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This chapter explores the transformative role of Generative AI in personalizing educational assessments within higher education and professional training. By leveraging advanced AI and Natural Language Processing techniques, AI-augmented frameworks, such as intelligent educational assistants and learning analytics tools provide customized feedback, adaptive learning pathways, and personalized support. Through case studies in higher education, we examine the impact of AI-driven virtual teaching assistants and learning analytics platforms on student engagement and learning outcomes. Additionally, we analyze applications in vocational training, where AI models like ChatGPT enhance educational performance in complex domains such as engineering and water quality management. These tools facilitate on-demand data analysis and user-friendly interpretation, empowering learners with essential knowledge for effective decision-making. Beyond the benefits, we also discuss the challenges and ethical considerations surrounding AI-driven assessment, including issues of fairness, transparency, and data privacy. The chapter concludes with insights into future directions, emphasizing the evolving role of Generative AI in shaping innovative, equitable, and efficient assessment practices in education and training.

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Adaptive Learning and Personalized Assessments with Generative AI: Insights from Higher Education and Professional Training

  • 章节

  • 发表日期：

    2026年

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  • Ramteja Sajja,
  • Vinay Pursnani,
  • Gabriel Vald,
  • Yusuf Sermet,
  • Ibrahim Demir

摘要

This chapter explores the transformative role of Generative AI in personalizing educational assessments within higher education and professional training. By leveraging advanced AI and Natural Language Processing techniques, AI-augmented frameworks, such as intelligent educational assistants and learning analytics tools provide customized feedback, adaptive learning pathways, and personalized support. Through case studies in higher education, we examine the impact of AI-driven virtual teaching assistants and learning analytics platforms on student engagement and learning outcomes. Additionally, we analyze applications in vocational training, where AI models like ChatGPT enhance educational performance in complex domains such as engineering and water quality management. These tools facilitate on-demand data analysis and user-friendly interpretation, empowering learners with essential knowledge for effective decision-making. Beyond the benefits, we also discuss the challenges and ethical considerations surrounding AI-driven assessment, including issues of fairness, transparency, and data privacy. The chapter concludes with insights into future directions, emphasizing the evolving role of Generative AI in shaping innovative, equitable, and efficient assessment practices in education and training.