Individualised counterfactual inferences estimate whether a specific student would have performed differently under different help conditions¶
Claim · All claims
Evidence · 1 study · designr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly
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? For a student who solved Q5 at the 2D level with scheme help, the counterfactual probability of solving Q5 at 2D without help is one; for Q12 solved at 1D with scheme help, the counterfactual probability of reaching 2D with feedback help is between 0 and 0.76, indicating uncertainty. → Francesca Mangili 2026
Evidence¶
Francesca Mangili 2026¶
Francesca Mangili, Alessandro Antonucci, Rafael Cabañas de Paz. (2026). Causal Modelling of Support Interventions for Student Competency Assessment. arXiv. https://arxiv.org/abs/2608.24632 doi:10.48550/arxiv.2608.24632
q2 · i? · design · r2
Individualised counterfactual inference for a single student from the CAT assessment (109-student dataset), conditioning on the student's full set of observed answers and hint usage. For Q12 the counterfactual probabilities were [0,0], [0.24,1] and [0,0.76] for 0D, 1D and 2D, indicating uncertainty about performance with more assistance.
"The former yields probability one forQ 5 = 2D, i.e., we are certain that the student would have been able to use a 2D algorithm even without help."
Discussion¶
Related Claims¶
- Group-level marginal inferences identify population propensity and autonomy but are nearly vacuous for higher algorithmic skill levels — related
- Counterfactual probabilities of necessity and sufficiency quantify the causal effect of hints and skills on task performance — related
- Marginal luck probabilities diagnose question calibration, flagging questions 7–9 as prone to over-performance and question 12 as particularly challenging — related
- Formalisation of theory offers generative models, counterfactual reasoning, and optimal-performance yardsticks unavailable to verbal accounts — a broader claim this one bears on
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
individual-counterfactuals-student-help-conditions |
title |
Individualised counterfactual inferences estimate whether a specific student would have performed differently under different help conditions |
description |
Individualised counterfactual inferences estimate whether a specific student would have performed differently under different help conditions |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
recheck_by |
2029 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — francesca-mangili-2026 |
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