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FACTRIA (Framework of Factors in the Analytical process and the data Context for Responsible Institutional Analytics)

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Evidence · 2 claims (2 for) · 1 study (1 qualitative), q2 · 1 of 1 report an effect size · 2 claims rest on one study

Description

A flexible, evidence-informed framework proposed by Marques et al. for helping higher-education managers, educators, and learning-analytics staff identify contextual and demographic biasing factors when interpreting institutional analytics.

Components

  • FACTRIA: a framework of biasing factors for responsible institutional analytics interpretation: FACTRIA (Framework of Factors in the Analytical process and the data Context for Responsible Institutional Analytics) synthesizes fragmented knowledge on factors that hinder responsible interpretation of IA visualizations. As the article states, it is "a framework that organizes potential biasing factors across four areas: the analytics pipeline, institutional context, course-level characteristics, and demographics." It does not prescribe decisions but provides "a structured, evidence-informed scaffold" helping users surface implicit assumptions, question comparability, and recognize factors shaping interpretation. The framework is intended as flexible and extensible, with additional biasing factors to be incorporated as IA practices evolve. (Marques et al. (2026))

Claims

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Key Sources

  • Marques, F., Ortiz-Beltrán, A., Amarasinghe, I., & Hernández-Leo, D. (2026). Responsible Institutional Analytics: Interpreting Bias with AI Support. Journal of Universal Computer Science, 33(6). https://arxiv.org/abs/2610.07205. doi:10.48550/arxiv.2610.07205
Page metadata
Field Value
type product
id factria-framework-of-factors-in-the-analytical-process-and-the-data-context-for-responsibl
title FACTRIA (Framework of Factors in the Analytical process and the data Context for Responsible Institutional Analytics)
description A flexible, evidence-informed framework proposed by Marques et al.
status review
product_kind framework
generated by process:settle-candidates on 2026-10-10
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