Curriculum analytics using cognitive diagnostic modeling and hierarchical learner-profile clustering¶
Research Method · All research methods
Evidence · 5 claims (5 for) · 1 study (1 associational),q2· 0 of 1 report an effect size · 5 claims rest on one study
Description¶
A two-step curriculum analytics approach that maps existing assessments to professional standards and applies a generalized cognitive diagnostic model to assessment grades to produce attainment probabilities (0–1) per standard, then uses hierarchical agglomerative clustering to group learners into interpretable profiles. The article states: "The model's output provides probabilities (on a scale of 0 to 1) indicating the extent to which the latent constructs (skills or standards) are attained." It was applied to an Australian ITE program using the APST framework and does not alter current assessment practices.
Accounts¶
- Curriculum analytics method combining CDM attainment estimation with hierarchical clustering of learner profiles: A two-step curriculum analytics approach that maps existing assessments to professional standards and applies a generalized cognitive diagnostic model to assessment grades to produce attainment probabilities (0–1) per standard, then uses hierarchical agglomerative clustering to group learners into interpretable profiles. The article states: "The model's output provides probabilities (on a scale of 0 to 1) indicating the extent to which the latent constructs (skills or standards) are attained." It was applied to an Australian ITE program using the APST framework and does not alter current assessment practices. (Abhinava Barthakur et al. (2026))
Claims¶
- CDM-estimated attainment of professional teaching standards varies non-uniformly across standards, with Standard 1 highest (0.86) and Standard 4 lowest (0.50) [+W]
- Hierarchical clustering of CDM attainment probabilities identifies five learner groups with distinct patterns of professional standards attainment [+W]
- Mean program GPA differs significantly across the five standards-attainment learner groups [+W]
- GPA fails to distinguish three pairs of learner groups that differ in standards-attainment patterns [+W]
- Standard 1 (knowing students) was attained relatively easily by all groups except the Novice group, while Standard 4 (supportive and safe environments) proved most challenging [+W]
Related Research Methods¶
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Key Sources¶
- Abhinava Barthakur, Jelena Jovanović, Ryan Baker, Vitomir Kovanović, Christopher Charles Deneen and Shane Dawson. (2026). Assessing Patterns of Students' Attainment of Professional Standards in Higher Education. Journal of Learning Analytics, 13(1), 42–56. https://doi.org/10.18608/jla.2026.9035
Page metadata
| Field | Value |
|---|---|
type |
research-method |
id |
curriculum-analytics-using-cognitive-diagnostic-modeling-and-hierarchical-learner-profile |
title |
Curriculum analytics using cognitive diagnostic modeling and hierarchical learner-profile clustering |
description |
A two-step curriculum analytics approach that maps existing assessments to professional standards and applies a generalized cognitive diagnostic model to assessment grades to produce attainment probabilities (0–1) per standard, then uses hierarchical agglomerative clustering to group learners into i |
status |
review |
moved_from |
element/cdm-clustering-curriculum-analytics-method |
generated |
by process:sweep-kinds on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — abhinava-barthakur-2026 |
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