BOOK-CHAPTER

AI-Driven Learning Analytics for Personalized Feedback and Assessment in Higher Education

Abstract

Advancements in artificial intelligence (AI) and learning analytics have opened up new possibilities for personalized education in higher education institutions. This chapter explores the potential of AI-driven learning analytics in higher education, focusing on its application in personalized feedback and assessment. By leveraging AI algorithms and data analytics, personalized feedback can be provided to students, targeting their specific strengths and areas for improvement. Adaptive and formative assessments can also be facilitated through AI-driven learning analytics, enabling personalized and accurate evaluation of students' knowledge and skills. However, ethical considerations, implementation challenges, and faculty training are crucial aspects that must be addressed for successful adoption. As technology continues to evolve, embracing AI-driven learning analytics can enhance student engagement, support individualized learning, and optimize educational outcomes.

Keywords:
Formative assessment Learning analytics Personalized learning Analytics Computer science Data science Knowledge management Artificial intelligence Teaching method Psychology Open learning Mathematics education Cooperative learning

Metrics

78
Cited By
86.74
FWCI (Field Weighted Citation Impact)
20
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Online Learning and Analytics
Physical Sciences →  Computer Science →  Computer Science Applications
Artificial Intelligence in Healthcare and Education
Health Sciences →  Medicine →  Health Informatics

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