The digital fingerprint of learner behavior: Empirical evidence for individuality in learning using deep learning

Salman, Asaf; Alexandron, Giora

doi:10.1016/j.caeai.2024.100322

Computers and Education: Artificial Intelligence

2024

DOI: 10.1016/j.caeai.2024.100322

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The digital fingerprint of learner behavior: Empirical evidence for individuality in learning using deep learning

Asaf Salman,

Giora Alexandron

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2024

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A Framework for the Responsible Integration of Generative AI Tools in Learning

Ko,

Chan

2024

Advances in Educational Technologies and Instructional Design

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Generative artificial intelligence (Gen-AI) tools are increasingly utilized in educational settings for tasks ranging from content creation to personalizing learning experiences. While these tools offer considerable potential to transform education, their integration brings challenges, including biases, dependency, and ethical dilemmas. Addressing these challenges and ethical concerns is essential to fully leveraging Gen-AI to promote equitable and effective learning. This chapter presents a framework for the responsible use of Gen-AI tools in learning environments, offering guidance to educators, technologists, policymakers, students, and other stakeholders. The framework provides proactive guidelines to navigate the complexities of Gen-AI, ensuring these tools are employed ethically and effectively to enhance student learning outcomes.

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A Framework for the Responsible Integration of Generative AI Tools in Learning

Ko,

Chan

2024

Advances in Educational Technologies and Instructional Design

View full text Add to dashboard Cite

show abstract

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The digital fingerprint of learner behavior: Empirical evidence for individuality in learning using deep learning

Cited by 1 publication

References 55 publications

A Framework for the Responsible Integration of Generative AI Tools in Learning

A Framework for the Responsible Integration of Generative AI Tools in Learning

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