Journal of Computer Science and Informatics Engineering
Vol 5 No 3 (2026): July

Prompt Engineering as a Digital Literacy Skill: A Conceptual Framework for Effective Human–AI Collaboration

Maryam Hussaini (Mewar International University)
Mahmud Lawan (Universitas Muhammadiyah Sumatera Utara)
Ukasha Abubakar (UIN Sunan Ampel Surabaya)



Article Info

Publish Date
11 Jul 2026

Abstract

The rapid adoption of generative artificial intelligence (AI) tools has transformed the way individuals interact with digital technologies across educational, professional, and research contexts. Despite the growing reliance on AI systems, many users lack the competencies required to formulate effective prompts, evaluate AI-generated outputs, and engage in responsible human–AI collaboration. Existing digital literacy frameworks primarily emphasize information access, communication, and technology use, while providing limited attention to prompt engineering as a distinct digital competency. This research introduces the conceptual model, the PIERCE Framework, which places prompt engineering as a crucial digital literacy skill in the era of generative AI. The framework was conceptualized by analyzing the latest literature on digital literacy, AI literacy, human–AI interaction, and prompt engineering. The proposed framework is divided into six interrelated components: Prompt Intent Formulation, Intelligent Prompt Design, Engagement with AI, Response Evaluation, Continuous Refinement, and Ethical Application. Together, these components provide a structured pathway for effective human–AI collaboration. The framework contributes to the growing discourse on AI literacy by offering a comprehensive perspective on the competencies required for productive and responsible AI use. The findings highlight the importance of integrating prompt engineering into future digital literacy initiatives, educational programs, and professional development practices.

Copyrights © 2026






Journal Info

Abbrev

cosie

Publisher

Subject

Computer Science & IT

Description

Artificial Intelligence Machine Learning Natural Language Processing Computer Vision Text Speech Text Mining Data mining Cryptography Data visualization Expert System Deep Learning Fuzzy Logic IoT and smart environments Neural Networks Pattern Recognition Image Processing Optimization Digital Signal ...