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  4. Leveraging Prompting Guides as Worked Examples for Advanced Prompt Engineering Strategies
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Leveraging Prompting Guides as Worked Examples for Advanced Prompt Engineering Strategies

Journal
International Conference on Information Systems (ICIS)
Type
conference paper
Date Issued
2024-12-18
Author(s)
Tolzin, Antonia
;
Knoth, Nils
;
Andreas Janson  
Research Team
IWI6
Abstract
Artificial intelligence systems, particularly those based on large language models, are increasingly prevalent in personal and professional settings, making the skill of prompt engineering—formulating effective AI inputs—vital. This paper explores the effects and how to enhance students' prompt engineering skills based on a multi-study design. Our first study confirmed the baseline hypothesis that prompt engineering can predict AI output quality, framing it as a critical skill. We then investigated whether instructional designs (worked examples & instructions), could develop prompting skills. Using worked examples, the second study tested the effectiveness of instructional materials on enhancing prompting skills. The experiment involved 245 students who demonstrated that a brief exposure to a worked example-based prompting guide significantly improved their ability to deploy targeted prompting strategies. These findings suggest that integrating worked examples into curricula could effectively equip students with essential prompting skills, offering both theoretical and practical implications for AI education.
Language
English
Keywords
Large Language Model
Worked Examples
Prompt Engineering
AI Interaction
Education
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher place
Bangkok, Thailand
Pages
17
Event Title
International Conference on Information Systems (ICIS)
Event Location
Bangkok, Thailand
Event Date
15.12-18.12.24
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/121032
Subject(s)

information managemen...

Division(s)

IWI - Institute of In...

File(s)
Thumbnail Image
Name

JML_990.pdf

Size

419.36 KB

Format

Adobe PDF

Checksum (MD5)

c24fc444be501819809d2fc052433925

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