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Generative AI and Agency in Education: A Critical Scoping Review and Thematic Analysis

Project Overview

The document provides a critical scoping review of the role of Generative AI (GenAI) in education, emphasizing its potential to enhance learner agency through personalized learning experiences and tailored support. Key applications of GenAI include adaptive learning systems that cater to individual student needs, thereby fostering engagement and improving educational outcomes. However, the review also identifies significant challenges, such as the risk of exacerbating existing inequalities and potentially undermining student autonomy. The authors argue for the development of comprehensive frameworks to ensure equitable access to GenAI tools and to safeguard learners’ agency in environments increasingly influenced by technology. Overall, the findings suggest that while GenAI has the potential to transform educational practices positively, careful consideration and strategic implementation are essential to mitigate risks and promote inclusivity.

Key Applications

GenAI tools for personalized learning and assessment support

Context: Higher education for college students and language learning environments, including tutoring, feedback, and grading

Implementation: Implemented through structured frameworks that guide the use of GenAI tools for personalized learning, tutoring, and grading in assessments. Teachers and students receive training in AI-assisted models to foster student-centered learning.

Outcomes: ['Enhanced learner agency', 'Improved academic achievement', 'Support for language acquisition and competence development', 'Increased grading efficiency']

Challenges: ['Potential inequities in access to GenAI tools', 'Risks of diminishing learner autonomy', 'Concerns over the automation of learning tasks limiting student engagement', 'Concerns about accuracy and bias in grading practices']

Implementation Barriers

Equity

Limited access to GenAI tools may exacerbate educational inequalities and the digital divide

Proposed Solutions: Recommendations for frameworks that promote equitable access to GenAI tools

Ethical

Concerns about academic integrity and ownership of work due to the use of GenAI tools

Proposed Solutions: Development of ethical guidelines and frameworks for responsible AI use in education

Transparency

GenAI tools are not transparent and may produce biased outputs

Proposed Solutions: Incorporate principles of accuracy and transparency into AI frameworks

Project Team

Jasper Roe

Researcher

Mike Perkins

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Jasper Roe, Mike Perkins

Source Publication: View Original PaperLink opens in a new window

Project Contact: Dr. Jianhua Yang

LLM Model Version: gpt-4o-mini-2024-07-18

Analysis Provider: Openai

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