A Systematic Review of Learning Analytics-Supported Feedback Practices in K-12 Education

• In Event: AERA Roundtable Session Thursday 2:15 pm - Gold 2
  In Roundtable Session: Systematic Reviews on Technology-Enhanced Learning and Educational Practices

Abstract

This systematic review examines learning analytics (LA)-supported feedback in K-12 education by analyzing 36 peer-reviewed journal articles. Findings reveal that LA-supported feedback is predominantly applied in STEM subjects, targets learning performance or engagement, and relies on short-term, cognitive data (e.g., task-related) sourced from log files and assessments. Feedback tends to be descriptive or diagnostic, using data aggregation or mining to present scores or visualizations. Few studies incorporate affective or psychomotor data, or feedback that promotes self-regulation. This review highlights the need for expanded research on long-term learning trajectories, non-STEM subjects, and advanced feedback types—shifting from descriptive to predictive and prescriptive forms, and from task- and process-level to self- and self-regulation-level feedback in K-12 contexts.

Authors

• Chaeyeon Kim, University of Wisconsin - Madison

• Jewoong Moon, University of Alabama

• Jieun Lim, Daegu National University of Education