REVIEW 2 cited by
Instructors as Innovators: A future-focused approach to new AI learning opportunities, with prompts
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
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.
Forward citations
Cited by 2 Pith papers
-
Watermark in the Classroom: A Conformal Framework for Adaptive AI Usage Detection
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.
-
Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation
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.
Discussion (0). Sign in to comment.