Basic, Structured, or Strategic? A Diagnostic Typology of Generation Z's Untrained AI Prompting Skills
DOI:
https://doi.org/10.62672/telad.v4i1.130Keywords:
AI literacy, Generation Z, Higher education, Human-AI interaction, Prompt engineeringAbstract
This study investigates the intuitive ("organic") capabilities of Generation Z students in designing Generative AI prompts, challenging the assumption that digital native status guarantees effective AI literacy. Through an in-depth qualitative content analysis of 125 prompts crafted by Educational Technology students at State University of Malang, this research maps their initial skill spectrum using a structured assessment rubric. The findings reveal a sharp polarization across three user typologies: Basic Users (42.4%) who tend to be ambiguous, Structured Users (32%) who are logical, and Strategic Users (25.6%) who demonstrate advanced control. This study concludes that general digital fluency does not automatically translate into AI literacy. Consequently, higher education institutions urgently need to explicitly integrate prompt engineering into the curriculum as a core future competency, rather than merely an adjunct technical skill.References
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Copyright (c) 2025 Henry Praherdhiono, Yerry Soepriyanto, Citra Kurniawan, Taufik Ikhsan Slamet, Fauziah Nur Aisyah Rosyidah, Rahma Izzatul Hajjah
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