified Learning
Arrangements for Online Learning Settings
Bartel, Alexander a; Hagel, Georg a and Wolff, Christian b
aFaculty of Computer Science, Kempten University of Applied Sciences, Germany,
bFaculty of Languages, Literature, and Cultures, University of Regensburg, Germany.
Abstract
This contribution describes the Emendo toolchain which enables the effective
creation and implementation of gamified learning arrangements for online
learning settings based on the domain-specific modeling approach. The
components of Emendo are a domain-specific modeling language, a
generator which transforms models based on the language into source code
as well as the embedding of the latter in a learning management system.
Scenarios for the usage of Emendo for teaching and learning are presented
with respect to the functionalities of the toolchain. In addition, a qualitative
evaluation concerning Emendo’s goals, concept and insights on the results is
given. The evaluation shows that Emendo reaches high acceptance for
teaching purposes and can serve as a promising means for the digitisation of
teaching and learning.
Keywords: Gamification; Learning; Learning Tool; Online Learning;
Learning Management System, Domain-specific Modeling.
4th International Conference on Higher Education Advances (HEAd’18)
Universitat Polit`
ecnica de Val`
encia, Val`
encia, 2018
DOI: http://dx.doi.org/10.4995/HEAd18.2018.8045
This work is licensed under a Creative Commons License CC BY-NC-ND 4.0
Editorial Universitat Polit`
ecnica de Val`
encia 613
Emendo – A Toolchain for Creating Gamified Learning Arrangements for Online Learning Settings
1. Introduction
Learning and the associated acquisition of skills and competences is possible in many ways.
One specific means is the use of online learning platforms or learning management systems
(LMS). In order to enhance learning motivation as the central driving force and hence a
prerequisite for learning to take place (Smolka, 2004), such platforms often integrate
aspects of gamification. Recent studies show that the concept of gamification can
successfully increase the learning motivation of individuals if it is integrated in learning
management systems (e.g. Ibanez et al., 2014; Bartel & Hagel, 2014; Hakulinen et al.,
2015; Hasegawa et al., 2015). According to Deterding et al. (2011), gamification can be
generically defined as “the use of game design elements in non-game contexts” (p. 10). In
this contribution, gamification is considered in the context of learning, and we will use the
following definition: “Gamification is described as a concept which integrates game design
elements and processes into learning activities in order to increase learning motivation and
thereby changes the behavior of learners” (Bartel & Hagel, 2016, p. 6).
Although various reports exist on how to integrate aspects of gamification in existing LMS,
e.g. as plugins into Moodle (Roderus, 2015) or as standalone applications (e.g. Hakulinen et
al., 2015), researchers (Dicheva et al., 2014; Dicheva & Dichev, 2016) argue that existing
learning management systems that integrate aspects of gamification
- are not effective in bringing gamified learning arrangements into practice,
- don’t provide an extensible set of elements for creating such arrangements and
- constrain instructors due to an inflexible environment.
1.1. Goals
This contribution demonstrates a novel toolchain called Emendo (Bartel et al., 2017) in
order to overcome the issues mentioned above. Emendo can be effectively used for creating
gamified learning arrangements in an online setting, it is extensible with regard to its
elements and does not constrain instructors in their definition of gamified learning
arrangements. Its basic toolchain structure as well as scenarios of usage for learning
purposes are demonstrated. Furthermore an evaluation with lecturers is shown. This
contribution complements the work described in Bartel et al. (2017) where Emendo was
technically detailed.
1.2. Structure
The rest of this contribution is structured into three sections: The following section relates
to the descriptions stated in Bartel et al. (2017) and presents an overview of the components
of the Emendo toolchain. In addition, it shows some scenarios for using Emendo and its
functionalities in learning contexts. The third section presents the goals, method and results
614
Bartel, A.; Hagel, G.; Wolff, C.
of an evaluation conducted with lecturers using Emendo. The last section summarizes the
findings and gives an outlook on future works.
2. Emendo Toolchain
2.1. Overview
The basic idea of Emendo was to build a system for creating and implementing gamified
learning arrangements since researchers argue that there is a lack of tools which efficiently
enable the creation of such arrangements for domain experts (Dicheva & Dichev, 2017).
