GrouPer

Product or Programme · All products and programmes
Evidence · 2 claims (2 for) · 2 studies (2 design), q2 · 0 of 2 report an effect size · 2 claims rest on one study

Description

GrouPer is an AI-based student-grouping recommendation tool developed for teachers that uses unsupervised clustering of assessment responses to support formative analysis and assignment of adapted learning activities.

Components

• GrouPer AI-based student-grouping recommendation tool: GrouPer is an AI-for-Teacher technology supporting personalized instruction in science education. Its analysis engine "uses an unsupervised machine learning algorithm (cluster analysis) to perform a multidimensional analysis of student responses to interactive assessment items", dividing students into clusters with similar knowledge profiles. The clusters are presented in an interactive dashboard that enables teachers to examine each cluster's performance and assign learning activities adapted to student groups' strengths and weaknesses. In this study it served as the research vehicle for studying trust and explainability, with both XAI explanation types presented textually alongside the dashboard. (Yael Feldman-Maggor et al. (2025))

Claims

• Unsupervised hierarchical clustering of knowledge vectors recovers expert bundle structure without bundle labels [+M]
• Clustering yields a small number of behaviorally distinct team clusters that instructors can use for cluster-differentiated feedback [+M]

Related Products and Programmes

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Key Sources

• Yael Feldman-Maggor, Mutlu Cukurova, Carmel Kent, Giora Alexandron. (2025). The Impact of Explainable AI on Teachers' Trust and Acceptance of AI EdTech Recommendations: The Power of Domain-specific Explanations. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-025-00486-6

Page metadata

Field	Value
type	product
id	grouper
title	GrouPer
description	GrouPer is an AI-based student-grouping recommendation tool developed for teachers that uses unsupervised clustering of assessment responses to support formative analysis and assignment of adapted learning activities.
status	review
product_kind	software
generated	by process:settle-candidates on 2026-10-12
trust	unverified — no one has confirmed this page's content

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