Mark Arinaitwe
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Mark Arinaitwe has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Emanuel S. Grant
School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA
1 shared publication - Qinxuan Shi
School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA
1 shared publication Reza Hassan
University of North Dakota
1 shared publication- Sicong Shao
University of North Dakota
1 shared publication
Latest Publications
- 2 September 2026
- Published by Springer Nature
- p. 484-497
Conceptualizing Trustworthiness of AI Systems
- Open Access
- 28 April 2025
- Published by MDPI AG in Engineering Proceedings
- Vol. 92 (1) , 26
Applying Artificial Intelligence in Software Development Education
Artificial intelligence (AI) is applied at a pace that challenges the verification of its suitability to the domains of application. This situation arises from the proliferation of AI development being conducted from a data science point of view rather than a software engineering approach. The situation leads to the question of whether software development course curricula are addressing the necessary educational needs for graduates to respond to the challenges of applying AI development in emerging domains. The challenge has two parts: the first is the use of AI in developing software systems, and the second is the development of AI systems. By looking at the first part of this challenge, we propose a pedagogy for introducing AI tools in software engineering education and structuring a methodology for AI application development to establish software engineering principles. This article is exploratory. We reviewed the existing literature to identify the commonalities of approaches to select a required set of topics, course outcomes, and structure for a curriculum on AI in software development.
- 28 April 2025
- Published by MDPI AG in Engineering Proceedings
- Vol. 92 (1) , 26
Open AccessApplying Artificial Intelligence in Software Development Education
Artificial intelligence (AI) is applied at a pace that challenges the verification of its suitability to the domains of application. This situation arises from the proliferation of AI development being conducted from a data science point of view rather than a software engineering approach. The situation leads to the question of whether software development course curricula are addressing the necessary educational needs for graduates to respond to the challenges of applying AI development in emerging domains. The challenge has two parts: the first is the use of AI in developing software systems, and the second is the development of AI systems. By looking at the first part of this challenge, we propose a pedagogy for introducing AI tools in software engineering education and structuring a methodology for AI application development to establish software engineering principles. This article is exploratory. We reviewed the existing literature to identify the commonalities of approaches to select a required set of topics, course outcomes, and structure for a curriculum on AI in software development.