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30th IEEE Conference on Software Engineering Education and Training (CSEE&T)

作者： Scatalon, Lilian P. Prates, Jorge M. de Souza, Draylson M. Barbosa, Ellen F. Garcia, Rogerio E. Univ Sao Paulo ICMC Sao Carlos SP Brazil Sao Paulo State Univ FCT UNESP Presidente Prudente SP Brazil Mato Grosso Do Sul State Univ UEMS Nova Andradina MS Brazil

ISBN: (纸本)9781538625361

Software testing can be very helpful to students if adopted in programming assignments throughout the Computer Science curriculum. Many testing practices involve students writing their own test cases. This approach implies that students are responsible for the test design task while performing the test activity. On the other hand, some testing practices follow the opposite approach of providing ready-made test cases, so students only need to execute and evaluate test results for their solution code. In this paper, we investigated the effect of test design in student programming performance. We conducted an experiment comparing two different testing approaches during programming assignments: student-written and instructor-provided test cases. We also assessed students' perceptions of this subject by means of a survey. Results suggest that when students are responsible for test design, i.e. when they write their own test cases, they perform better in programming assignments.

关键词： Software Testing Test Design Student-written Tests Instructor-provided Tests programming assignments

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When Black-box Testing is Not Enough - on Designing Auto-graded programming assignments 20

When Black-box Testing is Not Enough - on Designing Auto-gra...

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51st ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Jin, Karen H. Charpentier, Michel Univ New Hampshire Dept Appl Engn & Sci Manchester NH 03101 USA Univ New Hampshire Dept Comp Sci Durham NH 03824 USA

ISBN: (纸本)9781450367936

Automatic programming assignment assessment is often premised on black-box testing. Grading of student submissions typically relies on functional specifications expressed in terms of expected outputs for given test inputs. Many upper-level courses, however, are centered on concepts that relate to how programs are implemented. In a course that teaches functional programming, for instance, the assignments should require that students use functional programming techniques, even if imperative solutions are supported by the language. When students are required to use certain programming language constructs, algorithms or design strategies as they implement their programs, a different approach to automated assessment is needed. Our strategy is centered on programming assignments designed in such a way that the internals of the assignment implementation can be evaluated through automated testing. A challenge of designing such auto-graded assignments is that both the specifications and the grading tests have a much higher level of complexity compared to plain functional specifications and black-box tests. The specification of a homework assignment must have precise requirements, but not prescribe a certain solution or impair student creativity. Furthermore, test cases should not inadvertently rely on implementation details that were not specified, but must be able to detect forbidden algorithms or language features. The benefits and difficulties of our approach are discussed in this work.

关键词： programming assignments automated assessment programming language

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Investigating the Essential of Meaningful Automated Formative Feedback for programming assignments

Investigating the Essential of Meaningful Automated Formativ...

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IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

作者： Hao, Qiang Wilson, Jack P. Ottaway, Camille Iriumi, Naitra Arakawa, Kai Smith, David H. Western Washington Univ Bellingham WA 98225 USA

ISBN: (纸本)9781728108100

This study investigated the essential of meaningful automated feedback for programming assignments. Three different types of feedback were tested, including (a) What's wrong - what test cases were testing and which failed, (b) Gap - comparisons between expected and actual outputs, and (c) Hint - hints on how to fix problems if test cases failed. 46 students taking a CS2 participated in this study. They were divided into three groups, and the feedback configurations for each group were different: (1) Group One - What's wrong, (2) Group Two - What's wrong + Gap, (3) Group Three - What's wrong + Gap + Hint. This study found that simply knowing what failed did not help students sufficiently, and might stimulate system gaming behavior. Hints were not found to be impactful on student performance or their usage of automated feedback. Based on the findings, this study provides practical guidance on the design of automated feedback.

关键词： automated feedback automated grading formative feedback programming assignments computing education controlled experiments

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Towards understanding the effective design of automated formative feedback for programming assignments

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COMPUTER SCIENCE EDUCATION 2022年第1期32卷 105-127页

作者： Hao, Qiang Smith, David H. Ding, Lu Ko, Amy Ottaway, Camille Wilson, Jack Arakawa, Kai H. Turcan, Alistair Poehlman, Timothy Greer, Tyler Western Washington Univ Comp Sci Bellingham WA 98225 USA Western Washington Univ SMATE Bellingham WA 98225 USA Eastern Illinois Univ Fac Dev & Innovat Ctr Charleston IL 61920 USA Univ Washington Informat Sch Seattle WA 98195 USA FDSST Publ Sch Denver CO USA

Background and Context: automated feedback for programming assignments has great potential in promoting just-in-time learning, but there has been little work investigating the design of feedback in this context. Objective: to investigate the impacts of different designs of automated feedback on student learning at a fine-grained level, and how students interacted with and perceived the feedback. Method: a controlled quasi-experiment of 76 CS students, where students of each group received a different combination of three types of automated feedback for their programming assignments. Findings: feedback addressing the gap between expected and actual outputs is critical to effective learning;feedback lacking enough details may lead to system gaming behaviors. Implications: the design of feedback has substantial impacts on the efficacy of automated feedback for programming assignments;more research is needed to extend what is known about effective feedback design in this context.

