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21st Koli Calling Conference on Computing Education Research (Koli Calling)

作者： Kiljunen, Olli Aalto Univ Espoo Finland

ISBN: (纸本)9781450384889

While modern software development tools provide programmers with features that help locating and fixing errors in the code, using these tools is not necessarily easy for novice programmers. We call for methods of instruction that teach students how to fix errors in practice using a modern, industry-grade, IDE. We suggest an approach-utilizing tutorials embedded in an IDE-that we think could be suitable for this purpose. Our ongoing and future work include implementing and evaluating that approach.

关键词： programming errors debugging programming tools

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Qualitative Content Analysis of programming errors 17

Qualitative Content Analysis of Programming Errors

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5th International Conference on Information and Education Technology (ICIET)

作者： Shah, Philipp Berges, Marc Hubwieser, Peter Tech Univ Munich Arcisstr 21 D-80333 Munich Germany

ISBN: (纸本)9781450348034

In computer science education, the analysis of source code with errors is of interest as programming errors may give a hint to misconceptions. The analysis of misconceptions can help teachers to improve their exercises and lessons. The semantic analysis of texts or video sequences could lead to different, subjective interpretation. This problem also effects source code errors, which could contain semantic errors. In different projects, we were confronted with a lot of incorrect source codes, which were written by students of universities and secondary schools. A first analysis of these errors led to a categorization of errors regarding missing competencies. To avoid mainly subjective interpretation of source code errors a standardized method for categorizing errors, which could also be applied by a practitioner, has to be developed and justified. Categorizing texts or source code errors is a matter of semantics, because text or code elements have to be interpreted. Thus, a qualitative content analysis is most suitable. In this paper we explain the difference between errors and misconceptions and present our adaption of the qualitative content analysis of Mayring to source code errors.

关键词： Misconceptions programming errors source code errors content analysis qualitative research method error categorization

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Investigating the Role of errors in programming Learning 29

Investigating the Role of Errors in Programming Learning

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29th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Sha, Alyssa Shuang Nunes, Bernardo Pereira Shen, Jiayi Australian Natl Univ Canberra ACT Australia

ISBN: (纸本)9798400706035

Computer science students often perceive programming errors as weaknesses rather than learning opportunities, resulting in frustration, anxiety, and dropout. This study investigates how early programming errors can contribute to students' subsequent learning. We hypothesise that a certain number of errors made by students in the initial learning stage, which is distinct across different learning concepts, can enhance their future learning. Our hypothesis is tested using a real-world dataset consisting of 601 programming questions that were practised by 632 students. Additionally, we conduct a comprehensive clustering analysis on the error curves of students, revealing optimal error thresholds in various programming concepts. This approach brings novel perspectives on the significant role of "errors" in computer science education.

关键词： programming errors curve analysis

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Exploring the Effectiveness of Data-Driven Learning Materials for Promoting Student Performance in Introductory programming

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IEEE ACCESS 2024年 12卷 125170-125178页

作者： Qian, Yizhou Wu, Yifei Jiangnan Univ Dept Educ Technol Wuxi 214122 Peoples R China Jiangnan Univ Jiangsu Res Ctr Internet Plus Educ Wuxi 214122 Peoples R China

Cryptic and ambiguous error messages provided by programming environments are crucial barriers to beginners when learning to program. This study designed a coding manual to explain common Python programming errors to students using a data-driven approach, following guidelines suggested by prior studies. A quasi-experiment with two groups of middle school students was conducted to examine the effectiveness of the coding manual in reducing student errors, increasing confidence, and promoting learning performance. By analyzing 6015 erroneous student programs collected by the automated assessment tool (AAT) Mulberry, we found that the experimental group who used the coding manual during learning did not make fewer language specification errors (LSEs) in general. However, for LSEs indicating the actual errors in the program, the coding manual showed significant effects in reducing error frequencies. We also found that the coding manual failed to increase students' confidence in programming and promote learning performance. Possible causes of the ineffectiveness may include high cognitive loads during programming, the productivity of learning from the debugging process, and the incompleteness of the explanations and examples in the coding manual. We recommend that computer programming instructors use AATs or similar tools to collect learning data and identify students' common errors, directly explain identified common LSEs in class, and explicitly teach debugging methods and strategies. Future research should focus on students' self-regulation during programming, better methods of explaining common errors to novices, and the long-term effects of using a coding manual on students' learning in introductory programming.

