As instruction shifts away from traditional approaches, online learning has grown in popularity in K-12 and higher education. Artificial intelligence (AI) and learning analytics methods such as machine learning have been used by educational scholars to support online learners on a large scale. However, the fairness of AI prediction in educational…

This study reviewed papers in the Web of Science database from 2010 to 2020, which were relevant to the integration of the dynamic geometric software, GeoGebra, into mathematics education with a focus on publication trends, research methods, participants, application domains, learning strategies, and research issues. It was found that there have…

The topic of inequalities is one of the fundamental subject areas for the development of mathematical knowledge. Although there is a considerable body of research focused on one-variable inequalities, studies that investigate students' performance on two-variable inequalities are scarce. With this in mind, the aim of this study is twofold: first,…

The authors described the influence of the GeoGebra based environment on students' achievements in the field of functions with parameters, during collaborative learning. Functions with parameters are important because of their application in science. Students had to choose different values for parameters and to examine the properties of the…

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)…