Jul 2026· International Journal of Data Science and Analysis· Vol 22· 0 citations· 52 references
TL;DR
SchemaNet is introduced, a high-accuracy supervised model that detects student solution strategies via multi-view features, especially code schemas extracted at sub-problem granularity by the proposed SchemaMiner framework, and validated on a newly constructed, manually annotated dataset of 1,612 Python solutions.
Introductory programming courses face challenges to give scalable feedback on students’ understanding of core programming concepts. Automated grading shows whether code passes its test cases, but not the concept gaps behind the errors. Knowledge Tracing models target those concepts, but they demand extensive historical...
An LLM-based feedback analytics pipeline designed to transform students’ open-ended feedback into structured, actionable insights is proposed, ultimately supporting data-informed improvements in teaching and course management.
J. Jovanović, Irena Vodenska, V. Devedžić· Computer Science and Informa...· 0 citations
The adoption of large language models (LLMs) in software engineering has enabled the potential to automate complex activities such as requirements analysis. This paper presents an empirical performance analysis of four modern LLMs: GPT-4o, Aya, Gemma and Phi-4 on the task of automated classification of atomic software...
Nourchène Elleuch Ben Ayed, Jaber Jemai, Keletso J. Letsholo et al.· Journal of Information &...· 0 citations
Two novel contributions are introduced: CodeEval and CodeQual, an open-source execution framework that provides researchers with a ready-to-use evaluation pipeline for evaluating and improving LLMs in software engineering contexts, encompassing both functional correctness assessment and subjective code quality evaluati...
This work introduces RepoProbe, a novel benchmark for evaluating repository-level code understanding through open-ended Q&A using GitHub Discussions, which focuses on open-ended architectural inquiries rather than defect reporting and proposes a Checklist-Based Verification Protocol that decomposes answers into atomic,...
Experimental evaluation on 300 realistic pattern mining tasks demonstrates consistent improvements in algorithm configuration accuracy, parameter compliance, and dataset specification correctness across zero-shot, one-shot, and few-shot settings, highlighting the effectiveness of inference-time domain grounding for ena...
Madhavi Palla, Uday Kiran Rage, Arjun Chakravarthi Pogaku· International Journal of Dat...· 0 citations
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