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Revolutionizing Education Through Personalized Pedagogy and Machine Learning Algorithms

Revolutionizing Education Through Personalized Pedagogy and Machine Learning Algorithms

Chaimae Waladi, Mohamed Khaldi, Mohammed Sefian Lamarti
Copyright: © 2024 |Pages: 21
ISBN13: 9798369312063|ISBN13 Softcover: 9798369346358|EISBN13: 9798369312070
DOI: 10.4018/979-8-3693-1206-3.ch016
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MLA

Waladi, Chaimae, et al. "Revolutionizing Education Through Personalized Pedagogy and Machine Learning Algorithms." Fostering Pedagogical Innovation Through Effective Instructional Design, edited by Mohamed Khaldi, IGI Global, 2024, pp. 342-362. https://doi.org/10.4018/979-8-3693-1206-3.ch016

APA

Waladi, C., Khaldi, M., & Lamarti, M. S. (2024). Revolutionizing Education Through Personalized Pedagogy and Machine Learning Algorithms. In M. Khaldi (Ed.), Fostering Pedagogical Innovation Through Effective Instructional Design (pp. 342-362). IGI Global. https://doi.org/10.4018/979-8-3693-1206-3.ch016

Chicago

Waladi, Chaimae, Mohamed Khaldi, and Mohammed Sefian Lamarti. "Revolutionizing Education Through Personalized Pedagogy and Machine Learning Algorithms." In Fostering Pedagogical Innovation Through Effective Instructional Design, edited by Mohamed Khaldi, 342-362. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-1206-3.ch016

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Abstract

The combination of innovative pedagogy and machine learning algorithms presents transformative possibilities in the age of individualized education. This chapter explores the process of creating machine learning-enhanced personalized learning scenarios. It also looks at how intelligent pedagogy is built on the careful selection of learner activities, appropriate pedagogical approaches, and objectives. This chapter also includes a thoughtful case study that illustrates how these ideas are applied in the actual world. It has been demonstrated that the use of machine learning algorithms transforms remediation, assessment, and feedback while promoting a dynamic and adaptable learning environment. Through analyzing the effective application of machine learning in a real-world setting, teachers can acquire important knowledge about how to use these tools to maximize learning outcomes and give students more agency.

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