Adverse effects of personalized automated feedback

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
21 Downloads (Pure)


In large classes with hundreds of students, it is rarely feasible to provide students with individual feedback on their performance. Automatically generated personalized feedback on students' performance might help to overcome this issue, but available empirical effect studies are inconclusive due to lack of methodological rigor. This study uses a repetitive randomized control experiment to explore whether automatically generated feedback is effective and for which students. Our results indicate that feedback does not have a positive effect on performance for all students. Some groups benefit from receiving personalized feedback, while others do not perform better than the control group. Students that perform average benefit most from receiving personalized feedback. However, lower-scoring students who received feedback tend to have lower attrition rates and if they participate at the final exam, their performance is not higher than the control group. Therefore, providing automated feedback is not something that should be undertaken mindlessly.

Original languageEnglish
Title of host publicationHEAd 2023 - 9th International Conference on Higher Education Advances
PublisherUniversidad Politecnica de Valencia
Number of pages6
ISBN (Electronic)9788413960852
Publication statusPublished - 2023
Event9th International Conference on Higher Education Advances, HEAd 2023 - Valencia, Spain
Duration: 19-Jun-202322-Jun-2023

Publication series

NameInternational Conference on Higher Education Advances
ISSN (Electronic)2603-5871


Conference9th International Conference on Higher Education Advances, HEAd 2023


  • adverse effects
  • Automated feedback
  • empirical study
  • randomized control experiment
  • summative assessment


Dive into the research topics of 'Adverse effects of personalized automated feedback'. Together they form a unique fingerprint.

Cite this