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Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools

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arxiv 2412.14732 v1 pith:E5I4UVN5 submitted 2024-12-19 cs.CY cs.AIcs.HCcs.SE

classification cs.CYcs.AIcs.HCcs.SE
keywords genaitoolscomputingeducatorsliteratureprogrammingstudentssupport
verification ladder T0 review T1 audit T2 compute T3 formal
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Generative AI (GenAI) is advancing rapidly, and the literature in computing education is expanding almost as quickly. Initial responses to GenAI tools were mixed between panic and utopian optimism. Many were fast to point out the opportunities and challenges of GenAI. Researchers reported that these new tools are capable of solving most introductory programming tasks and are causing disruptions throughout the curriculum. These tools can write and explain code, enhance error messages, create resources for instructors, and even provide feedback and help for students like a traditional teaching assistant. In 2024, new research started to emerge on the effects of GenAI usage in the computing classroom. These new data involve the use of GenAI to support classroom instruction at scale and to teach students how to code with GenAI. In support of the former, a new class of tools is emerging that can provide personalized feedback to students on their programming assignments or teach both programming and prompting skills at the same time. With the literature expanding so rapidly, this report aims to summarize and explain what is happening on the ground in computing classrooms. We provide a systematic literature review; a survey of educators and industry professionals; and interviews with educators using GenAI in their courses, educators studying GenAI, and researchers who create GenAI tools to support computing education. The triangulation of these methods and data sources expands the understanding of GenAI usage and perceptions at this critical moment for our community.

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Cited by 3 Pith papers

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    In a Fall 2023 creative media course, a SPIRAL curriculum that delayed generative AI use until after domain skill practice was associated with higher creative media and GenAI use self-efficacy, demystification about A...

  2. Auto-grader Feedback Utilization and Its Impacts: An Observational Study Across Five Community Colleges

    cs.CY 2025-07 conditional novelty 4.0 of 10

    Students who checked auto-grader feedback more often earned higher assignment and resubmission scores, but the association may be driven by time spent and overall engagement.

  3. A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications

    cs.AI 2025-06 conditional novelty 4.0 of 10

    A survey of 80+ Deep Research systems that proposes a four-layer taxonomy (foundation models, tool use, planning, synthesis) and compares commercial and open-source implementations.

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