Computing Science Education on the AI Innovation Landscape

Ouldooz Baghban Karimi; Rebecca Robinson; Trevor Bonjour; Hannan Azhar; Mai Dahshan; Anuja Dharmaratne; Palak Halvadia; Elham E Khoda; Joyce Nakatumba Nabende; Syed Waqar Nabi; Andrea Salgian; Cigdem Sengul; Raja Sooriamurthi

doi:10.1145/3803401.3812053

Computing Science Education on the AI Innovation Landscape

Ouldooz Baghban Karimi
, Rebecca Robinson
, Trevor Bonjour
, Hannan Azhar
, Mai Dahshan
, Anuja Dharmaratne
, Palak Halvadia
, Elham E Khoda
, Joyce Nakatumba Nabende
, Syed Waqar Nabi
, Andrea Salgian
, Cigdem Sengul
, Raja Sooriamurthi

Simon Fraser University, Surrey, British Columbia, Canada
Department of Obstetrics and Gynaecology Monash University Clayton Victoria Australia
University of California San Diego, San Diego, IN, USA
Canterbury Christ Church University, Canterbury, England, United Kingdom
University of Virginia, Charlottesville, Virginia, USA
Faculty of IT, Monash University, Clayton, Victoria, Australia
University of Manchester, Manchester, England, United Kingdom
University of British Columbia, Vancouver, British Columbia, Canada
Makerere University, Makerere, Uganda
University of Glasgow, Glasgow, Scotland, United Kingdom
The College of New Jersey, Ewing, New Jersey, USA
Brunel University of London, London, United Kingdom
Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Recent advances in artificial intelligence (AI), including the widespread adoption of foundational models, have triggered changes across Computing Science (CS) programs. Developments include, but are not limited to, revisions to assessment practices, updates to academic integrity policies, curriculum redesign to integrate emerging concepts, and the growing use of conversational agents to support instruction. These developments aim to address effective preparation of graduates for an evolving AI innovation landscape.

The response of the CS education community over the past few years has been characterized by rapid experimentation, provisional deployments, and ad hoc adaptations. This work aims to move beyond a reactive response by synthesizing observations and experiences from students, educators, and industry stakeholders to identify key challenges, emerging patterns, and lessons learned. Drawing on the insights from this analysis and at a pivotal moment when institutions are shifting from exploratory adoption to long-term integration, we articulate recommendations and potential pathways to inform the sustainable and pedagogically grounded integration of AI in the future of CS education.

Original language	English
Title of host publication	ITiCSE 2026: Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 2
Place of Publication	New York
Publisher	ACM
Pages	783-784
ISBN (Electronic)	9798400726330
DOIs	https://doi.org/10.1145/3803401.3812053
Publication status	Published - 9 Jul 2026
Externally published	Yes

Keywords

Computing education
AI
Artificial inteligence

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10.1145/3803401.3812053Licence: CC BY-NC-ND

Cite this

Baghban Karimi, O., Robinson, R., Bonjour, T., Azhar, H., Dahshan, M., Dharmaratne, A., Halvadia, P., E Khoda, E., Nakatumba Nabende, J., Nabi, S. W., Salgian, A., Sengul, C., & Sooriamurthi, R. (2026). Computing Science Education on the AI Innovation Landscape. In ITiCSE 2026: Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 2 (pp. 783-784). ACM. https://doi.org/10.1145/3803401.3812053

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title = "Computing Science Education on the AI Innovation Landscape",

abstract = "Recent advances in artificial intelligence (AI), including the widespread adoption of foundational models, have triggered changes across Computing Science (CS) programs. Developments include, but are not limited to, revisions to assessment practices, updates to academic integrity policies, curriculum redesign to integrate emerging concepts, and the growing use of conversational agents to support instruction. These developments aim to address effective preparation of graduates for an evolving AI innovation landscape. The response of the CS education community over the past few years has been characterized by rapid experimentation, provisional deployments, and ad hoc adaptations. This work aims to move beyond a reactive response by synthesizing observations and experiences from students, educators, and industry stakeholders to identify key challenges, emerging patterns, and lessons learned. Drawing on the insights from this analysis and at a pivotal moment when institutions are shifting from exploratory adoption to long-term integration, we articulate recommendations and potential pathways to inform the sustainable and pedagogically grounded integration of AI in the future of CS education.",

keywords = "Computing education, AI, Artificial inteligence",

author = "\{Baghban Karimi\}, Ouldooz and Rebecca Robinson and Trevor Bonjour and Hannan Azhar and Mai Dahshan and Anuja Dharmaratne and Palak Halvadia and \{E Khoda\}, Elham and \{Nakatumba Nabende\}, Joyce and Nabi, \{Syed Waqar\} and Andrea Salgian and Cigdem Sengul and Raja Sooriamurthi",

year = "2026",

month = jul,

day = "9",

doi = "10.1145/3803401.3812053",

language = "English",

pages = "783--784",

booktitle = "ITiCSE 2026: Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 2",

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Baghban Karimi, O, Robinson, R, Bonjour, T, Azhar, H, Dahshan, M, Dharmaratne, A, Halvadia, P, E Khoda, E, Nakatumba Nabende, J, Nabi, SW, Salgian, A, Sengul, C & Sooriamurthi, R 2026, Computing Science Education on the AI Innovation Landscape. in ITiCSE 2026: Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 2. ACM, New York, pp. 783-784. https://doi.org/10.1145/3803401.3812053

Computing Science Education on the AI Innovation Landscape. / Baghban Karimi, Ouldooz; Robinson, Rebecca; Bonjour, Trevor et al.
ITiCSE 2026: Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 2. New York: ACM, 2026. p. 783-784.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Computing Science Education on the AI Innovation Landscape

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Keywords

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