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Lookup NU author(s): Dr Marie DevlinORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Team-based capstones are a cornerstone of computing education, designed to prepare students for professional computing practice. The rapid adoption of Generative AI (GenAI) is reshaping how students plan, implement, test, and document their capstone work, raising new questions about workflows, team dynamics, assessment practices, and graduate readiness for using GenAI in the workplace. This Working Group (WG) investigates how GenAI is influencing capstone design and practice from the perspectives of students, early-career graduates, instructors, and employers. Using a mixed-methods approach, including a scoping literature review, cross-institutional surveys, and semi-structured interviews, the WG will examine how GenAI is currently integrated into capstone courses, how students use and perceive GenAI across the project lifecycle, how instructors are adapting task design, supervision, feedback, and assessment, and how employer expectations for GenAI competencies align with university preparation. The ultimate goal is to produce evidence-based guidance that helps educators realign capstone experiences with the realities of GenAIintegrated professional computing practice.
Author(s): Shakil A, Devlin M, Fitzpatrick K, Carruthers S, Gutica M, Howard R, Jackson S, Johnson C, Latorre E, Menezes T, Mertz J, Olupitan T, Potanin A, Westerman F
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: ITiCSE 2026: ACM Conference on Innovation and Technology in Computer Science Education
Year of Conference: 2026
Pages: 733-734
Print publication date: 09/07/2026
Online publication date: 09/07/2026
Acceptance date: 01/07/2026
Date deposited: 10/08/2026
Publisher: Association for Computing MachineryNew York NYUnited States
URL: https://doi.org/10.1145/3803401.3812046
DOI: 10.1145/3803401.3812046
