A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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-tekijät tai -toimittajat


Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajatNiemelä, Marko, Kärkkäinen, Tommi; Äyrämö, Sami; Ronimus, Miia; Richardson, Ulla; Lyytinen, Heikki

Lehti tai sarjaBritish Journal of Educational Technology

ISSN0007-1013

eISSN1467-8535

Julkaisuvuosi2020

Volyymi51

Lehden numero6

Artikkelin sivunumerot2376-2390

KustantajaWiley-Blackwell

JulkaisumaaBritannia

Julkaisun kielienglanti

DOIhttps://doi.org/10.1111/bjet.12916

Julkaisun avoin saatavuusEi avoin

Julkaisukanavan avoin saatavuus

Julkaisu on rinnakkaistallennettu (JYX)https://jyx.jyu.fi/handle/123456789/67896


Tiivistelmä

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.


YSO-asiasanattietokoneavusteinen oppiminenoppimisvaikeudetlukihäiriötoppimispelithyötypelit

Vapaat asiasanatGraphoLearn


Liittyvät organisaatiot


Hankkeet, joissa julkaisu on tehty


OKM-raportointiKyllä

Raportointivuosi2020

JUFO-taso2


Viimeisin päivitys 2024-03-04 klo 21:17