Claims

Classical IRT models without learning terms do not fit tutor-web drill data; a logistic model with numseen and attempt terms is needed

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2014 · 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? The fitted model requires numseen, numseen-squared, numseen-cubed, natt and natt-squared terms beyond the Rasch model's first and last terms. → Anna Helga Jonsdottir 2014

Evidence

Anna Helga Jonsdottir 2014

Anna Helga Jonsdottir, Gunnar Stefansson. (2014). From evaluation to learning: Some aspects of designing a cyber-university. https://arxiv.org/abs/1310.5552

q2 · i? · associational · r2

Statistical model fitting to tutor-web drill data shows the two-parameter Rasch model is insufficient: "the remaining parameters are also statist ically significant and therefore also needed to explain the data at hand".

"The two-parameter Rach model only incorporates the first and last terms in equation 2, but the remaining parameters are also statist ically significant and therefore also needed to explain the data at hand."

Discussion

Page metadata
Field Value
type claim
id irt-models-fail-learning-environment-fitted-logistic-model
title Classical IRT models without learning terms do not fit tutor-web drill data; a logistic model with numseen and attempt terms is needed
description Classical IRT models without learning terms do not fit tutor-web drill data; a logistic model with numseen and attempt terms is needed
status review
evidence_strength moderate
newest_evidence 2014
generated by process:wiki-ingest on 2026-10-29
trust unverified — no one has confirmed this page's content
sources 1 — anna-helga-jonsdottir-2014

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