For this pupose, the domain-specific modeling (DSM) approach (Kelly & Tolvanen, 2008)
was chosen because of the idea that domain experts without the need for technical
knowledge should be able to use Emendo and bring their ideas to class. Figure 1 shows an
overview of the Emendo toolchain and its components. As already stated in Bartel et al.
(2017), currently there is no comparable approach in the educational field.
As documented in Bartel et al. (2017) and as a first step, a domain-specific modeling
language (DSML) was created following a literature review considering more than 3600
papers and a domain analysis of 12 gamified learning platforms. More than 91 conceptual
requirements (which were aggregated to concepts) for the Emendo DSML were elicitated
including various types of: game design elements (e.g. Badges, Points, Levels,
Leaderboards etc.), tasks (e.g. single choice, multiple choice etc.), learning materials (e.g.
texts, videos, podcasts etc.), rules for rewarding game design elements and giving feedback,
and elements to arrange them into learning paths. Subsequently the Emendo Designer was
created which enables the creation of models of the Emendo DSML by domain experts.
These models are instances of the abstract Emendo DSML and bring gamified learning
arrangements into practice: A code generator processes the gamified learning arrangements
and its output serves as input for the Emendo Learning Management System (LMS). The
Emendo LMS allows learners to work with the learning arrangements defined by lecturers.
During learners’ interaction with Emendo, lecturers can interact with them by discussing
questions and giving feedback on learners’ answers. Furthermore lecturers can track the
individual learning progress of learners with the use of learning analytics the LMS
provides.
2.2. Usage Scenarios
Emendo allows various scenarios of usage, depending on educational goals and the context
it is used in. This variety of applications is made possible by the design of the system: In
contrast to existing learning management systems, Emendo does not aim to provide static
heuristics for the modeling of gamified learning arrangements.
615
Emendo – A Toolchain for Creating Gamified Learning Arrangements for Online Learning Settings
Figure 1. Overview of the Emendo toolchain
Emendo's basic heuristics can be changed and adapted as required and is not limited by a
strict corset of building blocks for teaching. For example, if a particular type of learning
task or a certain type of feedback is not represented, it can simply be added to the Emendo
DSML as well as to the Emendo LMS. Admittedly, this adaptation requires a basic
understanding of the technical functionality of Emendo. However, Emendo already
provides a wide range of concepts that can be used in gamified online learning scenarios. In
parts their use is described in the following from the perspective of lecturers.
Emendo allows the definition of individual learning paths and the structuring according to
the learning goals or the educational contents of each path. This gives learners the freedom
to choose which learning element they want to deal with according to their personal sense
of competence and increases their sense of autonomy – an important influence on learning
motivation according to the self-determination theory (Ryan & Deci, 2000). Besides the
structuring of learning paths, Emendo also distinguishes between learning elements that are
616
Bartel, A.; Hagel, G.; Wolff, C.
optional and mandatory to process for learners. Hence, Emendo can be used simply for
learning (e.g. reading texts, watching videos) or testing learners’ performance (e.g.
integrating a quiz consisting of different types of questions in the middle of a learning topic
or in order to finalize a whole learning path). According to learners’ actions and the
progress state of learning elements, lecturers can integrate contextualized feedback. For
example, if a learner answered a single choice question, Emendo allows the definition of
several feedbacks, e.g. one which is displayed to provide a hint for its correct processing
when it was answered incorrectly and another one which is shown when the answer was
correct and to show its pedagogical value in the whole context (Nicholson, 2015). Besides
feedback, learners can be rewarded with game design elements, like points or badges,
which reflects typical elements of game mechanics like achievements or the collection of
virtual goods (Werbach & Hunter, 2015). The game design elements not only serve as an
external incentive, but also as a means of determining relative progress in comparison with
other learners. This leads to social inclusion and comparison which can further drive the
motivation to learn (Nah et al., 2013).
Emendo is not only extensible regarding its concepts, it is also scalable in terms of learning
units. An entire course covering a whole semester can be defined (e.g. as a blended learning
course), as well as a single unit within a course (e.g. as a peer instruction unit).