关键词： Codes Encoding programming profession Python Manuals programming environments Syntactics Data models Data-driven learning materials introductory programming programming errors

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Decoding Logic errors: A Comparative Study on Bug Detection by Students and Large Language Models 24

Decoding Logic Errors: A Comparative Study on Bug Detection ...

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26th Australasian Computing Education Conference (ACE)

作者： MacNeil, Stephen Denny, Paul Tran, Andrew Leinonen, Juho Bernstein, Seth Hellas, Arto Sarsa, Sami Kim, Joanne Temple Univ Philadelphia PA 19122 USA Univ Auckland Auckland New Zealand Aalto Univ Espoo Finland

ISBN: (纸本)9798400716195

Identifying and resolving logic errors can be one of the most frustrating challenges for novices programmers. Unlike syntax errors, for which a compiler or interpreter can issue a message, logic errors can be subtle. In certain conditions, buggy code may even exhibit correct behavior - in other cases, the issue might be about how a problem statement has been interpreted. Such errors can be hard to spot when reading the code, and they can also at times be missed by automated tests. There is great educational potential in automatically detecting logic errors, especially when paired with suitable feedback for novices. Large language models (LLMs) have recently demonstrated surprising performance for a range of computing tasks, including generating and explaining code. These capabilities are closely linked to code syntax, which aligns with the next token prediction behavior of LLMs. On the other hand, logic errors relate to the runtime performance of code and thus may not be as well suited to analysis by LLMs. To explore this, we investigate the performance of two popular LLMs, GPT-3 and GPT-4, for detecting and providing a novice-friendly explanation of logic errors. We compare LLM performance with a large cohort of introductory computing students (.. = 964) solving the same error detection task. Through a mixed-methods analysis of student and model responses, we observe significant improvement in logic error identification between the previous and current generation of LLMs, and find that both LLM generations significantly outperform students. We outline how such models could be integrated into computing education tools, and discuss their potential for supporting students when learning programming.

关键词： large language models generative AI programming errors bug detection computing education

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What makes a programming error message good? 22

What makes a programming error message good?

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4th Conference on United Kingdom and Ireland Computing Education Research (UKICER)

作者： Santos, Eddie Antonio Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450397421

programming error messages (PEMs) often prove to be troublesome for novice programmers. Guidelines to improve PEMs often lack theoretical or empirical justification. This research will establish a theoretical foundation for what makes a "good" PEM, based on existing theories that have not yet been applied to PEMs. These findings will be applied to an existing programming environment and result in empirically-validated advice for language implementers.

关键词： Compilers Compiler Error Messages Computer Science Education Computing Education CS1 Error Messages HCI Human Factors Human Computer Interaction Novice Programmers programming errors programming Error Messages programming Languages Software Engineering Syntax errors

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Compiler Error Messages Considered Unhelpful: The Landscape of Text-Based programming Error Message Research 19

Compiler Error Messages Considered Unhelpful: The Landscape ...

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24th ACM Working Group Reports Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE-WGR)

作者： Becker, Brett A. Denny, Paul Pettit, Raymond Bouchard, Durell Bouvier, Dennis J. Harrington, Brian Kamil, Amir Karkare, Amey McDonald, Chris Osera, Peter-Michael Pearce, Janice L. Prather, James Univ Coll Dublin Dublin Ireland Univ Auckland Auckland New Zealand Univ Virginia Charlottesville VA USA Roanoke Coll Roanoke VA USA Southern Illinois Univ Edwardsville Edwardsville IL USA Univ Toronto Scarborough Scarborough ON Canada Univ Michigan Ann Arbor MI 48109 USA Indian Inst Technol Kanpur Kanpur Uttar Pradesh India Univ Western Australia Perth WA Australia Grinnell Coll Grinnell IA 50112 USA Berea Coll Berea KY USA Abilene Christian Univ Abilene TX 79699 USA

ISBN: (纸本)9781450375672

Diagnostic messages generated by compilers and interpreters such as syntax error messages have been researched for over half of a century. Unfortunately, these messages which include error, warning, and run-time messages, present substantial difficulty and could be more effective, particularly for novices. Recent years have seen an increased number of papers in the area including studies on the effectiveness of these messages, improving or enhancing them, and their usefulness as a part of programming process data that can be used to predict student performance, track student progress, and tailor learning plans. Despite this increased interest, the long history of literature is quite scattered and has not been brought together in any digestible form. In order to help the computing education community (and related communities) to further advance work on programming error messages, we present a comprehensive, historical and state-of-the-art report on research in the area. In addition, we synthesise and present the existing evidence for these messages including the difficulties they present and their effectiveness. We finally present a set of guidelines, curated from the literature, classified on the type of evidence supporting each one (historical, anecdotal, and empirical). This work can serve as a starting point for those who wish to conduct research on compiler error messages, runtime errors, and warnings. We also make the bibtex file of our 300+ reference corpus publicly available. Collectively this report and the bibliography will be useful to those who wish to design better messages or those that aim to measure their effectiveness, more effectively.

