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Instructors as Innovators: A future-focused approach to new AI learning opportunities, with prompts

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arxiv 2407.05181 v1 pith:I6ZD5HPC submitted 2024-04-23 cs.CY cs.AI

classification cs.CYcs.AI
keywords instructorslearningpromptscreateexercisesapproachexperiencesinnovators
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This paper explores how instructors can leverage generative AI to create personalized learning experiences for students that transform teaching and learning. We present a range of AI-based exercises that enable novel forms of practice and application including simulations, mentoring, coaching, and co-creation. For each type of exercise, we provide prompts that instructors can customize, along with guidance on classroom implementation, assessment, and risks to consider. We also provide blueprints, prompts that help instructors create their own original prompts. Instructors can leverage their content and pedagogical expertise to design these experiences, putting them in the role of builders and innovators. We argue that this instructor-driven approach has the potential to democratize the development of educational technology by enabling individual instructors to create AI exercises and tools tailored to their students' needs. While the exercises in this paper are a starting point, not a definitive solutions, they demonstrate AI's potential to expand what is possible in teaching and learning.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Watermark in the Classroom: A Conformal Framework for Adaptive AI Usage Detection

    stat.AP 2025-07 conditional novelty 6.0 of 10

    Standard, hierarchical, and weighted conformal prediction applied to LLM watermark scores can control false-positive rates when detecting guideline-violating AI edits in simulated classroom essays.

  2. Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation

    cs.CL 2025-06 conditional novelty 5.0 of 10

    Fine-tuning a math tutor model on 11 fine-grained pedagogical intents instead of 4 broad ones gave better automatic scores and a modest human preference in a small evaluation.

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