Optimizing challenge in an educational game using large-scale design experiments

Conference paper (2013)

Authors

J.D. Lomas Carnegie Mellon University
Kishan Patel Dhirubhai Ambani Institute of Information and Communication Technology
Jodi Forlizzi Carnegie Mellon University
Kenneth R. Koedinger Carnegie Mellon University
Affiliation
External organisation
More Info
expand_more

Published Date

2013

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Affiliation

External organisation

Abstract

Online games can serve as research instruments to explore the effects of game design elements on motivation and learning. In our research, we manipulated the design of an online math game to investigate the effect of challenge on player motivation and learning. To test the "Inverted-U Hypothesis", which predicts that maximum game engagement will occur with moderate challenge, we produced two large-scale (10K and 70K subjects), multifactor (2x3 and 2x9x8x4x25) online experiments. We found that, in almost all cases, subjects were more engaged and played longer when the game was easier, which seems to contradict the generality of the Inverted-U Hypothesis. Troublingly, we also found that the most engaging design conditions produced the slowest rates of learning. Based on our findings, we describe several design implications that may increase challenge-seeking in games, such as providing feedforward about the anticipated degree of challenge.