Adaptive serious games for computer science education

Serious games have the potential to effectively engage students to learn, however, these games tend to struggle accommodating learners with diverse abilities and needs. Furthermore, customizing a serious game to the individual learner has historically required a great deal of effort on the part of subject matter experts, and is not always feasible for increasingly complex games. This thesis proposes the use of automatic methods to adapt serious programming games to learners' abilities. To understand the context of the problem, a survey was conducted of the serious programming game literature, which found that while many games exist, there has been very little consideration for the use of adaptation. Given the breadth of the existing serious programming game literature, a methodology was developed to support adaptation of existing games. To demonstrate the efficacy of this adaptive methodology in serious programming games, two case studies were conducted: 1) a study comparing adaptive and non-adaptive gameplay in the Gidget game, and 2) a study assessing non-adaptive gameplay, adaptive gameplay, and adaptive hints in the RoboBug game. The results from both case studies provide evidence to the need for adaptation in serious programming games, and illustrate how the adaptive methodology can be utilized to positively affect the engagement of learners and their ability to achieve learning outcomes.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Miljanovic, Michael A.

Advisor dc:contributor.advisor

• Bradbury, Jeremy

• Adaptation
• Programming
• Education
• Serious games

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/1262

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/1262