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Theory-practice dialogue mechanism: generative AI bridges the gap between theory instruction and business practice

Design · All designs
Evidence · 1 claim (1 for) · 1 study (1 theoretical), q1 · 0 of 1 report an effect size · 1 claim rests on one study

Description

The first of the article's three proposed mechanisms for reconfiguring classroom pedagogy with generative AI. As the article states, "The theory-practice dialogue mechanism is designed to bridge the gap between theory and practice." In the strategic management course example, the mechanism uses generative AI to connect theoretical frameworks taught in class with contemporary business practice, supporting the shift from knowledge transmission toward capability development.

Design Implications

Context

Requirements

  • Access to generative AI tools in the classroom
  • A course with substantial theory content that students must connect to practice

Constraints

  • Proposed for management education, illustrated with a strategic management course; the article reports no empirical evaluation of the mechanism

Target Learners

  • business and management students in higher education

Learning Goals

  • connecting management theory to business practice
  • decision-making capabilities in complex business environments

Claims

Examples

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Key Sources

  • Shi, X., Dai, T., & Zhang, G. (2026). From Memorization to Experiential Learning: Reconfiguring Classroom Pedagogy in Management Education through Generative AI. Journal of Teaching Innovation and Practice, 2(1), 23–32. https://doi.org/10.65170/jtip.v2i1.53
Page metadata
Field Value
type design
id genai-theory-practice-dialogue-mechanism
title Theory-practice dialogue mechanism: generative AI bridges the gap between theory instruction and business practice
description The first of the article's three proposed mechanisms for reconfiguring classroom pedagogy with generative AI.
status review
generated by process:settle-candidates on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — shi-2026

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