Using Engage E-Text Data for Modeling Student Engagement

Instructional activity data from digital learning environments (DLEs) enable educators and researchers to gain a better understanding of student engagement. Course-level analytics in the Engage e-text reader allow instructors to monitor students' engagement with assigned readings and diagnose students' needs for remediation. Institutionally, DLEs data can go beyond descriptive reports through explanations engagement and achievement as a function of other determinants. In this presentation, researchers from Indiana University will discuss their experience in processing, analyzing, visualizing, and interpreting the Engage data. This presentation seeks to inform researchers and institutions on possible approaches for developing analytics from DLE data.

Outcomes: Explore the challenges and opportunities for analytics with data from e-texts and data from other DLE *Explore and discuss the development of analytics for e-texts and other data from DLEs *Explore the practical approaches for understanding student engagement from e-text and other DLE analytics