HCI International 2019 – Late Breaking Posters by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9783030307127
Publisher: Springer International Publishing

Self-explanationAdaptive learning environmentVideo games

1 Introduction

Video games have the potential to improve learning, but the multimedia complexity of games can make it difficult to capture that learning [4, 7, 14, 21]. There is a growing body of research demonstrating that certain game features, introduced into well-designed video games [11, 12, 19, 24] or multi-media simulations [6, 10, 20], improve learning. One method for managing a multi-media learning environment is to couple it with an intelligent tutoring system (ITS) that tailors the student learning experience based on a player’s initial knowledge of a phenomenon, and in-task performance [8, 26, 27]. ITSs have been used mainly in math and physics domains, and few have been implemented in a video game [1, 8, 12]. Van Lehn describes a set of alternatives for improving learning that works in human tutoring, but has yet to be fully examined in the ITS literature [23]. One such example is introducing self-reflection or self-explanation into a learning environment.

In this paper, we analyze a set of open-ended hints left by players for themselves and future players, and make some recommendations for using hints in a serious game. Our analysis contributes to the ITS and self-explanation research in two ways. First, based on our literature review, it is one of the few studies on self-explanation, generated by players, in a serious video game. Given the dynamic nature of games, if this approach is useful it could contribute to playtesting methodology and game design. Second, it examines self-explanation in a new context (i.e., inferential reasoning) [16].

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