mlsanityData to 14 Oct 2026

Learning Outcomes, Assessment, and Evaluation in Educational Recommender Systems: A Systematic Review

arXiv 2407.09500 ↗First posted 12 Jun 2024cs.HC cs.IRcited by 1

Not on the map. Why?

Abstract (arXiv)

In this paper, we analyse how learning is measured and optimized in Educational Recommender Systems (ERS). In particular, we examine the target metrics and evaluation methods used in the existing ERS research, with a particular focus on the pedagogical effect of recommendations. While conducting this systematic literature review (SLR), we identified 1395 potentially relevant papers, then filtered them through the inclusion and exclusion criteria, and finally selected and analyzed 28 relevant papers. Rating-based relevance is the most popular target metric, while less than a half of papers optimize learning-based metrics. Only a third of the papers used outcome-based assessment to measure the pedagogical effect of recommendations, mostly within a formal university course. This indicates a gap in ERS research with respect to assessing the pedagogical effect of recommendations at scale and in informal education settings.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 12 Jun 2024.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.