Computational analysis methods and machine learning techniques introduce innovative ways to capture classroom interactions and display data on analytics dashboards. Automated classroom analytics employ advanced data analysis, providing educators with comprehensive insights into student participation, engagement, and behavioral trends within…

The purpose of this case study is to demonstrate how to utilize machine learning approaches to analyze student process data for validating and informing digital game-based assessments (DGBAs) with an evidence-centered game design (ECgD). The first analysis was conducted to examine whether students' mastery of the overall skill required by the game…

Purpose: The digitalization of society results in challenges and opportunities for learning and education. This paper describes exemplary transformations from current to future practices. It illustrates multi-dimensional aspects of learning which complement and transcend current frameworks of learning focused on schools. While digital technologies…

Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…