The Evolving Usage of GenAI by Computing Students (2412.16453v1)

Abstract: Help-seeking is a critical aspect of learning and problem-solving for computing students. Recent research has shown that many students are aware of generative AI (GenAI) tools; however, there are gaps in the extent and effectiveness of how students use them. With over two years of widespread GenAI usage, it is crucial to understand whether students' help-seeking behaviors with these tools have evolved and how. This paper presents findings from a repeated cross-sectional survey conducted among computing students across North American universities (n=95). Our results indicate shifts in GenAI usage patterns. In 2023, 34.1% of students (n=47) reported never using ChatGPT for help, ranking it fourth after online searches, peer support, and class forums. By 2024, this figure dropped sharply to 6.3% (n=48), with ChatGPT nearly matching online search as the most commonly used help resource. Despite this growing prevalence, there has been a decline in students' hourly and daily usage of GenAI tools, which may be attributed to a common tendency to underestimate usage frequency. These findings offer new insights into the evolving role of GenAI in computing education, highlighting its increasing acceptance and solidifying its position as a key help resource.

The Evolving Usage of GenAI by Computing Students

The paper "The Evolving Usage of GenAI by Computing Students" provides an empirical investigation into the shifting patterns of help-seeking behaviors among computing students concerning generative AI tools. With a focus on the two-year timeframe covering the widespread adoption of Generative AI (GenAI) resources like ChatGPT, the research delineates notable trends in how these technologies are perceived and utilized by students within academic settings.

Key Findings

The paper employs a repeated cross-sectional survey methodology involving 95 computing students across various North American universities between 2023 and 2024. The results highlight a significant evolution in GenAI usage:

• Increased Adoption: There was a marked increase in the use of GenAI tools such as ChatGPT. By 2024, 93.75% of surveyed students reported at least monthly utilization of these tools, compared to 65.96% in 2023.
• Shift in Resource Preference: While GenAI tools were ranked fourth in terms of help-seeking preference in 2023, by 2024, they had moved to nearly match conventional online searches as the most frequently used resources.
• Reduction in Hourly Usage: Interestingly, although the overall adoption increased, there was a reported decline of 8.51% in hourly reliance on GenAI, potentially suggesting nuanced changes in usage patterns that may be influenced by factors such as the novelty effect or restrictions on usage limits by AI providers.

Implications

The transition in help-seeking preferences represents a substantial shift in educational and learning paradigms. The burgeoning reliance on GenAI tools suggests a movement towards personalized, instant assistance that these technologies offer. This has profound implications for computing education, potentially impacting:

1. Pedagogical Strategies: The growing integration of AI tools necessitates revisiting instructional strategies to align with contemporary help-seeking behaviors, including the potential shift from traditional pedagogical methods to more technology-mediated educational practices.
2. Resource Accessibility and Equity: The widespread access to AI tools could democratize learning resources. However, discrepancies in usage patterns, as observed, may indicate a digital divide or varying levels of confidence in technology among students that educators need to address.
3. Development of Critical Skills: As students increasingly leverage AI tools for immediate problem-solving assistance, there could be implications for the development of critical thinking and problem-solving skills traditionally honed through peer and instructor interactions.

Future Research Directions

The paper opens multiple avenues for further exploration:

• Longitudinal Analysis: Future studies could consider longitudinal research to follow the same cohort over time, providing deeper insights into the persistence of these trends and their impact on learning outcomes.
• Comparative Studies Across Disciplines: Beyond computing, examining whether similar trends are occurring in other disciplines could offer a more comprehensive understanding of AI's role in education.
• Impact on Cognitive and Metacognitive Skills: A deeper investigation into how GenAI influences cognitive processes, including metacognitive strategies and self-regulation among students, would be invaluable.

Despite its contributions, the paper is not without limitations, including its geographical focus and sample size. However, the findings remain a significant step toward understanding the integration of AI resources in education, providing actionable insights for researchers and educators aiming to harness the potential of GenAI to enhance learning experiences.