Skip to content

Pedagogy-guided integration of generative AI in undergraduate engineering education

Sep 2026 · Journal of Applied Research in Higher Education · 0 citations · 20 references

TL;DR

The findings suggest that the educational value of generative AI depends on pedagogical orchestration, guided prompting and reflection rather than simple access to the tool.

Abstract

This study examines whether a pedagogy-guided, artificial intelligence (AI)-assisted learning environment can improve learning performance and student perceptions in undergraduate engineering education. Rather than positioning generative AI as an answer-generating tool, the study frames it as a scaffold embedded within a structured teaching process. A quasi-experimental design was implemented in an undergraduate engineering course in Taiwan. Eighty-two students participated across an AI-assisted group and a comparison group receiving conventional instruction. The intervention followed four recurring stages: problem introduction, AI-supported exploration, critical reflection and discussion with feedback. Quantitative evidence was drawn from five rubric-assessed problem-solving assignments and a post-course questionnaire administered to the AI-assisted cohort, while qualitative evidence came from students' reflective writing. Because the questionnaire was administered only to the AI-assisted cohort, its results are reported descriptively rather than as between-group effects. The AI-assisted cohort showed higher composite assignment performance and reported strong engagement, perceived usefulness and problem-solving confidence. Qualitative findings showed that structured reflection helped students question AI-generated responses, identify limitations and refine their own reasoning rather than accept outputs uncritically. As the comparison group came from a previous semester, assignments were scored by the course instructor and prior AI exposure was not measured systematically, the findings should be interpreted as promising exploratory evidence rather than definitive causal proof. The findings suggest that the educational value of generative AI depends on pedagogical orchestration, guided prompting and reflection rather than simple access to the tool. The paper offers a classroom-tested model for integrating generative AI into higher engineering education in a pedagogically meaningful and ethically responsible way.

View source

Similar papers

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
#generative ai Open access Sep 2026

Generative AI as Instructional Scaffolding: Effects on Critical Thinking and Classroom Engagement in Secondary Education

It is demonstrated that generative artificial intelligence effectively supports critical thinking and classroom engagement when used as guided instructional scaffolding rather than as a provider of final answers.

Herman Herman, Muh. Nasir, A. Putra et al. · 0 citations
Review Open access Aug 2026

Integrating AI into Engineering Design Education: A Comparative Study of Traditional and AI-Enhanced Approaches in a Second-Year Design Course

Investigation of the impact of integrating GenAI tools on student learning in the second-year engineering design course at the University of Prince Edward Island finds that students most frequently used GenAI for brainstorming, problem definition, and concept generation, while strongly engaging with ethical verificatio...

K. Grewal, Mikkayla Ellsworth-Reid, Prabhnoor Sigh et al. · 0 citations
Open access Sep 2026

Towards professionalism: AI to benefit student-teachers’ lesson planning

The findings unveil that the chatbot-supported cohort exhibited marked improvements in overall lesson planning, with notable gains in crafting worked examples and posing probing questions, alongside significant advancements in pedagogical knowledge, and a robust boost in teaching self-efficacy.

A. Abukhanova, Bibigul Almukhambetova, A. Mamekova et al. · 0 citations
Open access Sep 2026

Designing an AI-integrated role-rotation pedagogical model to support competence-related learning in pre-service educational psychologists

The principal contribution of the study lies in conceptualizing systematic role rotation as a pedagogical mechanism for structuring critical human–AI interaction in professional learning.

Zh.т. Kenzhebayeva, B. Matayev, E. Sarsembayeva et al. · 0 citations

Related blog posts

MIT News · Artificial Intelligence Oct 30, 2026

Q&A: Hey AI, who should I vote for this year?

MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.

Microsoft Research Blog Oct 30, 2026

From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence

Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.

GPT-Lab Oct 30, 2026

Black October? The Week AI Changed the Cybersecurity Conversation

Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.

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