A Systematic Literature Review on Adaptive Supports in Serious Games for Programming

Abstract

This paper reviews the research on adaptive serious games for programming regarding the implementation of their support systems. Serious games are designed to educate players in an entertaining and engaging manner. A key element in terms of meeting their educational goals is the presentation of the learning content through a support system. Recent developments in artificial intelligence, data analysis, and computing made the development of support systems that adapt to player individual characteristics possible. A systematic literature review is necessary to evaluate the efficiency of adaptive supports and examine the implementation approaches. This review identified 18 papers reporting evidence about the efficiency of the provided support and methods of development. A variety of techniques for presenting educational content was found, with text being the preferred type. Researchers employed data-driven approaches to model student knowledge levels and behavior such as Bayesian networks and questionnaires, with fuzzy logic being utilized most frequently. The efficiency of the supports, when compared with non-adaptive or traditional methods of teaching, was mostly positive, although this is not a decisive conclusion. Some papers did not provide empirical evidence or concluded no difference in efficiency. The limited number of articles in the field, together with the lack of a standard evaluation methodology, leads to the conclusion that further work needs to be carried out in the area.