Furthermore, from a students’ point of view, the LMS can either be used as a client on
computers or mobile devices which allows formal learning in educational institutions and
informal learning in their leisure time.
3. Evaluation
3.1. Goals and Evaluation Concept
A first evaluation was conducted that aimed at finding out how lecturers evaluate Emendo.
The following research questions guided the evaluation:
- RQ1: How do lecturers judge Emendo regarding its applicability and usefulness
for their teaching in general?
- RQ2: How do lecturers judge the modeling experience using the Emendo DSML
in the Emendo Designer for creating a gamified learning arrangement?
To answer the research questions a two-part qualitative evaluation concept was developed:
As a first step and in order to enhance comparability, a short video was shown to the test
persons demonstrating the components and features of the Emendo toolchain, followed by
an semi-standardized interview based on the Structure Laying Technique (SLT) according
to Scheele & Gröben (1988). In the second part, the test persons received a handout
containing a description of the user interface of the Emendo Designer and explanations for
the elements of the Emendo DSML. In addition, the handout contained a scenario
617
Emendo – A Toolchain for Creating Gamified Learning Arrangements for Online Learning Settings
describing a gamified learning arrangement as a learning unit for a software engineering
course. After the guided application of the Emendo Designer, test persons were
interviewed using the SLT. As in the first part of the evaluation, the SLT allows given
patterns of actions to be combined with experiments. Additionally, all statements of
probands were visualized with flashcards and were adjusted in dialogue with the researcher.
Thus, the interviewer can ask for more information on a certain argument.
The sample of this qualitative evaluation includes n=8 (3 female, 5 male) university
lecturers who participated voluntarily. Each evaluation had an average duration of 2 hours.
To maximize variety, the persons interviewed were chosen according to specific personal
criteria (e.g. experience in using gamification, specialist area, experience in teaching etc.).
The interviews were recorded and analyzed together with the flashcards regarding the
research questions.
3.2. Results
Due to capacity reasons only a small part of the results are demonstrated in this
contribution. In general, both research questions can be answered positively. In particular,
all participants stated that they would actually integrate Emendo in their teaching since it
supports the quick implementation of ideas for teaching. The vast majority (n=7) also stated
that they see a high applicability of Emendo for learning because it is not bound to a
technical discipline, its learning elements are extendable and it provides the possibility to
increase students’ learning motivation due to the use of gamification and the way it
facilitates adaptive learning facets. Prerequisites for an integration in courses is a fast,
intuitive and easy use of the tools, especially concerning the Emendo Designer with its
DSML. Furthermore, the integration in existing LMS like Moodle has a high significance
for the interview partners. In addition, Emendo needs to provide a solid documentation and
support (e.g. automated imports) to keep the effort for switching over from existing course
compositions low. Regarding the second research question, figure 2 gives an overview of
the aggregated positive (green) and negative (red) statements.
Figure 2. Aggregated result statements regarding RQ2
618
Bartel, A.; Hagel, G.; Wolff, C.
4. Conclusion and Future Work
This contribution demonstrates the Emendo toolchain, its components and suggestions for
scenarios of usage based on its functionalities. A qualitative evaluation of its goals,
concepts is shown along with insights on results. Emendo introduces a new type of
platform-based and gamified online learning that reaches high acceptance for teaching
purposes. However, the evaluation also reveals some issues for improvement. Besides that,
another evaluation focusing on learners’ needs will be conducted as a next step in order to
examine learners’ attitudes towards the LMS and this specific way of learning. After that,
more studies can follow which should be conducted in different subject areas, but at the
same time using comparable designs of gamified learning arrangements.
References
Bartel, A., Hagel, G., & Wolff, C. (2017). Effective Integration of Gamification and
Learning Management Systems for Creating Gamified Learning Arrangements. In J.
Domenech, C. M. Vicent-Vela, E. de La Poza, & D. Blazquez (Eds.), Proceedings of
the 3rd International Conference on Higher Education Advances (pp. 679–686).
Bartel, A., & Hagel, G. (2014). Engaging Students With a Mobile Game-Based Learning
System in University Education. International Journal of Interactive Mobile
Technologies, 8(4), 56–60.
