Twenty-Second International Conference on Technology, Knowledge, and Society

Abstract

As university professors of education, we recognize the pedagogical opportunities and the critiques surrounding generative AI. To address these tensions, we propose the 4E-Model of AI Pedagogy as a framework for purposefully integrating AI into teaching and learning. The first element, efficiency, highlights AI’s capacity to reduce time and effort, while emphasizing the need for educators and students to understand AI’s knowledge base, limitations, and embedded biases. Without this critical awareness, efficiency risks becoming a shortcut that undermines learning. The second element, effectiveness, challenges educators to reconsider the purpose of assignments and assessments in an AI era. If AI can perform traditional tasks, then pedagogical design must shift toward fostering reasoning, creativity, reflection, and judgment, making AI the rebirth of critical thought. The third element, engagement, underscores the importance of preventing pedagogical detachment by integrating self-regulation, inquiry, and critical analysis into AI-supported learning. Engagement requires students to manage and critique their interactions with AI, fostering metacognitive awareness and meaningful collaboration. Finally, ethics is interwoven throughout the model. An ethical lens draws attention to issues such as academic integrity, professional responsibility, sustainability, and social justice. We conclude by offering reflective questions to guide the alignment of AI educational practices with the 4E-Model. Rather than viewing AI as a threat, our model positions it as a pedagogical opportunity that is efficient, effective, engaging, and ethically grounded.