Article

A Transparency Index Framework for AI in Education

Authors:

Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium: 23rd International Conference, AIED 2022, Durham, UK, July 27–31, 2022, Proceedings, Part II

Pages 195 - 198

https://doi.org/10.1007/978-3-031-11647-6_33

Published: 27 July 2022 Publication History

Abstract

Numerous AI ethics checklists and frameworks have been proposed focusing on different dimensions of ethical AI such as fairness, explainability, and safety. Yet, no such work has been done on developing transparent AI systems for real-world educational scenarios. This paper presents a Transparency Index framework that has been iteratively co-designed with different stakeholders of AI in education, including educators, ed-tech experts, and AI practitioners. We map the requirements of transparency for different categories of stakeholders of AI in education. The main contribution of this study is that it highlights the importance of transparency in developing AI-powered educational technologies and proposes an index framework for its conceptualization for AI in education.

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Cited By

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Zhou QSuraworachet WCukurova M(2024)Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative LearningProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636894(392-403)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636894

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Published In

Jul 2022

669 pages

ISBN:978-3-031-11646-9

DOI:10.1007/978-3-031-11647-6

Editors:
Maria Mercedes Rodrigo
Ateneo De Manila University, Quezon, Philippines
,
Noburu Matsuda
Department of Computer Science, North Carolina State University, Raleigh, NC, USA
,
Alexandra I. Cristea
Durham University, Durham, UK
,
Vania Dimitrova
University of Leeds, Leeds, UK

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 27 July 2022

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Zhou QSuraworachet WCukurova M(2024)Harnessing Transparent Learning Analytics for Individualized Support through Auto-detection of Engagement in Face-to-Face Collaborative LearningProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636894(392-403)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636894

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References

Cited By

Recommendations

A machine learning approach for intelligent tutoring systems

Leading teachers' perspective on teacher-AI collaboration in education

Artificial Intelligence in Education: Ethical Issues and its Regulations

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