Item-level visualizations of discrimination index and discrimination efficiency led instructors to identify troublesome items and replace or modify them¶
Claim · All claims
Evidence · 1 study · designr2·q2
Currency · newest study 2021 · checked against its sources 2026-10-28 (automated, 1 of 1 entry) · 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? Using item-level visualizations such as item discrimination index and discrimination efficiency, instructors identified troublesome items, some with statements hard to understand even for top students, and decided to replace or modify them. → Josu Arruarte 2021
Evidence¶
Josu Arruarte 2021¶
Josu Arruarte, Mikel Larrañaga, Ana Arruarte & Jon A. Elorriaga. (2021). Measuring the Quality of Test-based Exercises Based on the Performance of Students. International Journal of Artificial Intelligence in Education, 31, 585–602. https://doi.org/10.1007/s40593-020-00208-0
q2 · i? · design · r2
Item-level analysis within the same retrospective evaluation, using TEA visualizations of metrics such as item discrimination index and discrimination efficiency. The article reports instructors "identified troublesome items" and "decided to replace or modify them for the following academic years". No effect sizes are printed.
"In this analysis, they identified troublesome items, some of them entailed statements that might be hard to understand, even for top students, and decided to replace or modify them for the following academic years."
Discussion¶
Related Claims¶
- Boxplot visualizations enriched with correlation to final marks identified the same suspicious tests as the consistency metrics, and instructors modified two of them for the next academic year — related
- A discrimination index can empirically validate Q-matrix specifications by identifying and replacing misspecified entries in the Q-matrix — related
- In a retrospective higher-education evaluation, instructors using TEA found low CIC values and unbalanced True Weights in three of the ten tests and marked them for further analysis — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
tea-item-level-troublesome-items-replaced |
title |
Item-level visualizations of discrimination index and discrimination efficiency led instructors to identify troublesome items and replace or modify them |
description |
Item-level visualizations of discrimination index and discrimination efficiency led instructors to identify troublesome items and replace or modify them |
status |
review |
evidence_strength |
weak |
newest_evidence |
2021 |
source_checked |
2026-10-28 |
generated |
by process:wiki-ingest on 2026-10-28 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — josu-arruarte-2021 |
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