OPTIMIZING EDUCATIONAL PROCESSES WITH GENERATIVE AI: INNOVATIVE INSTRUCTIONAL DESIGN AND AUTOMATED ASSESSMENT TOOLS
Keywords:
generative artificial intelligence, instructional design, automated assessment, personalized learning, intelligent tutoring systems, educational technology, large language models, learning analytics.Abstract
The rapid emergence of generative artificial intelligence (GenAI) has introduced a structural shift in how educational processes are designed, delivered, and evaluated. This paper examines the role of GenAI in optimizing modern education through three interrelated dimensions: innovative instructional design, automated assessment, and personalized learning. Adopting a structured review and comparative analysis methodology, the study synthesizes recent literature (2021-2026) and documented institutional case studies to identify the mechanisms by which large language models and related technologies enhance teaching efficiency, scalability, and learner engagement. The analysis indicates that GenAI-enabled systems can substantially reduce instructional workload, accelerate content authoring, and provide continuous formative feedback, while raising critical concerns regarding academic integrity, algorithmic bias, data privacy, and over-reliance.
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