The DOI matches its Crossref record, with a small difference in title or year; the references it cites are not checked yet.
A Framework for Integrating Artificial General Intelligence into Engineering Education: Enhancing Human-Centric Approaches for Industry 5.0
Open accessAbstract
In this paper, we present an advanced conceptual framework for integrating Artificial General Intelligence (AGI) into engineering education (Artificial General Intelligence Integration into Engineering Education (AGI 2 E 2 )). Our aim is to harmonize technical skills with intrinsic human qualities, such as creativity and ethical reasoning, essential for the Industry 5.0 landscape. This framework is based on comprehensive literature reviews and empirical data from student and faculty surveys, analyzed to assess AGI's potential to foster these human-centered qualities. Our proposal includes dynamic, interdisciplinary learning environments, personalized educational trajectories, continuous adaptation, and lifelong learning, addressing the ethical issues of AGI application. This framework not only advances engineering education to meet Industry 5.0 demands but also fosters holistic, human-centered learning experiences, preparing technically competent engineers equipped with vital interpersonal skills. This work builds upon previous research presented at a conference on integrating AI into engineering education.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This shift toward process-based assessment aligns with the broader movement toward durable skill development in higher education [30,106,107].”
From A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students' Critical Thinking (2026) · cites this paper as [107]
Citations
The citation lists haven’t been fetched yet
References 37 · Cited by 3
Metadata
- Authors
- Balart, T. S., & Shryock, K. J.
- Published
- 2024-06-07
- OpenAlex
- W4399423311
- Cited by
- 3
- References
- 37
- Citations by year
- 2026: 2 · 2025: 1
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Education › Engineering Education and Curriculum Development
- Social Sciences › Education › Engineering Education and Pedagogy
- Keywords
- artificial general intelligence, engineering education, Industry 5.0, human-centered learning, creativity, moral reasoning, interdisciplinary learning, personalized learning, lifelong learning, AI ethics, social skills
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Framework for Integrating Artificial General Intelligence into Engineering Education: Enhancing Human-Centric Approaches for Industry 5.0. https://app.cochat.ai/papers/10.36227/techrxiv.171778881.15802086/v1
- The paper
- Balart, T. S., & Shryock, K. J. (2024). A Framework for Integrating Artificial General Intelligence into Engineering Education: Enhancing Human-Centric Approaches for Industry 5.0. https://doi.org/10.36227/techrxiv.171778881.15802086/v1