This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…

In this study, we investigated effects of the proportion of language minority students in classrooms on the development of students' intrinsic motivation in language lessons and the mediating role of instructional climate (e.g., teacher support, focus on student interests). In addition, we explored the interaction between the proportion of…

Recently, there is a growing interest in the automatic analysis of learner activity in web-based learning environments. The approach and system SIAM (System for Interaction Analysis by Machine learning) presented in this article aims at helping to establish a basis for the automatic analysis of interaction data by developing a data logging and…