A Conceptual Framework for Utilizing Artificial Intelligence as a Teaching Assistant in Instructional Planning and Learning Activity Design in Higher Education
Keywords:
instructional design, higher education, Bloom’s Taxonomy, generative AIAbstract
This article proposes a conceptual framework for AI-augmented teaching to support instructional planning and learning activities in higher education. The framework is developed based on the Bloom’s Taxonomy Revised and evidence-based principles from cognitive science, aiming to enhance educator efficiency through the integration of artificial intelligence. The framework comprises four primary stages: (1) Planning: utilizing AI to analyze curriculum standards and define learning outcomes aligned with cognitive levels; (2) Design: employing AI to create activities, instructional materials, and assessment tools covering all six levels of thinking; (3) Implementation: leveraging AI as an in-class assistant to promote personalized learning and provide feedback to students; and (4) Evaluation: analyzing learning achievement data to inform continuous improvement of teaching quality. The framework adheres to the principle of AI as a teaching assistant, with instructors retaining ultimate control and academic decision-making authority, thereby ensuring that technological adoption is comprehensive and grounded in the highest standards of academic integrity and ethics. Additionally, the article presents examples of prompts ready for practical use at each stage of the conceptual framework, along with explanations of appropriate prompt engineering techniques. This aims to provide instructors with concrete practices for integrating artificial intelligence into teaching within the context of Thai higher education according to the higher education qualification standards, 2022
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