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AI-Driven Curriculum Transformation and Faculty Development in Developing Universities
4
Zitationen
2
Autoren
2025
Jahr
Abstract
Higher education institutions in developing regions face constraints related to curriculum design and faculty readiness. Prior research identified gaps in aligning course content with evolving technological demands, which triggered the need for a reimagined learning framework. This chapter examines how purposeful integration of machine learning tools and data-driven methodologies can enhance teaching processes while addressing learner-centered outcomes. Findings from prior initiatives showed that faculty participation in continuous professional development contributed to sustainable program improvements. Results indicated that adaptive platforms boosted student engagement and performance. This chapter underscores the importance of context-based innovations that respond to local constraints. The proposed strategies expand existing knowledge on curriculum transformation, highlighting models for replicable practices that advance institutional objectives.
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