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Assessing student perceptions and use of instructor versus AI ‐generated feedback
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A Conceptual Framework for Human–AI Hybrid Adaptivity in Education
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Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky
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Student perceptions of assessment feedback: a critical scoping review and call for research
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Effects of different feedback strategies on academic achievements, learning motivations, and self-efficacy for novice programmers
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Evaluation of LLM Tools for Feedback Generation in a Course on Concurrent Programming
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Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties
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A systematic review of the role of learning analytics in enhancing feedback practices in higher education
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Peer feedback content and sender's competence level in academic writing revision tasks: Are they critical for feedback perceptions and efficiency?
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Computer-based feedback matters when relevant prior knowledge is not activated
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Facilitating Students’ Active Engagement with Feedback
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Effects of differential feedback on students’ examination performance.
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Feedback both helps and hinders learning: The causal role of prior knowledge.
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inferredcites →https://doi.org/10.1080/02602938.2016.1174187openalex-snapshot
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A Survey of Automated Assessment Approaches for Programming Assignments
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Understanding Instructor Immediacy, Credibility, and Facework Strategies Through a Qualitative Analysis of Written Instructor Feedback
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The Recent Development of Automated Programming Assessment
inferredcites →https://doi.org/10.1109/cist.2016.7805112openalex-snapshot
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Exploring the Potential of Large Language Models to Generate Formative Programming Feedback
inferredcites →https://doi.org/10.1109/icalt.2019.00061openalex-snapshot
An Analysis of the use of Good Feedback Practices in Online Learning Courses
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Enhancing syntax error messages appears ineffectual
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Code Quality Issues in Student Programs
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Introductory programming: a systematic literature review
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A Survey on Evaluation of Large Language Models
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Automatic graders for programming classes
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A multi-national, multi-institutional study of assessment of programming skills of first-year CS students
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inferredcites →https://doi.org/10.1186/s41239-024-00455-4openalex-snapshot
Feedback sources in essay writing: peer-generated or AI-generated feedback?
inferredcites →https://doi.org/10.1609/aaai.v38i21.30372openalex-snapshot
Students’ Perceptions and Preferences of Generative Artificial Intelligence Feedback for Programming
inferredcites →https://doi.org/10.25080/majora-92bf1922-011openalex-snapshot
Statsmodels: Econometric and Statistical Modeling with Python
inferredcites →https://doi.org/10.25080/majora-ebaa42b7-014openalex-snapshot
Proceedings of the 10th Python in Science Conference
inferredcites →https://doi.org/10.3389/fpsyg.2021.697045openalex-snapshot
Teacher Feedback Practices, Student Feedback Motivation, and Feedback Behavior: How Are They Associated With Learning Outcomes?
inferredcites →https://doi.org/10.4324/9780203074336openalex-snapshot
Feedback in Higher and Professional Education
inferredcites →https://doi.org/10.48550/arxiv.2401.11817openalex-snapshot
Hallucination is Inevitable: An Innate Limitation of Large Language Models
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The Impact of Multimedia Feedback in Blended Learning Environments on University Students’ Programming Skills
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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AI and Human Peer Feedback in Introductory Programming: A Mixed Methods Study
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How Generative AI Influences Learning Outcomes in Programming Education: A Three-level Bayesian Meta-analysis
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Aligning AI affordances with critical thinking skills in Chinese EFL: a discrepancy-based needs analysis for an AI-integrated blended reading module
inferred← citeshttps://doi.org/10.3389/fpsyg.2026.1871951openalex-snapshot
AI-peer integrated feedback in second language writing classes: exploring students’ engagement and writing performance
inferred← citeshttps://doi.org/10.3390/bs16071196openalex-snapshot
When Do Undergraduate Students Prefer AI? Insights into AI Scoring and Feedback
inferred← citeshttps://doi.org/10.3390/computers15100665openalex-snapshot
Generative-AI/LLM-Enabled E-Assessment in Higher Education: A Bibliometric Analysis of Research Trends, Collaboration Networks, and Thematic Evolution
inferred← citeshttps://doi.org/10.3390/educsci16060816openalex-snapshot
Can Generative AI Feedback Effectively Enhance Learning Outcomes? A Meta-Analysis of 36 Experimental and Quasi-Experimental Studies
inferred← citeshttps://doi.org/10.3390/electronics14214154openalex-snapshot
VClass Engager: A Generative AI-Based System for Enhancing Student Engagement in Synchronous Online Classes
inferred← citeshttps://doi.org/10.3390/higheredu4040059openalex-snapshot
Examining Student Perceptions of AI-Driven Learning: User Experience and Instructor Credibility in Higher Education
inferred← citeshttps://doi.org/10.3390/su18199801openalex-snapshot
Responsible Use of AI-Generated Feedback and Sustainable Learning Engagement Among Chinese University Students: A Dual-Path Model of Feedback Literacy and Feedback Dependence
inferred← citeshttps://doi.org/10.4018/979-8-3373-0122-8.ch015openalex-snapshot
A Systematic Review of Educators' Overreliance and Misuse of AI in Student Feedback
inferred← citeshttps://doi.org/10.4018/979-8-3373-5601-3.ch007openalex-snapshot
Comparing Teacher and ChatGPT Feedback in EFL/ESL Writing
inferred← citeshttps://doi.org/10.4018/979-8-3373-7579-3.ch011openalex-snapshot
AI-Supported Feedback for Writing
inferred← citeshttps://doi.org/10.53358/ezehzt04openalex-snapshot
Impacto educativo de la inteligencia artificial generativa:
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.