Generative AI and the social functions of educational assessment

This paper examines the transformative potential of Generative AI (GenAI), particularly large language models such as ChatGPT, for the social functions of educational assessment. Using Patricia Broadfoot’s ‘four Cs’ framework – competence, competition, content, and control – the analysis considers how GenAI may enhance or challenge these traditional roles. Two additional ‘C’s are introduced: ‘credibility’, concerning the authenticity of learner performance in an era of AI-generated outputs, and ‘connoisseurship’, relating to the ability to effectively use and critically assess AI-generated content. While GenAI offers significant opportunities for personalised learning and more nuanced assessments of competence, it also presents challenges related to authenticity, surveillance, and inequality. We conclude that the ‘four Cs’ framework remains a valid lens for understanding the social functions of educational assessment, now augmented by the dimensions of credibility and connoisseurship.

Authors

Institutions

Publication Details

Journal
Oxford Review of Education
Published
2025-03-04
DOI
https://doi.org/10.1080/03054985.2025.2455549
Citations
3
Primary Topic
Artificial Intelligence in Education
Type
article
Field-Weighted Citation Impact
9.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generative AI and the social functions of educational assessment

Patricia Broadfoot, James Rockey
3 citations
Oxford Review of Education
Artificial Intelligence in Education
9.74
article

Generative AI and the social functions of educational assessment

Patricia Broadfoot, James Rockey
article en
3 citations

Abstract

This paper examines the transformative potential of Generative AI (GenAI), particularly large language models such as ChatGPT, for the social functions of educational assessment. Using Patricia Broadfoot’s ‘four Cs’ framework – competence, competition, content, and control – the analysis considers how GenAI may enhance or challenge these traditional roles. Two additional ‘C’s are introduced: ‘credibility’, concerning the authenticity of learner performance in an era of AI-generated outputs, and ‘connoisseurship’, relating to the ability to effectively use and critically assess AI-generated content. While GenAI offers significant opportunities for personalised learning and more nuanced assessments of competence, it also presents challenges related to authenticity, surveillance, and inequality. We conclude that the ‘four Cs’ framework remains a valid lens for understanding the social functions of educational assessment, now augmented by the dimensions of credibility and connoisseurship.

Oxford Review of EducationVol. 51(2)
University of Bristol (GB), University of Birmingham (GB)
Reduced inequalities
Openalex Percentile: Top 3%
Artificial Intelligence in Education
9.74
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Generative AI and the social functions of educational assessment — Patricia Broadfoot, James Rockey · Oxford Review of Education (2025) | TGRS Research Map | TGRS