On the CASED challenge test set, all participating engagement-prediction methods converge near random-chance performance, with the best F1 Macro at 0.52¶
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Evidence · 1 study · designr2·q2
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q2 i? All participating methods on the CASED classification and regression tracks perform near random chance, with the best method reaching F1 Macro 0.52 and all submissions obtaining near-zero or negative R2, Pearson, and CCC in regression. → leaderboard-1
Evidence¶
leaderboard-1¶
Alperen Kantarcı, Visvanathan Ramesh, and Gemma Roig. 2026. Mind the Student: Behavioral and Contextual Cues for Automated Engagement Prediction in Online Learning. ICMI '26, Napoli, Italy. https://doi.org/10.1145/3776574.3832485
q2 · i? · design · r2
Official CASED challenge leaderboard results (Tables 1 and 2) reported by the authors. In regression, "all submissions obtained near-zero or negative values for 𝑅2, Pearson correlation, and CCC", indicating no method reliably captured the engagement signal.
"Best-performing method obtained a F1 Macro of 0.52, suggesting that all approaches face with similar limitations imposed by the dataset and the task."
Discussion¶
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Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
cased-challenge-methods-near-random-chance |
title |
On the CASED challenge test set, all participating engagement-prediction methods converge near random-chance performance, with the best F1 Macro at 0.52 |
description |
On the CASED challenge test set, all participating engagement-prediction methods converge near random-chance performance, with the best F1 Macro at 0.52 |
status |
review |
evidence_strength |
moderate |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — leaderboard-1 |
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