Learning analytics approaches show promise for supporting study success and identifying students at risk of dropping out, but rigorous large-scale evidence of effectiveness is still lacking¶
Claim · All claims
Evidence · 1 study · reviewr3·q2
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? A systematic review of 46 key publications finds a considerable number of learning analytics approaches utilising effective techniques to support study success and students at risk of dropping out, yet rigorous large-scale evidence of effectiveness is lacking. → Dirk Ifenthaler 2020
Evidence¶
Dirk Ifenthaler 2020¶
Dirk Ifenthaler, Jane Yin-Kim Yau. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Education Tech Research Dev. https://doi.org/10.1007/s11423-020-09788-z
q2 · i? · review · r3
Systematic review following eight standardised steps; an initial set of 6220 articles was identified and the final sample includes 46 key publications. The review reports promise but states that "rigorous, large-scale evidence of the effectiveness of learning analytics in supporting study success is still lacking".
"The findings obtained in this systematic review suggest that there are a considerable number of learning analytics approaches which utilise effective techniques in supporting study success and students at risk of dropping out. However, rigorous, large-scale evidence of the effectiveness of learning analytics in supporting study success is still lacking."
Discussion¶
Related Claims¶
- None of the 46 key publications on learning analytics for study success were rated as strong research rigour (11 weak; 35 moderate) — a narrower finding that bears on this claim
- The evidence base does not yet provide a menu of program options for helping students at risk of dropping out, and program developers need a way to identify approaches while stronger scientific evidence is developed — related
- Large-scale studies regarding the effectiveness of learning analytics are still lacking — possibly the same claim (merge candidate)
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
la-study-success-evidence-lacking |
title |
Learning analytics approaches show promise for supporting study success and identifying students at risk of dropping out, but rigorous large-scale evidence of effectiveness is still lacking |
description |
Learning analytics approaches show promise for supporting study success and identifying students at risk of dropping out, but rigorous large-scale evidence of effectiveness is still lacking |
status |
review |
evidence_strength |
weak |
newest_evidence |
2020 |
generated |
by process:wiki-ingest on 2026-10-29 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — dirk-ifenthaler-2020 |
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