arXiv AI

AI-Automation Tooling in Computer Engineering Education: Mixed-Methods TAM/UTAUT Evidence for a General Acceptance Attitude

arXiv:2606. 12424v1 Announce Type: cross Abstract: As generative AI and low-code workflow platforms become routine in software practice, a key educational question is whether the next generation of computer engineers will accept these tools as useful, usable, and worthy of sustained engagement.

arXiv AI
Jul 7

Three-Phase Evaluation of AI-Assisted Software Development Life Cycle

arXiv:2607. 05125v1 Announce Type: cross Abstract: This paper presents an exploratory evaluation of how increasing levels of AI autonomy affect software development productivity, requirement adherence, and developer cognitive workload.

By Joshua Strubel, Professor Carrie Russell, Carson Crockett, Jason Ferraro, Nathan Londhe, Uzayr Syed, Jacob Viehe
arXiv AI
6d ago

A Conceptual Framework for Enhancing Workforce Readiness for Smart Manufacturing in the AI Era

arXiv:2608. 11540v1 Announce Type: cross Abstract: The convergence of artificial intelligence (AI), Industrial Internet of Things, cyber-physical systems, and advanced robotics is reshaping manufacturing faster than engineering curricula can adapt, widening the gap between the competencies required on the shop floor and those delivered by traditional engineering and technology education.

By Dalton Ross Smith, Wilburn Whittington, Alejandro Martinez, Aidan Duncan, Gang Li
arXiv AI
Jul 8

Prompt Coach: An Empirical Evaluation of an Agentic Tutor for Learning Prompt Engineering in Software Development

arXiv:2607. 06074v1 Announce Type: cross Abstract: Prompt engineering has emerged as a critical yet undertaught skill for software developers, one that traditional learning approaches are ill-equipped to support given its evolving, interactive, and context-dependent nature.

By Rohit Mehra, Kapil Singi, Vikrant Kaulgud, Vibhu Saujanya Sharma, Swapnajeet Gon Choudhury, Swati Sharma, Adam P. Burden, Majd Sakr