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Four-dimension classification for grading student model portability

Research Method · All research methods
Evidence · 1 claim (1 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

The article introduces a classification that grades student models in terms of portability. Portability is measured across four dimensions — accessibility, complexity, architecture, and popularity — each composed of factors such as open source status, availability, inputs, types of data, input formats, computational techniques, data mining use, model origin, implementation, modularity, server/client architecture, and re-implementation. Each factor is graded 1 to 4 (low, mid, high restrictions, or no information), dimension grades are normalized sums mapped to 1–4, and the overall grade is the sum of the dimensions, where a grade of 4 represents "the models with least types restrictions we found (Very Low)". The authors intend it "to be used by researchers both as a methodology to measure the portability of a student model and as a guide to find existing reusable models".

Accounts

  • A four-dimension classification for grading student model portability: The article introduces a classification that grades student models in terms of portability. Portability is measured across four dimensions — accessibility, complexity, architecture, and popularity — each composed of factors such as open source status, availability, inputs, types of data, input formats, computational techniques, data mining use, model origin, implementation, modularity, server/client architecture, and re-implementation. Each factor is graded 1 to 4 (low, mid, high restrictions, or no information), dimension grades are normalized sums mapped to 1–4, and the overall grade is the sum of the dimensions, where a grade of 4 represents "the models with least types restrictions we found (Very Low)". The authors intend it "to be used by researchers both as a methodology to measure the portability of a student model and as a guide to find existing reusable models". (Valdés Aguirre et al. (2016))

Claims

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Key Sources

  • Valdés Aguirre, B., Ramírez Uresti, J. A., & du Boulay, B. (2016). An Analysis of Student Model Portability. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-016-0113-0
Page metadata
Field Value
type research-method
id four-dimension-classification-for-grading-student-model-portability
title Four-dimension classification for grading student model portability
description The article introduces a classification that grades student models in terms of portability.
status review
generated by process:settle-candidates on 2026-10-27
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