Sociotechnical Imaginaries of ChatGPT in Higher Education: The Evolving Media Discourse

2025-08-20

AI Summary

This study investigates how U.S. mainstream media constructed narratives around ChatGPT’s adoption in higher education and shaped socio-technical imaginaries between November 2022 and October 2024. Applying framing theory, we conducted a dual temporal and sentiment analysis of 198 news articles. Methodologically, we identified dominant interpretive frames and tracked their evolution across key thematic domains—including institutional response, academic integrity, admissions, and assessment reform. Results reveal a pronounced “response bias”: media overwhelmingly foregrounded short-term institutional adaptations (e.g., policy revisions, pedagogical adjustments) while systematically marginalizing long-term ethical and structural implications. Admissions-related coverage sustained negative sentiment, whereas discourse on academic integrity and assessment reform shifted markedly from uncertainty to cautious optimism. This study is the first to empirically document this response preference in generative AI education narratives, demonstrating how selective framing constrains public imagination of educational AI innovation—offering critical empirical grounding for science and technology studies and educational technology communication research.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Knowledge Representation and Reasoning: Argumentation

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Consent frameworks and practices on the web

Abstract

This study investigates how U.S. news media framed the use of ChatGPT in higher education from November 2022 to October 2024. Employing Framing Theory and combining temporal and sentiment analysis of 198 news articles, we trace the evolving narratives surrounding generative AI. We found that the media discourse largely centered on institutional responses; policy changes and teaching practices showed the most consistent presence and positive sentiment over time. Conversely, coverage of topics such as human-centered learning, the job market, and skill development appeared more sporadically, with initially uncertain portrayals gradually shifting toward cautious optimism. Importantly, media sentiment toward ChatGPT's role in college admissions remained predominantly negative. Our findings suggest that media narratives prioritize institutional responses to generative AI over long-term, broader ethical, social, and labor-related implications, shaping an emerging sociotechnical imaginary that frames generative AI in education primarily through the lens of adaptation and innovation.

Problem

• Analyzing media framing of ChatGPT in higher education
• Tracking evolving narratives through temporal sentiment analysis
• Examining institutional responses versus broader societal implications

Innovation

• Framing Theory analysis media discourse
• Temporal sentiment analysis news articles
• Tracking institutional responses policy changes