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Analysing Ireland's PISA 2022 Mathematics Profile Using AI-enhanced Assessment Modelling

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Vydáno v:OECD Education Working Papers no. 337 (2025), p. 1-29
Hlavní autor: Okubo, Tomoya
Další autoři: Reinertsen, Nata
Vydáno:
Organisation for Economic Cooperation and Development (OECD)
Témata:
Organization for Economic Cooperation & Development
Ireland
Problem solving
Curricula
Mathematics
Automation
Cognition & reasoning
Large language models
Learning
Literacy
Artificial intelligence
Journalism
Computer Simulation
Educational Quality
Mathematics Skills
Computer Assisted Testing
Curriculum Development
Geometric Concepts
Inferences
Curriculum Design
Addition
Learning Processes
International Assessment
Mathematics Achievement
Mathematics Education
Educational Change
Benchmarking
Misconceptions
Evidence
Arithmetic
Numeracy
Feedback (Response)
Educational Assessment
Mathematical Models
Mathematical Concepts
Educational Facilities Improvement
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Abstrakt:International large-scale assessments excel at robust cross-national comparisons, and detailed insight into students learning progressions emerges when paired with complementary diagnostic approaches. This study employed an Al-enhanced approach-the Collective Intelligence Model for Education (CIME)-to transform item-level responses from students in Ireland who participated in the PISA 2022 mathematics assessment into multidimensional diagnostic profiles. The profiles highlighted pronounced strengths in chance and probability and identified areas for continued development in geometric relationships and measurement. Students demonstrated proficiency in working with data and established mathematical representations, and showed developing proficiency in devising solution strategies, formalising complex situations, and applying mathematical models to structure and analyse real-world contexts. The findings indicate that Al-enhanced profiling yields fine-grained, policy-relevant diagnostics that complement headline scores and inform curriculum planning and system-level improvement.
ISSN:1993-9019
Zdroj:ABI/INFORM Global