Brett, J., Gatzidis, C., Davis, T., Amelidis, P., Xu, N. and Gladwell, T., 2021. Learning through Play; A Study Investigating How Effective Video Games Can Be Regarding Keyboard Education at a Beginner Level. In: FDG'21: The 16th International Conference on the Foundations of Digital Games, 2-7 August 2021.
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Abstract
This paper describes the development of a set of video games designed to reduce the high drop-off rates associated with learning to play the keyboard by gamifying rote tasks that require monotonous practice. By defining our own understanding of what musicianship is and creating a custom framework for assessment through the use of existing curriculums and learning applications, we have chosen specific areas which require the most rote learning, are critical to developing motor skills and to building an understanding of music; these include learning and practicing musical scales, keeping in time with tempo and the basics of hand coordination and fingering styles. We developed solutions which offer a new way for learners to practice in an engaging and entertaining way with the aim to reduce the drop-off rates and lower the barrier for entry to learning keyboard. Developing games requires an iterative process of development, testing, isolating key issues and solving them through further development. Therefore, through a pilot study (using observations, screen recordings and semi-structured interviews as data collection methods), we have observed that whilst this novel method of learning and practicing using video games is positively accepted by learners and teachers alike, the games themselves and the process of validation requires refinement in order to truly gauge each game relating to engagement, motivation and educational benefit. This paper describes the findings of this pilot study regarding the improvements and changes of each developed game as well how to improve future user studies.
Item Type: | Conference or Workshop Item (Paper) |
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Group: | Faculty of Media & Communication |
ID Code: | 36231 |
Deposited By: | Symplectic RT2 |
Deposited On: | 09 Nov 2021 14:16 |
Last Modified: | 14 Mar 2022 14:30 |
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