关键词： Automated feedback formative feedback programming assignments system gaming behavior

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Engaging programming assignments to Recruit and Retain CS0 Students 18

Engaging Programming Assignments to Recruit and Retain CS0 S...

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49th ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Sprint, Gina O'Fallon, Andy Gonzaga Univ Spokane WA 99258 USA Washington State Univ Pullman WA 99164 USA

ISBN: (纸本)9781450351034

Many universities offer an optional CS0 course taken prior to traditional CS1 and CS2 courses. Students enrolling in CS0 represent a variety of programming experience levels and majors. To more successfully recruit students to CS0 and retain students as CS majors, it is important to engage students in the course materials early on and frequently. There are several types of course materials (e.g. lesson notes, in class activities) and approaches to design engaging material (e.g. team-based learning, POGIL). In this poster, we focus on programming assignments that incorporate engagement practices put forth by the National Center for Women in Information Technology (NCWIT). NCWIT sponsors a program called EngageCSEdu, which is a collection of peer-reviewed introductory CS materials that are contributed by faculty. All materials in the database have demonstrated evidence of NCWIT"s engagement practices. In this poster, we present seven of our programming assignments that have been accepted into the EngageCSEdu database, two of which have won Engagement Excellence awards. The assignments cover the topics in a Python-based CS0 course at Washington State University. The poster presents the assignments, their learning outcomes, and their engagement practices. We include student commentary and examples of student submissions that demonstrate students" interest and creativity. Lastly, we present advertising materials we deployed that showcase the CS0 programming assignments to recruit more students to take the course. The assignments, student examples, and advertising efforts we present offer insights for educators about recruiting, engaging, and retaining students of all majors in introductory CS courses.

关键词： CS0 CS1 Python programming assignments NCWIT EngageCSEdu

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GRAD-AI: An automated grading tool for code assessment and feedback in programming course

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EDUCATION AND INFORMATION TECHNOLOGIES 2025年第7期30卷 9859-9899页

作者： Gambo, Ishaya Abegunde, Faith-Jane Gambo, Omobola Ogundokun, Roseline Oluwaseun Babatunde, Akinbowale Natheniel Lee, Cheng-Chi Obafemi Awolowo Univ Dept Comp Sci & Engn Ife 220282 Osun State Nigeria Lead City Univ Dept Arts & Social Sci Educ Ibadan 200005 Nigeria Kaunas Univ Technol Dept Software Engn LT-44249 Kaunas Lithuania Landmark Univ Dept Comp Sci Omu Aran 251103 Nigeria Tshwane Univ Technol TUT Dept Comp Syst Engn Pretoria South Africa Kwara State Univ Dept Comp Sci Malete 241103 Nigeria Fu Jen Catholic Univ Dept Lib & Informat Sci New Taipei City 24206 Taiwan Asia Univ Dept Comp Sci & Informat Engn Taichung 41354 Taiwan

The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading, timely feedback, and personalized support, enhancing the education process. This paper aims to develop "GRAD-AI," an automated grading tool for computer programming assignments. The objective is to overcome the limitations of manual grading by harnessing AI's capabilities to deliver accurate and timely assessments, thus creating a more interactive and supportive learning environment. The results show that GRAD-AI provides unbiased grading and timely and accurate feedback delivery for programming assignments by using the Halstead Complexity Measure, Term Frequency - Inverse Document Frequency Measure, Abstract Syntax Tree Process, and K-means Clustering. GRAD-AI marks a substantial stride in improving grading and feedback delivery within the education sector. Its real-time feedback provision and gap identification contribute to enhanced learning outcomes. As AI's role expands, integrating automated grading tools like GRAD-AI becomes crucial for fostering personalized learning and adaptability. The paper underscores AI's potential to revolutionize assessment and grading processes, supporting global students' growth and development.

