02073nas a2200289   4500000000100000000000100001008004100002260001200043653002300055653001400078653001600092653001000108653002200118100001600140700001600156700001700172700001600189700001800205700002000223700001200243245009900255856008200354300001200436490000600448520131500454022001401769       2021                            d  c12/202110aLearning Analytics10aEducation10aData Mining10aGames10aLiterature Review1 aAhmed Tlili1 aMaiga Chang1 aJewoong Moon1 aZhichun Liu1 aDaniel Burgos1 aNian-Shing Chen1 aKinshuk00aA Systematic Literature Review of Empirical Studies on Learning Analytics in Educational Games  uhttps://www.ijimai.org/journal/sites/default/files/2021-11/ijimai7_2_22_0.pdf  a250-2610 v73 aLearning analytics (LA) in educational games is considered an emerging practice due to its potential of enhancing the learning process. Growing research on formative assessment has shed light on the ways in which students' meaningful and in-situ learning experiences can be supported through educational games. To understand learners' playful experiences during gameplay, researchers have applied LA, which focuses on understanding students' in-game behaviour trajectories and personal learning needs during play. However, there is a lack of studies exploring how further research on LA in educational games can be conducted. Only a few analyses have discussed how LA has been designed, integrated, and implemented in educational games. Accordingly, this systematic literature review examined how LA in educational games has evolved. The study findings suggest that: (1) there is an increasing need to consider factors such as student modelling, iterative game design and personalisation when designing and implementing LA through educational games; and (2) the use of LA creates
several challenges from technical, data management and ethical perspectives. In addition to outlining these findings, this article offers important notes for practitioners, and discusses the implications of the study’s results.  a1989-1660