Leveraging Generative Artificial Intelligence to Broaden Participation in Computer Science (original) (raw)
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Computing Education in the Era of Generative AI
arXiv (Cornell University), 2023
The computing education community has a rich history of pedagogical innovation designed to support students in introductory courses, and to support teachers in facilitating student learning. Very recent advances in artificial intelligence have resulted in code generation models that can produce source code from natural language problem descriptions-with impressive accuracy in many cases. The wide availability of these models and their ease of use has raised concerns about potential impacts on many aspects of society, including the future of computing education. In this paper, we discuss the challenges and opportunities such models present to computing educators, with a focus on introductory programming classrooms. We summarize the results of two recent articles, the first evaluating the performance of code generation models on typical introductory-level programming problems, and the second exploring the quality and novelty of learning resources generated by these models. We consider likely impacts of such models upon pedagogical practice in the context of the most recent advances at the time of writing. CCS CONCEPTS • Social and professional topics → Computing education; • Computing methodologies → Artificial intelligence.
Journal of University Teaching and Learning Practice, 2023
The global higher education sector has been significantly disrupted by the proliferation of generative artificial intelligence tools such as ChatGPT, especially in relation to its implications for assessment. However, few studies to date have explored student perspectives on these tools. This article reports on one of the first large-scale quantitative studies of student views on generative artificial intelligence at an Australian university (n = 1,135). When the survey was conducted, most students had low knowledge, experience, and confidence in using these tools. These results varied across disciplines and across some student sub-groups, such as mature-age students and international students. Confidence appeared to increase with experience, although the data also revealed a portion of students that have never used these tools yet still felt confident in using them. In exploring these results, this article aims to shed new light on this fast-evolving landscape and inform the future direction of supporting students to engage with generative artificial intelligence tools appropriately.
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With the advent of large language models like ChatGPT, there is interest in leveraging these tools as teaching assistants in higher education. However, important questions remain regarding the effectiveness and appropriateness of AI systems in educational settings. This study evaluated ChatGPT's potential as a teaching assistant for an introductory programming course. We conducted an experimental study where ChatGPT was prompted in response to common student questions and misconceptions from a first-year programming course. This study was conducted over a period of 2 weeks with 20 undergraduate students and 5 faculty members from the department of computer science. ChatGPT's responses were evaluated along several dimensions-accuracy, completeness, pedagogical soundness, and the ability to resolve student confusion by five course faculties through a survey. Additionally, another survey was administered to students in the course to assess their perception of ChatGPT's usefulness after interacting with the tool. The findings suggested that while ChatGPT demonstrated strengths in explaining introductory programming concepts accurately and completely, it showed weaknesses in resolving complex student confusion, adapting responses to individual needs, and providing tailored debugging assistance. This study highlighted key areas needing improvement and provided a basis to develop responsible integration strategies that harness AI to enrich rather than replace human instruction in technical courses. The results, based on the limited sample size and study duration, indicated that ChatGPT has potential as a supplemental teaching aid for core concepts, but also highlighted areas where human instruction may be particularly valuable, such as providing advanced support. Further research with larger 166 STEM Education Volume 4, Issue 3, 165-182 samples and longer study periods is needed to assess the generalizability of these findings.
arXiv (Cornell University), 2022
The introductory programming sequence has been the focus of much research in computing education. The recent advent of several viable and freely-available AI-driven code generation tools present several immediate opportunities and challenges in this domain. In this position paper we argue that the community needs to act quickly in deciding what possible opportunities can and should be leveraged and how, while also working on how to overcome or otherwise mitigate the possible challenges. Assuming that the effectiveness and proliferation of these tools will continue to progress rapidly, without quick, deliberate, and concerted efforts, educators will lose advantage in helping shape what opportunities come to be, and what challenges will endure. With this paper we aim to seed this discussion within the computing education community.
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