Jul 2026· Annual Conference on Innovation and Technology in Computer Science Education· 1 citation· 26 references
Computer Science
TL;DR
The findings suggest that the impact of GenAI use is present in various contexts, highlighting the need for instructional guidance on how students should use GenAI as a learning aid, and insights for other instructors that wish to integrate GenAI tools into computing curricula.
Abstract
Generative Artificial Intelligence (GenAI) tools are increasingly used by computing students, yet their effects on learning outcomes remain mixed. Prior work found that while GenAI use may improve performance on assignments, it can negatively relate to overall course performance. We aim to replicate and extend this work across four computing courses. Using self-reported GenAI usage from assignments and study preferences alongside course performance data, we examine how these relationships vary by course, and compared to the previous study. Our results show that students who used GenAI tools to solve the assignment performed equally or better than those who did not report using it, however, they received lower final grades in the course. We observe no major difference between students who used GenAI to study for the midterm test compared to those who did not. These findings suggest that the impact of GenAI use is present in various contexts, highlighting the need for instructional guidance on how students should use GenAI as a learning aid, and insights for other instructors that wish to integrate GenAI tools into computing curricula.
This paper presents the development and initial validation of an instrument to measure self-efficacy while using GenAI to learn programming, and finds strong support for the validity of the existing Steinhorst instrument in a new context, specifically an introductory programming course that fully integrates GenAI.
J. Prather, Lauren E. Margulieux, Yekaterina Kharitonova et al.· Proceedings of the 2026 ACM...· 0 citations
This research paper describes an initiative to supplement novice design knowledge with generative AI (genAI). Past studies show students feel they don’t have sufficient genAI knowledge and skills, and faculty are concerned about students’ ability to evaluate genAI. Although there is concern that students may become too reliant on genAI, research shows that genAI can support the development of and ultimately automate aspects of the engineering design process. This research identifies students’ perceptions of the use of genAI in engineering design courses. Building on the designer patterns described in Crismond and Adam’s Informed Design Learning and Teaching Matrix, this work explores genAI’s impact on engineering design. Findings show students are generally comfortable using genAI, they feel they are using it effectively, that it increases their quality of work and efficiency, and feel it enhances their creativity. Students reported mixed messages from instructors and concerns about ethical use, unfair advantage, and over-reliance.
N. Nelson, C. Rennick, Silas Ifeanyi· Proceedings of the Canadian...· 0 citations
The rapid expansion of artificial intelligence (AI) tools, including generative AI, is reshaping task completion and interaction, leading educational researchers to examine learning opportunities as well as emerging concerns in the present technological landscape. Despite ongoing discussions, it is less clear how students may envision such tools being integrated into computing education. We applied the Technology Acceptance Model and conducted a survey across three tertiary academic institutions in the United States, gathering quantitative and qualitative insights on n = 340 computing students' perspectives. Closed-ended items were examined with descriptive statistics, and an open-ended prompt around AI tool use in computing education was explored through reflexive thematic analysis. We found that 64.1% of students somewhat or strongly agreed that using AI tools (e.g., ChatGPT or GitHub Copilot) made them feel as though they were not truly doing the work themselves. Additionally, 48.8% of students somewhat or strongly agreed that they felt conflicted about using AI tools because competent computing/tech students should be able to figure things out without help. The qualitative themes spoke to instances where students may find adoption beneficial, like ''Expediting and enhancing learning, task completion, and organization,'' or problematic, such as ''Moral concerns and regard for social and environmental impact.'' Based on our results, we discuss strategies for teaching alongside AI tools and future considerations for computing educators and developers to support students' agency, ethical reasoning, and decision-making.
S. Lunn, Ashmita Thapaliya, Elodie V. Billionniere et al.· Annual Conference on Innovat...· 0 citations
It is found that there is no significant differential effect of GenAI availability on grades overall or among previously lower-performing students, and the findings temper concerns that GenAI inflates grades and reduces students's satisfaction.
J. Dumlao, Meng Wang, Zhonghan Xie et al.· 0 citations
Higher education has seen a significant shift towards using Generative Artificial Intelligence (GenAI), which has revolutionized student learning and behavior by significantly improving their ability to engage with information. The effects of Generative AI tools on academic libraries are investigated in a study conducted among undergraduate college students in Kashmir. Google Forms was employed to implement a questionnaire that provided measurable research findings. In the study, undergraduate students from degree colleges in Kashmir were observed to adopt and use Generative AI tools. The analysis of 172 valid responses was carried out using descriptive statistics, with the data being analysed using frequencies and percentages, and then presented in tables and figures.
The results show that many students are familiar with Generative AI tools and ChatGPT is the most popular plateform. Most of the students use Generative AI mainly for learning new concepts, studying to clear exams and doing homework. Additionally, students indicate that Generative AI can be beneficial in terms of improving learning efficiency and reducing time-wasting. Also, most respondents believed that academic libraries should be a key factor in improving literacy on AI by providing instruction and knowledge about the responsible and ethical use of Generative AI technologies.
The study suggests that academic libraries should enhance their AI literacy programmes and user education programmes to address the growing presence of Generative AI in student academic activities. The outcomes provide valuable information for librarians, teachers, and policy makers on how to make the use of Generative AI more responsibly in higher education.
Shakir Ahmad Dar, Fajar ul Islam Malla· International Journal of Inn...· 0 citations
The rapid influx of generative artificial intelligence (GenAI) into higher education has resulted in a large number of research studies over the past three years. Much of the research to date has focused on the researcher/educator perspective of the optimal usage, benefits and challenges in the implementation of GenAI, often in a very general sense. The importance of the student voice and discipline-specific results must not be lost in this debate. This study investigates students’ decisions to use (or not use) GenAI for mathematics purposes and the reasons they give to support this choice. This was done by surveying almost 700 students in an Irish university, using an online, anonymous survey in March 2025. The students in the sample were all studying at least one mathematics module at the time. In addition, students were asked what they perceive the benefits and challenges to be of GenAI for mathematics in higher education. 91% of respondents were using GenAI for mathematics purposes. Both their reasons for using GenAI and the benefits they perceived for it fell into four main themes: Self-Improvement, Tools, Access, and Support. Their reasons for not using GenAI, and the challenges they perceived, were categorised under Unnecessary/Unknown, Inaccurate, Skill Loss, and Ethical Concerns. Students mentioned using GenAI for self-improvement reasons, such as bettering their understanding of mathematics, and found the lack of interaction with a person to be a benefit rather than a challenge. This study was conducted at a unique moment in time when the usage of GenAI was moving from sporadic to widespread and reflects students’ self-reported reasons for this.
E. Ní Fhloinn, Conor Feeney· Education sciences· 1 citation
