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Artificial Intelligence and Machine Learning in Educational Research: Applications, Challenges, and Ethical Considerations

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Title: Artificial Intelligence and Machine Learning in Educational Research: Applications, Challenges, and Ethical Considerations
Language: English
Authors: Mudit Kumar Verma (ORCID 0000-0001-8543-1667)
Source: Online Submission. 2026.
Peer Reviewed: N
Page Count: 8
Publication Date: 2026
Document Type: Reports - Evaluative
Descriptors: Artificial Intelligence, Natural Language Processing, Educational Research, Barriers, Ethics, Intelligent Tutoring Systems, Individualized Instruction, Predictor Variables, Data Use, Information Security, Learning Analytics
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are transforming educational research through the integration of computational intelligence, data-driven analysis, and adaptive learning systems. This chapter explores the multifaceted applications of AI and ML in education, ranging from personalized learning environments to predictive analytics, natural language processing, and intelligent tutoring systems. The discussion extends to methodological and ethical considerations, emphasising the importance of transparency, fairness, and data privacy in the use of these technologies. It also highlights the challenges associated with algorithmic bias, interpretability, and scalability in educational contexts. Drawing upon contemporary research, the chapter articulates a conceptual framework linking AI's computational capacity with educational theory and practice, providing a critical perspective on how emerging technologies are reshaping pedagogy, assessment, and policy. The concluding sections envision the future trajectory of AI in education, underscoring the need for interdisciplinary collaboration, ethical governance, and human-centred design in educational AI systems. [This paper was published in: "Educational Research: Perspectives and Practices," edited by Dhriti Tiwari and Azkiya Waris, Book Rivers, 2026, pp. 126-133.]
Abstractor: As Provided
Entry Date: 2026
Accession Number: ED679676
Database: ERIC
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  Availability: 0
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  Data: Artificial Intelligence (AI) and Machine Learning (ML) are transforming educational research through the integration of computational intelligence, data-driven analysis, and adaptive learning systems. This chapter explores the multifaceted applications of AI and ML in education, ranging from personalized learning environments to predictive analytics, natural language processing, and intelligent tutoring systems. The discussion extends to methodological and ethical considerations, emphasising the importance of transparency, fairness, and data privacy in the use of these technologies. It also highlights the challenges associated with algorithmic bias, interpretability, and scalability in educational contexts. Drawing upon contemporary research, the chapter articulates a conceptual framework linking AI's computational capacity with educational theory and practice, providing a critical perspective on how emerging technologies are reshaping pedagogy, assessment, and policy. The concluding sections envision the future trajectory of AI in education, underscoring the need for interdisciplinary collaboration, ethical governance, and human-centred design in educational AI systems. [This paper was published in: "Educational Research: Perspectives and Practices," edited by Dhriti Tiwari and Azkiya Waris, Book Rivers, 2026, pp. 126-133.]
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      – SubjectFull: Natural Language Processing
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      – SubjectFull: Educational Research
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      – SubjectFull: Information Security
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      – SubjectFull: Learning Analytics
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