Skip to content
Open access

AI as Scaffold or Shortcut? Metacognitive Regulation in Graduate Students’ Educational App Design

Jul 2026 · Education sciences · Vol 16, pp. 1198 · 0 citations · 44 references

TL;DR

The findings show that AI was used differently across the six cases, and appeared to function more as a cognitive scaffold when participants questioned, checked, revised, or justified AI-generated outputs, and more as a shortcut when outputs were used mainly for convenience with limited further reflection.

Abstract

The increasing use of artificial intelligence (AI) in education has raised important questions about how learners and teachers regulate their thinking when interacting with AI-supported tools. This study investigates metacognitive regulation during the design of AI-supported educational applications by graduate students (N = 12) in a UAE teacher education programme. The qualitative research adopted a multiple-case study method to analyse six student design teams involved in designing educational applications as part of a technology integration course. Data were collected from three main sources: the educational apps themselves, the corresponding Teacher Guides, and reflective interviews conducted using a semi-structured interview guide. Data analysis combined deductive qualitative coding based on the regulation-of-cognition dimensions of the Metacognitive Awareness Inventory (MAI) framework with inductive thematic analysis of participants’ experiences and conceptualisations of AI. The findings show that AI was used differently across the six cases. It appeared to function more as a cognitive scaffold when participants questioned, checked, revised, or justified AI-generated outputs, and more as a shortcut when outputs were used mainly for convenience with limited further reflection. Planning was the most visible regulatory process, while stronger regulatory engagement was evident when AI-generated outputs were examined, questioned, and refined rather than accepted without further consideration.

Read PDF

Similar papers

Open access 2026

AI-Supported Mind Mapping for Collaborative Discussion: An Exploratory Qualitative Classroom Study Using Personary

Examination of a classroom practice using Personary, a digital mind-mapping platform with an optional AI-assisted mode, to explore how university students conceptualize competencies needed in the AI era shows that students understood AI-era competencies as multidimensional capacities rather than as technical skills alo...

Hiroko Kanoh · 0 citations
Open access Aug 2026

Analysis of the Implementation of Problem-Based Gamified Quizzes in Coding and AI Learning to Strengthen High School Students Computational Thinking Skills

The development of Computational Thinking Skills (CTS) is increasingly important in Coding and Artificial Intelligence (AI) learning; however, students’ CTS remains influenced by multiple interrelated learning factors. Previous studies have generally examined these factors separately, leaving limited evidence on their...

Marina Elfera, H. Hidayat, T. Sriwahyuni et al. · 0 citations
Open access Jul 2026

AI AS A PEDAGOGICAL COMPANION IN HIGHER EDUCATION: TRANSFORMING TEACHING AND LEARNING PRACTICES IN THE ERA OF GENERATIVE ARTIFICIAL INTELLIGENCE

This study aims to analyze how artificial intelligence (AI) functions as a learning companion in transforming learning and teaching practices in a higher education setting. The study employed a qualitative approach using a dual-case study design, conducted in two classes in the Education Study Program at Sangga Buana Y...

R. Sari, Dadi Priadi, Sonya Meylani · 0 citations
Jul 2026

Generative AI supported practicum experiences contribute to the pedagogical reasoning and professional identity development of preservice mathematics teachers

This study explores how pre-service mathematics teachers experience AI-supported teaching during their practicum and how they make sense of the perceived influence of these experiences on pedagogical decision-making, classroom management, reflective awareness, and professional identity development. Conducted within a q...

Şahin Danişman · 0 citations
Open access Sep 2026

The Illusion of Analytical Depth: AI-Mediated Responses and Contextual Reasoning Challenges in Early Childhood Teacher Education

Differences in students’ pedagogical analysis across unmediated and AI-mediated response conditions in early childhood teacher education indicate that AI-mediated and prompt-structured conditions may support more organized written responses, but they do not necessarily demonstrate independently internalized analytical...

R. Pangastuti, Mukhoiyaroh, Rina Insani Setyowati et al. · 0 citations
Open access Aug 2026

From Mandatory Exposure to Guided Engagement: Investigating the Structured Integration of Generative AI in Higher Education

It is suggested that perceived learning usefulness remains relevant in mandatory AI-integration contexts and Pedagogical scaffolding—including prompt literacy, verification practices, and reflective documentation—provides a structured framework for guided and responsible use of generative AI tools in higher education.

Emese Belényesi, M. Korpics, Tamás Méhes et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.