RT Journal Article
T1 Applications of data science to game learning analytics data: A systematic literature review
A1 Alonso Fernández, Cristina
A1 Calvo Morata, Antonio
A1 Freire Morán, Manuel
A1 Martínez Ortiz, Iván
A1 Fernández Manjón, Baltasar
AB Data science techniques, nowadays widespread across all fields, can also be applied to the wealth of information derived from student interactions with serious games. Use of data science techniques can greatly improve the evaluation of games, and allow both teachers and institutions to make evidence-based decisions. This can increase both teacher and institutional confidence regarding the use of serious games in formal education, greatly raising their attractiveness. This paper presents a systematic literature review on how authors haveapplied data science techniques on game analytics data and learning analytics data from serious games to determine: (1) the purposes for which data science has been applied to game learning analytics data, (2) which algorithms or analysis techniques are commonly used, (3) which stakeholders have been chosen to benefit from this information and (4) which results and conclusions have been drawn from these applications. Based on the categories established after the mapping and the findings of the review, we discuss the limitations of the studiesanalyzed and propose recommendations for future research in this field.
SN 0360-1315
YR 2019
FD 2019-11
LK https://hdl.handle.net/20.500.14352/99560
UL https://hdl.handle.net/20.500.14352/99560
LA eng
DS Docta Complutense
RD 10 abr 2025