Bartel, A., & Hagel, G. (2016). Gamified Just-in-Time Teaching - A Conceptual Approach
Based on Best Practices. In G. Hagel & J. Mottok (Eds.), Proceedings of ECSEE 2016 -
European Conference Software Engineering Education (pp. 1–17). Aachen: Shaker.
Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to
gamefulness: defining gamification. In A. Lugmayr, H. Franssila, C. Safran, & I.
Hammouda (Eds.), Proceedings of the 15th International Academic MindTrek
Conference: Envisioning Future Media Environments (pp. 9–15).
Dicheva, D., & Dichev, C. (2016). An Active Learning Model Employing Flipped Learning
and Gamification Strategies. In Proceedings of first Int. Workshop on Intelligent
Mentoring Systems (IMS 2016), Zagreb, Croatia (pp. 1–6).
Dicheva, D., Irwin, K., Dichev, C., & Talasila, S. (2014). A course gamification platform
supporting student motivation and engagement. In 2014 International Conference on
Web & Open Access to Learning (ICWOAL) (pp. 1–4). Piscataway, NJ: IEEE.
Hakulinen, L., Auvinen, T., & Korhonen, A. (2015). The Effect of Achievement Badges on
Students’ Behavior: An Empirical Study in a University-Level Computer Science
Course. International Journal of Emerging Technologies in Learning (iJET), 10(1), 18-
29.
619
Emendo – A Toolchain for Creating Gamified Learning Arrangements for Online Learning Settings
Hasegawa, T., Koshino, M., & Ban, H. (2015). An English vocabulary learning support
system for the learner's sustainable motivation. SpringerPlus, 4(99).
Ibanez, M., Di Serio, A., & Delgado Kloos, C. (2014). Gamification for Engaging
Computer Science Students in Learning Activities: A Case Study. IEEE Transactions
on Learning Technologies, 7(3), 291–301.
Kelly, S., & Tolvanen, J.-P. (2008). Domain-specific modeling: Enabling full code
generation. Hoboken, N.J.: John Wiley & Sons.
Nah, F. F.-H., Telaprolu, V. R., Rallapalli, S., & Venkata, P. R. (2013). Gamification of
Education Using Computer Games. In S. Yamamoto (Ed.), Lecture Notes in Computer
Science. Human Interface and the Management of Information. Information and
Interaction for Learning, Culture, Collaboration and Business (Vol. 8018, pp. 99–107).
Springer Berlin Heidelberg.
Nah, F. F.-H., Zeng, Q., Telaprolu, V. R., Ayyappa, A. P., & Eschenbrenner, B. (2014).
Gamification of Education: A Review of Literature. In F. F.-H. Nah (Ed.), HCI in
Business: First International Conference, HCIB 2014, Heraklion, Crete, Greece, June
22-27, 2014. Proceedings (pp. 401–409). Cham: Springer.
Nicholson, S. (2015). A RECIPE for Meaningful Gamification. In T. Reiners & L. C.
Wood (Eds.), Gamification in Education and Business (pp. 1–20). Cham: Springer
International Publishing.
Roderus, S. (2015). Ein Kurskonzept zur Förderung des kontinuierlichen Lernens durch den
Einsatz von Gamification. In Zentrum für Hochschuldidaktik (Ed.), Tagungsband zum
2. HDMINT Symposium 2015 (pp. 81–86).
Ryan, R. M., & Deci, E. L. (2000). Self-Determination Theory and the Facilitation of
Intrinsic Motivation, Social Development, and Well-Being. American Psychologist,
55(1), 68–78.
Scheele, B., & Groeben, N. (1988). Dialog-Konsens-Methoden zur Rekonstruktion
subjektiver Theorien: D. Heidelberger Struktur-Lege-Technik (SLT), konsensuale Ziel-
Mittel- Argumentation u. kommunikative Flußdiagramm-Beschreibung von
Handlungen. Tübingen: Francke.
Smolka, D. (2004). Schülermotivation: Konzepte und Anregungen für die Praxis (2.,
durchges. Aufl). München, Neuwied: Luchterhand.
Werbach, K., & Hunter, D. (2015). The Gamification Toolkit: Dynamics, Mechanics, and
Components for the Win. New York: Wharton Digital Press.
620
