A1 Journal article (refereed)
Game learning analytics for understanding reading skills in transparent writing system (2020)


Niemelä, M., Äyrämö, S., Ronimus, M., Richardson, U., & Lyytinen, H. (2020). Game learning analytics for understanding reading skills in transparent writing system. British Journal of Educational Technology, 51(6), 2376-2390. https://doi.org/10.1111/bjet.12916


JYU authors or editors


Publication details

All authors or editors: Niemelä, Marko, Kärkkäinen, Tommi; Äyrämö, Sami; Ronimus, Miia; Richardson, Ulla; Lyytinen, Heikki

Journal or series: British Journal of Educational Technology

ISSN: 0007-1013

eISSN: 1467-8535

Publication year: 2020

Volume: 51

Issue number: 6

Pages range: 2376-2390

Publisher: Wiley-Blackwell

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1111/bjet.12916

Publication open access: Not open

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/67896


Abstract

Serious games are designed to improve learning instead of providing only entertainment. Serious games analytics can be used for understanding and enhancing the quality of learning with serious games. One challenge in developing computerized support for learning is that learning of skills varies between players. Appropriate algorithms are needed for analyzing the performance of individual players. This paper presents a novel clustering-based profiling method for analyzing serious games learners. GraphoLearn, a game for training connections between speech sounds and letters, serves as the game-based learning environment. The proposed clustering method was designed to group the learners into profiles based on game log data.

The obtained profiles were statistically analyzed. For instance, the results revealed one profile consisting of 136 players who had difficulties with connecting most of the target sounds and letters, whereas learners in the other profiles typically had difficulties with specific sound-letter pairs. The results suggest that this profiling method can be useful for identifying children with a risk of reading disability and the proposed approach is a promising new method for analyzing serious game log data.


Keywords: computer-assisted learning; learning difficulties; reading disorders; educational games; serious games

Free keywords: learning analytics; serious games; letter knowledge; reading difficulties; GraphoLearn


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Related projects


Ministry reporting: Yes

Reporting Year: 2020

JUFO rating: 2


Last updated on 2024-22-04 at 13:18