关键词： Automated grading tool Feedback programming assignments Assessment Automated Manual Python programming Artificial intelligence Characteristic extraction K-means clustering Plagiarism detection User Interface

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A new automated grading approach for computer programming

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COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2013年第3期21卷 484-490页

作者： Liu, Xiong'en Fujian Agr & Forestry Univ Sch Comp & Informat Fuzhou 350002 Peoples R China

The current grading systems for computer programming assignments have taken correctness, efficiency, complexity, and maintainability into account. Of these four components, the most important measurement is the correctness. However, the existing grading systems still have some drawbacks. It is hard to measure college students' overall programming skills based only on their answers to a single form of programming questions. The author proposes a new approach by presenting multiple forms of computer programming questions, such as statement filling-in, program modifying and algorithm designing, and by providing an automated grading algorithm to measure the correctness, time efficiency, space efficiency, complexity, and robustness. This proposed automated grading method has been employed successfully in the development of C programming and Delphi programming exam systems for Computer Application Ability Exam for College Students in Fujian. It has also been applied to the development of an online programming self-testing system for Data Structure course which is offered by Fujian Agriculture and Forestry University. (c) 2010 Wiley Periodicals, Inc. Comput Appl Eng Educ 21: 484-490, 2013

关键词： automated grading programming assignments form of programming question paperless exam

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Towards Comprehensive Metrics for programming Cheat Detection 2024

Towards Comprehensive Metrics for Programming Cheat Detectio...

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55th ACM Technical Symposium on Computer Science Education (SIGCSE)

作者： Vahid, Frank Pang, Ashley Denzler, Benjamin Univ Calif Riverside Comp Sci & Engn Riverside CA 92521 USA

ISBN: (纸本)9798400704239

Automated assistance for detecting cheating on programs has long been investigated by CS educators, especially with the rise of "homework help" websites over the past decade, and recently with AI tools like ChatGPT. The main detection approach has long been flagging similar submission pairs. Modern cheating, like hiring contractors or using ChatGPT, may not yield such similarity. And, cases based on similarity alone may be weak. Thus, over the past several years, building on logs from an online program auto-grader (zyBooks), we developed additional "cheating concern metrics": points rate, style anomalies, style inconsistencies, IP address anomalies, code replacements, and initial copying. Most are defined not only for one programming assignment but also across a set of assignments. The metrics can help catch more kinds of cheating, provide more compelling evidence of cheating, reduce false cheating accusations based on similarity alone, and help instructors focus their limited cheat-detection time on the most egregious cases. We describe the techniques, and our experiences (via our own Python scripts and a commercial tool) for several terms, showing benefits of having more metrics than just similarity. Of 30 cheating cases over 3 terms and 300 students, most were based on metrics beyond similarity, all students admitted, none later contested, and time per student was only 1-2 hours (far less than previously). Our goal is to prevent cheating in the first place, by reducing opportunity via strong detection tools, as part of a multi-faceted approach to having students truly learn and stay out of trouble.

关键词： CS1 cheating plagiarism AI homework programming assignments

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OBSERVATIONS ON PLAGIARISM IN programming COURSES

OBSERVATIONS ON PLAGIARISM IN PROGRAMMING COURSES

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2nd International Conference on Computer Supported Education

作者： Kaucic, Branko Sraka, Dejan Ramsak, Maja Krasna, Marjan Univ Ljubjana Fac Educ Dept Math & Comp Sci Kardeljeva Ploscad 16 Ljubljana Slovenia Univ Maribor Fac Arts Maribor Slovenia

ISBN: (纸本)9789896740245

Plagiarism is a well known problem of today's society. Widespread of the internet, ease of data exchange, Bologna reforms and individual circumstances influence on students to resort to plagiarism. Many courses in computer science where students have programming assignments suffer from so called source code plagiarism. Beside the internet, most common origins of solved assignments are fellow students from the same or the previous generation. In this paper the source code plagiarism is discussed. Main results from observing the plagiarism in programming assignments are given showing to which extent students plagiarize.

关键词： Plagiarism Source code Teaching programming programming assignments

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Automatic Grading and Feedback using Program Repair for Introductory programming Courses 17

Automatic Grading and Feedback using Program Repair for Intr...

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ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Parihar, Sagar Dadachanji, Ziyaan Singh, Praveen Kumar Das, Rajdeep Karkare, Amey Bhattacharya, Arnab Indian Inst Technol Dept Comp Sci & Engn Kanpur Uttar Pradesh India

ISBN: (纸本)9781450347044

We present GradeIT, a system that combines the dual objectives of automated grading and program repairing for introductory programming courses (CS1). Syntax errors pose a significant challenge for testcase-based grading as it is difficult to differentiate between a submission that is almost correct and has some minor syntax errors and another submission that is completely off-the-mark. GradeIT also uses program repair to help in grading submissions that do not compile. This enables running testcases on submissions containing minor syntax errors, thereby awarding partial marks for these submissions (which, without repair, do not compile successfully and, hence, do not pass any testcase). Our experiments on 15613 submissions show that GradeIT results are comparable to manual grading by teaching assistants (TAs), and do not suffer from unintentional variability that happens when multiple TAs grade the same assignment. The repairs performed by GradeIT enabled successful compilation of 56% of the submissions having compilation errors, and resulted in an improvement in marks for 11% of these submissions.

关键词： CS1 programming assignments Automated Grading

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