Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Brief Prompt-Engineering Clinic Substantially Improves AI Literacy and Reduces Technology Anxiety in First-Year Teacher-Education Students

A Pre–Post Pilot Study

Bibliographic Data

ID22047185
AuthorsRoberto Carlos Dávila Morán (0000-0003-3181-8801, Universidad Continental, corresponding author), Juan Manuel Sánchez Soto (0000-0002-3276-6778, Los Andes Peruvian University), Henri Emmanuel López Gómez (0000-0002-5404-4047, Los Andes Peruvian University), Manuel Silva Infantes (0000-0002-6500-0592, Los Andes Peruvian University), Andrés Arias Lizares (0000-0002-7536-4146, Universidad Nacional del Altiplano), Lupe Marilu Huanca Rojas (0000-0002-2533-1055, Universidad Nacional Intercultural de la Amazonía), Simon Jose Cama Flores (Universidad Nacional José María Arguedas)
Year2025
Volume15
Issue8
Pages1010
Publication date2025-08-06
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci15081010
OpenAlexW4413038081
LanguageEN
Citations received3
References cited21

Generative AI tools such as ChatGPT are reshaping educational practice, yet first-year teacher-education students often lack the prompt-engineering skills and confidence required to use them responsibly. This pilot study examined whether a concise three-session clinic on prompt engineering could simultaneously boost AI literacy and reduce technology anxiety in prospective teachers. Forty-five freshmen in a Peruvian teacher-education program completed validated Spanish versions of a 12-item AI-literacy scale and a 12-item technology-anxiety scale one week before and after the intervention; normality-checked pre–post differences were analysed with paired-samples t-tests, Cohen’s d, and Pearson correlations. AI literacy rose by 0.70 ± 0.46 points (t (44) = −6.10, p

Anxiety · Curriculum · Literacy · Mathematics education · Medical education · Pedagogy · Psychiatry · Computer Science · Digital Mental Health Interventions · Medicine · Psychology

  • A critical review and actionable framework for integrating generative AI into teacher professional development

    Open Access•Prashanth Shenoy, Mirka Saarela•Discover Education•2026

  • Building the AI Empowerment Framework for Teacher Education

    Open Access•Yao Fu, Zhenjie Weng•Teaching and Teacher Education•2026

  • Learning to question the machine

    Open Access•Abdullah M Dagamseh, Hesham Aldamen et al.•Cogent Arts and Humanities•2026

  • Statistical Power Analysis for the Behavioral Sciences

    Jacob Cohen•Statistical Power Analysis for…•2013

  • Resolving the 50‐year debate around using and misusing Likert scales

    Open Access•James Carifio, Rocco J Perla et al.•Medical Education•2008

  • In search of artificial intelligence (AI) literacy in teacher education

    Open Access•Katarina Sperling, Carl-Johan Stenberg et al.•Computers and Education Open•2024

  • Calculating and reporting effect sizes to facilitate cumulative science

    Open Access•Daniël Lakens•Frontiers in Psychology•2013

  • Likert scales, levels of measurement and the “laws” of statistics

    Open Access•Geoff Norman, Geoffrey R Norman•Advances in Health Sciences…•2010

  • Guidelines for the Process of Cross-Cultural Adaptation of Self-Report Measures

    Dorcas E Beaton, Dorcas Beaton et al.•Spine•2000

  • Fostering AI literacy in pre-service physics teachers

    Open Access•Aigerim Abdulayeva, Nazym Zhanatbekova et al.•Frontiers in Education•2025

  • Prompt engineering as a new 21st century skill

    Open Access•Denis Federiakin, Dimitri Molerov et al.•Frontiers in Education•2024

  • Comprehension, apprehension, and acceptance

    Open Access•Gianluca Schiavo, Stefano Businaro et al.•Technology in Society•2024

Citations per year3
Citation span2026 - 2026 (1)
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae