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Instructor-centered framework for translating institutional GenAI guidance into course implementation via three mediating factors

Design · All designs
Evidence · 1 claim (1 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

The authors propose a framework that guides the translation of institutional guidance to course implementation by placing the instructor at the center of the process and considering mediating factors (Figure 3). The first factor is the instructor's current expertise in GenAI use and broader AI literacy, along with the training needed to implement GenAI in instruction; in CS this includes understanding model limitations in code generation and recognizing security vulnerabilities in AI-generated code. The second factor is discipline or domain, since implications of GenAI use differ sharply between theory-heavy courses such as algorithms and applied ones such as software engineering. The third factor is the nature of instruction and required pedagogical knowledge, as GenAI use varies across lecture-based, lab-based and project-based courses.

Design Implications

Context

Requirements

  • Instructor AI literacy and training to implement GenAI in instruction
  • Accounting for whether the course is theory-heavy or applied
  • Pedagogical knowledge matched to lecture-based, lab-based, or project-based instruction

Constraints

  • The framework is proposed, not empirically tested in this study; the authors state the transition to productive GenAI use will be an arduous task and substantial revisions to existing CS pedagogical practices will be needed

Target Learners

  • Higher education students in computing courses

Learning Goals

  • Responsible and productive GenAI use aligned with course learning outcomes
  • Preservation of problem-solving skills while supporting technical skill development

Claims

Examples

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Key Sources

  • Amrita Ganguly, Aditya Johri, Nora McDonald, Areej Ali, Umama Dewan, and Aayushi Hingle Collier. (2026). A Comparative Analysis of Institutional and Course Generative AI Policies within Higher Education: Implications for Instruction in Computing Education.
Page metadata
Field Value
type design
id instructor-centered-genai-implementation-framework
title Instructor-centered framework for translating institutional GenAI guidance into course implementation via three mediating factors
description The authors propose a framework that guides the translation of institutional guidance to course implementation by placing the instructor at the center of the process and considering mediating factors (Figure 3).
status review
generated by process:settle-candidates on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — amrita-ganguly-2026

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