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PEGAM – a Personalized Gamification design Model for programming language e-courses


This dissertation addresses decreased academic participation, low engagement and poor experience as issues often related to students’ retention in online learning courses. The issues were identified at the Department of Computer Science at RWTH Aachen University, Germany, although high dropout rates are a growing problem in Computer Science studies worldwide.

A solving approach often used in addressing the before mentioned problems includes gamification and personalization techniques: Gamification is a process of applying game design principles in serious contexts (i.e., learning), while personalization refers to tailoring the context to users’ needs and characteristics. In this work, the two techniques are used in combination in the Personalized Gamification Model (PeGaM), created for designing an online course for learning programming languages.

PeGaM is theoretically grounded in the principles of the Gamified Learning Theory and the theory of learning tendencies. Learning tendencies define learners’ preferences for a particular form of behavior, and those behaviors are seen as possible moderators of gamification success. Moderators are a concept explained in the Gamified Learning Theory, and refer to variables that can influence the impact of gamification on the targeted outcomes. Gamification success is a measure of the extent to which students behave in a manner that leads to successful learning. The conceptual model of PeGaM is an iterative process in which learning tendencies are used to identify students who are believed to be prone to avoid certain activities. Gamification is then incorporated in activities that are recognized as ‘likely to be avoided’ to produce a specific learning-related behavior responsible for a particular learning outcome. PeGaM model includes five conceptual steps and 19 design principles required for gamification of learning environments that facilitate student engagement, participation and experience.

In practice, PeGaM was applied in an introductory JavaScript course with Bachelor students of Computer Science at RWTH Aachen University. The investigation was guided by the principles of the Design-Based Research approach. Through this approach, PeGaM was created, evaluated and revised, over three iterative cycles. The first cycle had an explorative character, included one control and one treatment group, and gathered 124 participants. The second and third cycle were experimental studies, in which 69 and 171 participants were randomly distributed along one control and two treatment groups. Through the three interventions, mixed methods were used to capture students’ academic participation (a measure of students’ online behavior in the course collected through activity logs), engagement (evaluated quantitatively through a questionnaire compiled to measure behavioral, emotional, and cognitive engagement), and gameful experience (quantitative measure of students’ experience with the gamified system). In addition, supporting data was collected through semi-structured interviews and open-ended survey questions.

The empirical findings revealed that gamification with PeGaM contributes to learning outcomes and that the success of gamification is conditioned by the applicability of game elements with learners’ preferences and learning activities. Cross case comparisons supported the application 4 of PeGaM design principles and demonstrated its potential. Even though limited support was found to confirm the moderating role of learners’ learning tendencies, the study demonstrated that the gamification of learning activities that students are likely to avoid can increase their participation - but must be carefully designed. Most importantly, it has been shown that educational gamification can support and enhance learning-related behavior but require relevant and meaningful learning activities in combination with carefully considered reward, collaborative and feedback mechanisms.

The study provides practical and theoretical insights but also highlights challenges and limitations associated with personalized gamification thus offers suggestions for further investigation.