关键词： compiler error messages considered harmful CS1 CS-1 design guidelines diagnostic error messages error messages human computer interaction HCI introduction to programming novice programmers programming errors programming error messages review run-time errors survey syntax errors warnings

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A New Look at Novice Programmer errors

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ACM TRANSACTIONS ON COMPUTING EDUCATION 2019年第4期19卷 38-38页

作者： McCall, Davin Kolling, Michael Kings Coll London London WC2R 2LS England

The types of programming errors that novice programmers make and struggle to resolve have long been of interest to researchers. Various past studies have analyzed the frequency of compiler diagnostic messages. This information, however, does not have a direct correlation to the types of errors students make, due to the inaccuracy and imprecision of diagnostic messages. Furthermore, few attempts have been made to determine the severity of different kinds of errors in terms other than frequency of occurrence. Previously, we developed a method for meaningful categorization of errors, and produced a frequency distribution of these error categories;in this article, we extend the previous method to also make a determination of error difficulty, in order to give a better measurement of the overall severity of different kinds of errors. An error category hierarchy was developed and validated, and errors in snapshots of students source code were categorized accordingly. The result is a frequency table of logical error categories rather than diagnostic messages. Resolution time for each of the analyzed errors was calculated, and the average resolution time for each category of error was determined;this defines an error difficulty score. The combination of frequency and difficulty allow us to identify the types of error that are most problematic for novice programmers. The results show that ranking errors by severity-a product of frequency and difficulty-yields a significantly different ordering than ranking them by frequency alone, indicating that error frequency by itself may not be a suitable indicator for which errors are actually the most problematic for students.

关键词： programming errors novice programmers Java

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Towards Deriving programming Competencies from Student errors 4

Towards Deriving Programming Competencies from Student Error...

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4th International Conference on Learning and Teaching in Computing and Engineering (LaTICE)

作者： Berges, Marc Striewe, Michael Shah, Philipp Goedicke, Michael Hubwieser, Peter Tech Univ Munich TUM Sch Educ Arcisstr 21 D-80333 Munich Germany Univ Duisburg Essen Ruhr Inst Software Technol Gerlingstr 16 D-45127 Essen Germany

ISBN: (纸本)9781509025046

Learning outcomes are more and more defined and measured in terms of competencies. Many research projects are conducted that investigate combinations of knowledge and skills that students might learn. Yet, it is also promising to analyze what students might fail to learn, which provides information about the absence of certain competencies. For this purpose, we are evaluating the outcomes of automatic assessment tools that provide automatic feedback to the participating students. In particular, we analyzed the errors of the students that participated in an introductory programming course. The 604 students participating in the course had to solve six tasks during the semester, resulting in a total of 12274 submissions. The error analysis is done by evaluating the data from the automatic assessment tool JACK, which provides automatic feedback on programming tasks. To derive information about prospective competencies, we conducted a qualitative analysis of the different errors the students made in their solutions. The results provide interesting insights into missing competencies. In further research our findings have to be validated by investigating the cognitive processes involved during programming.

关键词： Electronic assessment programming competence programming errors Qualitative text analysis

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Static analysis of source code written by novice programmers 8

Static analysis of source code written by novice programmers

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8th IEEE Global Engineering Education Conference (EDUCON)

作者： Delev, Tomche Gjorgjevikj, Dejan Ss Cyril & Methodius Univ Fac Comp Sci & Engn Skopje North Macedonia

ISBN: (纸本)9781509054671

In this paper we are reporting the finding on the use of a static analysis of C source code written by students learning to program. Two different tools for static code analysis were used to analyze the solutions submitted by the students on the partial exams and exams from the introductory course in programming in a three year period. We have collected, analyzed and compared most common errors reported by both tools. We further investigate if the available checks provided by these tools, often used in professional software development practices to find bugs and improve the code quality, can also help novice programmers in tracking down and resolving their problems in the code or have any other value in the process of learning programming.

关键词： static analysis novice programmers programming errors

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