Content area
Quality feedback is essential for supporting student learning in higher education, yet personalized feedback at scale remains costly. Advances in learning analytics and artificial intelligence now enable the automated delivery of personalized feedback to many students simultaneously. At the same time, recent feedback research increasingly emphasizes learner-centered approaches, particularly the role of feedback literacy—students' varying capacities to engage with and benefit from feedback. Despite growing interest, few studies have quantified how feedback literacy affects students' perceptions of feedback, especially in technology-supported contexts. To address this, we examined (1) students' perceptions of personalized, detailed feedback generated via learning analytics and (2) how feedback literacy moderated these perceptions. In a randomized field experiment, teacher education students (N = 196) participated in a week-long computer-supported collaborative learning task on cognitive activation in the classroom. Both groups received automated, personalized feedback: the control group received basic feedback on task completion, while the experimental group received detailed feedback on group processes and the quality of their collaborative statement. The highly informative feedback significantly improved perceptions of feedback helpfulness, enhanced learning insights, and supported self-reflection and self-regulation. Feedback literacy partially moderated these effects, influencing perceptions of feedback helpfulness and motivational regulation.
Details
Incentives;
Literature Reviews;
Error Correction;
Influence of Technology;
Attention Span;
Learning Processes;
Academic Achievement;
Researchers;
Learning Theories;
Literacy;
Cooperative Learning;
Meta Analysis;
Motivation;
Intelligence;
Electronic Learning;
Individual Differences;
Formative Evaluation;
Automation;
Emotional Response;
Teacher Education;
Learner Engagement;
Higher Education;
Programming
Feedback;
Literacy;
Teacher education;
Student attitudes;
Collaborative virtual environments;
Educational technology;
Automation;
Cognitive tasks;
Distance learning;
Customization;
Students;
Motivation;
Perceptions;
Artificial intelligence;
Learning analytics;
Collaborative learning;
Helping behavior;
Collaboration;
Student teacher relationship;
Self control;
Teachers;
Learning;
Task completion;
Student-centered learning;
Cooperative learning;
Selfreflection;
Group processes;
Educational activities;
Self regulation;
Regulation;
Groups;
Classrooms
; Fink, Aron 2 ; Frey, Andreas 2 ; Jivet, Ioana 3 ; Gombert, Sebastian 4 ; Menzel, Lukas 2 ; Giorgashvili, Tornike 2 ; Yau, Jane 4 ; Drachsler, Hendrik 5 1 University of Zurich, Zurich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650); Zurich University of Teacher Education, Zurich, Switzerland (GRID:grid.483054.e) (ISNI:0000 0000 9666 1858); DIPF – Leibniz Institute for Research and Information in Education, Frankfurt am Main, Germany (GRID:grid.461683.e) (ISNI:0000 0001 2109 1122)
2 Goethe University Frankfurt, Frankfurt am Main, Germany (GRID:grid.7839.5) (ISNI:0000 0004 1936 9721)
3 DIPF – Leibniz Institute for Research and Information in Education, Frankfurt am Main, Germany (GRID:grid.461683.e) (ISNI:0000 0001 2109 1122); Goethe University Frankfurt, Frankfurt am Main, Germany (GRID:grid.7839.5) (ISNI:0000 0004 1936 9721); FernUniversität in Hagen, Hagen, Germany (GRID:grid.31730.36) (ISNI:0000 0001 1534 0348)
4 DIPF – Leibniz Institute for Research and Information in Education, Frankfurt am Main, Germany (GRID:grid.461683.e) (ISNI:0000 0001 2109 1122)
5 DIPF – Leibniz Institute for Research and Information in Education, Frankfurt am Main, Germany (GRID:grid.461683.e) (ISNI:0000 0001 2109 1122); Goethe University Frankfurt, Frankfurt am Main, Germany (GRID:grid.7839.5) (ISNI:0000 0004 1936 9721); Open University of the Netherlands, Heerlen, The Netherlands (GRID:grid.36120.36) (ISNI:0000 0004 0501 5439)