A Proof-of-Concept Study of Game-Based Learning in Higher Education

Author:

Crocco Francesco1,Offenholley Kathleen1,Hernandez Carlos1

Affiliation:

1. City University of New York, USA

Abstract

Background. Much literature has theorized on the potential educational benefits offered by game-based learning (GBL). However, recent meta-data analyses of studies conducted on the efficacy of GBL offer mixed results. Furthermore, many of the studies available rely more on close reading, inference, small sample sizes, and qualitative responses than on quantitative, data-driven analyses. Aim. This article describes a proof-of-concept study designed to assess the effects of GBL on enjoyment, engagement, and learning in higher education using a large sample size and quantitative measures. Method. The study uses a large data set (n = 440) involving English, Math and Science undergraduate courses. For the first semester, faculty participants were trained in how to implement game-based pedagogy and created analog game-based lessons. In the following semester, each professor taught one section of a course using games and another section of the same course without games. Students in the game-based and control groups were given attitude surveys about the subject at the beginning of the semester, a post-lesson survey after the game or regular lesson, and a post-lesson quiz with separate questions to assess surface learning and deep learning. Results. Enjoyment correlated with improvements in deep learning in both the game and non-game classes. Games increased reported enjoyment levels, especially in subjects where students reported the greatest anxiety about learning, and this increase in enjoyment correlated positively with improvements in deep learning and higher-order thinking. These results may have particular impact on non-traditional students. Conclusion. While further investigation is necessary to assess the specific affordances and long-term effects of GBL in higher education, this study offers preliminary support for the claim that GBL can improve deep learning in this setting, by increasing enjoyment.

Publisher

SAGE Publications

Subject

Computer Science Applications,General Social Sciences

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