Using Engage E-Text Data for Modeling Student Engagement

Tuesday, February 14 | 10:00AM–10:45AM | Houston Ballroom Foyer
Session Type: Poster Session
Delivery Format: Poster Session
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


  • Serdar Abaci

    Educational Research and Evaluation Specialist, Indiana University
  • Anastasia Morrone

    Dean, Indiana University Bloomington
  • Josh Quick

    Learning Data Analyst, Indiana University

Resources & Downloads

  • Using Engage EText Data for Modeling Student Engagement

    282 KB, pdf - Updated on 1/26/2024