Game learning analytics for understanding reading skills in transparent writing system
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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
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British Journal of Educational TechnologyAuthors
Date
2020Copyright
© 2020 British Educational Research Association
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.
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Wiley-BlackwellISSN Search the Publication Forum
0007-1013Keywords
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https://converis.jyu.fi/converis/portal/detail/Publication/34656136
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Research Council of Finland; Foundation BotnarFunding program(s)
Academy Programme, AoF; Research profiles, AoF; OthersAdditional information about funding
This study was supported by a grant from the Academy of Finland for the Unesco professor Heikki Lyytinen (decision numbers 292493 and 311737), the professor Tommi Kärkkäinen (decision numbers 311877 and 315550), and the professor Ulla Richardson (decision number 274050). The study was also supported by a grant from the Foundation Botnar for the professor Ulla Richardson (decision number 6066). All the authors gratefully acknowledge the postdoctoral researcher Harri Ketamo for the valuable discussions related to serious games and data analytics. ...License
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