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An application of adaptive games-based learning based on learning style to teach SQL
ARTICLE

, , , University of the West of Scotland, United Kingdom

Computers & Education Volume 86, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd

Abstract

The fact that each student has a different way of learning and processing information has long been recognised by educationalists. In the classroom, the benefits derived from delivering learning content in ways that match the student's learning style have also been identified. As new modes of delivery of learning content such as computer-assisted learning systems (e.g. eLearning) have become increasingly popular, research into these has also identified the benefits of tailoring learning content to learning styles. However, in games-based learning (GBL), the adaptation based on learning style to enhance the educational experience has not been well researched. For the purpose of this research, a game with three game modes has been developed: 1) non-adaptivity mode; 2) a mode that customises the game according to the student's learning style identified by using a learning style questionnaire; and 3) a mode that has an in-game adaptive system that dynamically and continuously adapts its content according to the student's interactions in the game.This paper discusses the term adaptivity in a GBL context and presents the results of an experimental study investigating the differences in learning effectiveness of the different game modes compared to a paper-based learning. The study was performed with 120 Higher Education students learning the database language SQL (Structured Query Language). The results show that the game developed, regardless of mode, produced better learning outcomes than those who learned from a textbook while adaptive GBL was better in terms of allowing learners to complete the tasks faster than the other two game versions.

Citation

Soflano, M., Connolly, T.M. & Hainey, T. (2015). An application of adaptive games-based learning based on learning style to teach SQL. Computers & Education, 86(1), 192-211. Elsevier Ltd. Retrieved September 18, 2019 from .

This record was imported from Computers & Education on January 29, 2019. Computers & Education is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.compedu.2015.03.015

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