Designing a curriculum for AI prompting strategy for business decision‐makers—A qualitative approach

Pavankumar Mulgund et al.

Decision Sciences Journal of Innovative Education2026https://doi.org/10.1111/dsji.70020article
AJG 1ABDC C
Weight
0.50

What the paper says

Abstract Prompt engineering has emerged as a critical skill for optimizing interactions with Large Language Models (LLMs) across diverse applications. Despite its growing influence in the commercial sector, this discipline remains underrepresented in academic curricula, particularly within business schools. To address this gap, we present a comprehensive syllabus for an introductory prompt engineering course, tailored specifically for future digital product designers and managers. This course equips students with the skills to harness LLMs effectively, transforming them into valuable tools for problem‐solving and innovation. By detailing the course's motivation, objectives, key assignments, and expected outcomes, this article demonstrates how integrating prompt engineering education can prepare business students to navigate and lead in an AI‐driven marketplace, ultimately bridging the divide between academic learning and industry demands.

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https://doi.org/https://doi.org/10.1111/dsji.70020

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@article{pavankumar2026,
  title        = {{Designing a curriculum for AI prompting strategy for business decision‐makers—A qualitative approach}},
  author       = {Pavankumar Mulgund et al.},
  journal      = {Decision Sciences Journal of Innovative Education},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/dsji.70020},
}

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Designing a curriculum for AI prompting strategy for business decision‐makers—A qualitative approach

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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