Developing Prompt Engineering as a 21st-Century Skill

Artificial intelligence (AI)-powered large language models, such as ChatGPT, are increasingly utilized in education, particularly for language learning. However, the effectiveness of AI-assisted learning is highly dependent on the quality of user-generated prompts. This study examines how structured instruction in prompt engineering affects English as a Foreign Language (EFL) students' ability to craft effective ChatGPT prompts, their engagement with AI, and their confidence in AI-assisted learning, culminating in the development of skills that will increasingly be in demand in the workplace. Using a three-phase intervention, students first generated self-created prompts, then used teacher-provided prompts based on the Nazari and Saadi framework, and finally received explicit instruction in structured prompt writing. After receiving instruction in prompt engineering, there were significant improvements in student prompt quality. Additionally, students’ confidence in prompt generation significantly increased after instruction. However, teacher-provided prompts alone did not significantly enhance student perceptions of ChatGPT’s usefulness for grammar or vocabulary improvement. These findings underscore the importance of explicit instruction in AI prompt engineering, suggesting that providing structured frameworks enhances student engagement, prompt effectiveness, and confidence in AI-assisted learning. Implications for AI-based language instruction and future research directions are discussed.

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Publication Details

Journal
GiLE Journal of Skills Development
Published
2025-10-08
DOI
https://doi.org/10.52398/gjsd.2025.v5.i3.pp87-108
Primary Topic
Smoking Behavior and Cessation
Type
article
Field-Weighted Citation Impact
0.00
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article

Developing Prompt Engineering as a 21st-Century Skill

GiLE Journal of Skills Development
Smoking Behavior and Cessation
article

Developing Prompt Engineering as a 21st-Century Skill

article en

Abstract

Artificial intelligence (AI)-powered large language models, such as ChatGPT, are increasingly utilized in education, particularly for language learning. However, the effectiveness of AI-assisted learning is highly dependent on the quality of user-generated prompts. This study examines how structured instruction in prompt engineering affects English as a Foreign Language (EFL) students' ability to craft effective ChatGPT prompts, their engagement with AI, and their confidence in AI-assisted learning, culminating in the development of skills that will increasingly be in demand in the workplace. Using a three-phase intervention, students first generated self-created prompts, then used teacher-provided prompts based on the Nazari and Saadi framework, and finally received explicit instruction in structured prompt writing. After receiving instruction in prompt engineering, there were significant improvements in student prompt quality. Additionally, students’ confidence in prompt generation significantly increased after instruction. However, teacher-provided prompts alone did not significantly enhance student perceptions of ChatGPT’s usefulness for grammar or vocabulary improvement. These findings underscore the importance of explicit instruction in AI prompt engineering, suggesting that providing structured frameworks enhances student engagement, prompt effectiveness, and confidence in AI-assisted learning. Implications for AI-based language instruction and future research directions are discussed.

GiLE Journal of Skills DevelopmentVol. 5(3)
Johannes Kepler University of Linz (AT)
Quality Education
Openalex Percentile: Top 41%
Smoking Behavior and Cessation
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