Concept-Based Automated Grading of CS-1 Programming Assignments
Zhiyu Fan, Shin Hwei Tan, Abhik Roychoudhury
摘要
Due to the increasing enrolments in Computer Science programs, teaching of introductory programming needs to be scaled up. This places signi cant strain on teaching resources for programming courses for tasks such as grading of submitted programming assignments. Conventional attempts at automated grading of programming assignment rely on test-based grading which assigns scores based on the number of passing tests in a given test-suite. Since test-based grading may not adequately capture the student's understanding of the programming concepts needed to solve a programming task, we propose the notion of a concept graph which is essentially an abstracted control ow graph. Given the concept graphs extracted from a student's solution and a reference solution, we de ne concept graph matching and comparing of di ering concepts. Our experiments on 1540 student submissions from a publicly available dataset show the e cacy of concept-based grading vis-a-vis test-based grading. Speci cally, the concept based grading is (experimentally) shown to be closer to the grade manually assigned by the tutor. Apart from grading, the concept graph used by our approach is also useful for providing feedback to struggling students, as con rmed by our user study among tutors. CCS CONCEPTS • Applied computing → Computer-assisted instruction; • Software and its engineering → Software testing and debugging.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- Characterizing and Detecting Program Representation Faults of Static Analysis FrameworksHuaien Zhang, Yu Pei, Shuyun Liang, Zezhong Xing 等ISSTA 2024 · 被引用 2 次
- BRAFAR: Bidirectional Refactoring, Alignment, Fault Localization, and Repair for Programming AssignmentsLinna Xie, Chongmin Li, Yu Pei, Tian Zhang 等ISSTA 2024 · 被引用 1 次
相关 Paper
- ErrorCLR: Semantic Error Classification, Localization and Repair for Introductory Programming AssignmentsSiqi Han, Yu Wang, Xuesong LuSIGIR 2023 · 被引用 9 次
- Program equivalence for assisted grading of functional programsJoshua Clune, Vijay Ramamurthy, Ruben Martins, Umut A. AcarOOPSLA 2020 · 被引用 11 次
- Learning Interpretable Relationships between Entities, Relations and Concepts via Bayesian Structure Learning on Open Domain FactsJingyuan Zhang, Mingming Sun, Yue Feng, Ping LiACL 2020 · 被引用 6 次
- Giving Feedback on Interactive Student Programs with Meta-ExplorationEvan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech 等NeurIPS 2022 · 被引用 8 次
- Inductive Cognitive Diagnosis for Fast Student Learning in Web-Based Intelligent Education SystemsShuo Liu, Junhao Shen, Hong Qian, Aimin ZhouWWW 2024 · 被引用 35 次
