This chapter explores the integration of AI tools in STEM education assessments, emphasizing their potential to enhance teaching, learning, and assessment practices. It examines how generative AI models like ChatGPT, Grammarly, and coding-specific platforms can offer personalized feedback, automate grading, and foster creativity in assessment design. The chapter highlights the advantages of AI, such as time-saving, tailored evaluations, and real-time feedback, while also addressing challenges like bias, fairness, and the risk of diminished human interaction in assessment processes. Furthermore, it emphasizes the importance of a hybrid approach, where AI tools complement traditional assessment methods, ensuring a comprehensive evaluation of both technical skills and creativity. The chapter concludes with implications for policy and practice, urging policymakers to implement equitable access to AI tools, promote transparency, and address ethical concerns, ultimately preparing students for the evolving demands of the workforce in a technology-driven world.

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Ethical Dilemmas and Practical Strategies for Leveraging Generative AI in STEM Assessment in Higher Education

  • Dharel P. Acut,
  • Sotero O. Malayao,
  • Amelia T. Buan,
  • Jun Karren V. Caparoso,
  • Jivulter C. Mangubat,
  • Manuel B. Garcia

摘要

This chapter explores the integration of AI tools in STEM education assessments, emphasizing their potential to enhance teaching, learning, and assessment practices. It examines how generative AI models like ChatGPT, Grammarly, and coding-specific platforms can offer personalized feedback, automate grading, and foster creativity in assessment design. The chapter highlights the advantages of AI, such as time-saving, tailored evaluations, and real-time feedback, while also addressing challenges like bias, fairness, and the risk of diminished human interaction in assessment processes. Furthermore, it emphasizes the importance of a hybrid approach, where AI tools complement traditional assessment methods, ensuring a comprehensive evaluation of both technical skills and creativity. The chapter concludes with implications for policy and practice, urging policymakers to implement equitable access to AI tools, promote transparency, and address ethical concerns, ultimately preparing students for the evolving demands of the workforce in a technology-driven world.