Exploring the Role of Automated Feedback in Programming Education: A Systematic Literature Review

[2602.00089] Exploring the Role of Automated Feedback in Programming Education: A Systematic Literature Review Skip to main content Search Submit Donate Log in Computer Science > Computers and Society arXiv:2602.00089 (cs) This paper has been withdrawn by Unggi Lee [Submitted on 23 Jan 2026 ( v1 ), last revised 27 Aug 2026 (this version, v2)] Title: Exploring the Role of Automated Feedback in Programming Education: A Systematic Literature Review Authors: Yeonji Jung , Yunseo Lee , Jiyeong Bae , DoYong Kim , Heungsoo Choi , Minji Kang , Unggi Lee No PDF available, click to view other formats Abstract: Automated feedback systems have become increasingly integral to programming education, where learners engage in iterative cycles of code construction, testing, and refinement. Despite its wider integration in practices and technical advancements into AI, research in this area remains fragmented, lacking synthesis across technological and instructional dimensions. This systematic literature review synthesizes 61 empirical studies published by September 2024, offering a conceptually grounded analysis of automated feedback systems across five dimensions: system architecture, pedagogical function, interaction mechanism, contextual deployment, and evaluation approach. Findings reveal that most systems are fully automated, embedded within online platforms, and primarily focused on error detection and code correctness. While recent developments incorporate adaptive features and large language models to enable more personalized and interactive feedback, few systems offer support for higher-order learning processes, interactive components, or learner agency. Moreover, evaluation practices tend to emphasize short-term performance gains, with limited attention to long-term outcomes or instructional integration. These findings call for a reimagining of automated feedback not as a technical add-on for error correction, but as a pedagogical scaffold that supports deeper, adaptive, and interactive learning. Comments: The publisher's copyright agreement for the published version does not permit retention of this preprint on arXiv Subjects: Computers and Society (cs.CY) Cite as: arXiv:2602.00089 [cs.CY] (or arXiv:2602.00089v2 [cs.CY] for this version) https://doi.org/10.48550/arXiv.2602.00089 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Unggi Lee [ view email ] [v1] Fri, 23 Jan 2026 05:20:37 UTC (684 KB) [v2] Thu, 27 Aug 2026 00:13:27 UTC (1 KB) (withdrawn) Full-text links: Access Paper: Withdrawn Additional Features Audio Summary Current browse context: cs.CY < prev | next > new | recent | 2026-02 Change to browse by: cs References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from (opens in new tab) (opens in new tab) (opens in new tab)

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