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Machine learning based approaches for pedagogical data analysis / editors, Anirban Mukherjee, Arpan Deyasi, Soumen Mukherjee, Pampa Debnath, Lidia Ghosh.
- Format:
- Book
- Language:
- English
- Subjects (All):
- Educational innovations.
- Educational technology.
- Machine learning--Educational applications.
- Machine learning.
- Physical Description:
- 1 online resource (268 pages) : illustrations.
- Place of Publication:
- Boca Raton FL : CRC Press, [2026]
- Contents:
- Preface. Theme: Artificial Intelligence in Digital Education. 1. Machine Learning Architectures for Pedagogical Data-Driven Teaching, Learning, and Assessment. 2. Artificial Intelligence in Education: Intelligent Tools and Techniques for Effective Teaching and Learning. 3. Usage of Library Resources supporting Informal Learning in Constructing Information Resilient Society: A Pedagogical Approach. 4. Recipe Vision: A Machine Learning Approach for Pedagogical Food Image Analysis and Image-to-Recipe Generation. Theme: Artificial Intelligence in Education Management. 5. A Research Agenda on NLP and NLU Applications in Developing Learning and Teaching Assistants. 6. A Novel Machine Learning Based Approach for Evaluating the Correctness of An English Sentence. 7. Data Retrieval from Documents by Question-Answer Approach: Using Large Language Model Application Architecture Based on the Retrieval Augmented Generation Model. 8. Facial Recognition-Enabled Classroom Attendance System. 9. Early Stage Mental Health Screening for Students using Machine Learning Techniques. 10. Machine Learning Based Spam Email Identification through Subject Affinity Applied for Pedagogical Persuasion Analysis. 11. A Machine Learning Approach to Recommendation System for Educational Data Analysis. Theme: Disruptive Technologies in Pedagogy. 12. Explainable AI: Enhancing Transparency and Trust in Educational Technology. 13. Embracing the Digital Frontier: Generative AI in Higher Education.
- Notes:
- "CRC Press"
- Electronic reproduction. London Available via World Wide Web.
- Online resource; title from pdf information screen (Taylor and Francis, viewed May 20, 2026)
- ISBN:
- 9781003559511
- 1003559514
- 9781040589625
- 1040589626
- 9781040678589
- 1040678580
- Publisher Number:
- 40033226674
- Access Restriction:
- Restricted for use by site license.
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