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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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Teaching Students to Fix programming errors with Tutorials Embedded in an IDE 21

Teaching Students to Fix Programming Errors with Tutorials E...

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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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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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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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A New Look at Novice Programmer errors

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ACM TRANSACTIONS ON COMPUTING EDUCATION 2019年第4期19卷 1–30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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Implementing smart pump technology in a pediatric intensive care unit: A cost-effective approach

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INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2014年第2期83卷 99-105页

作者： Manrique-Rodriguez, Silvia Sanchez-Galindo, Amelia C. Lopez-Herce, Jesus Angel Calleja-Hernandez, Miguel Martinez-Martinez, Fernando Iglesias-Peinado, Irene Carrillo-Alvarez, Angel Sanjurjo-Saez, Maria Fernandez-Llamazares, Cecilia M. Hosp Gen Univ Gregorio Maranon Serv Farm Madrid 28007 Spain Hosp Gen Univ Gregorio Maranon Pediat Intens Care Unit Madrid 28007 Spain Hosp Univ Virgen de las Nieves Serv Pharm Granada 18014 Spain Univ Granada Fac Pharm E-18071 Granada Spain Univ Complutense Madrid Fac Pharm E-28040 Madrid Spain

Objective: To analyze the cost effectiveness of implementing smart infusion pump technology in a pediatric intensive care unit (PICU). Material and methods: An observational, prospective, intervention study with analytical components was carried out. A drug library was developed and integrated into the Carefusion Alaris Guardrails (R) infusion systems. A systematic analysis of all the data stored on the devices during use was performed by the data processing program Guardrails (R) CQI v4.1 Event Reporter. Intercepted errors were classified in terms of their potential severity and probability of causing an adverse effect (PAE) had they reached the patient. Knowing the estimated cost of a preventable adverse effect (AE), we analyzed costs saved and the profit/cost ratio resulting from the implementation process. Results: Compliance with the drug library was 92% and during the study period 92 infusion-related programming errors were intercepted, leading to a saving of 172,279 euros by preventing AEs. This means that 2.15 euros would be obtained for each euro invested in hiring a pharmacist to implement this technology. Discussion: The high percentage of use of safety software in our study compared to others allowed for the interception of 92 errors. The estimation of the potential impact of these errors is based on clinical judgment. The cost saved might be underestimated because the cost of an AE is usually higher in pediatrics, indirect and intangible costs were not considered and pharmacists involved do not spend the whole day on this task. Conclusions: Smart pumps have shown to be profitable in a PICU because they have the ability to intercept potentially serious medication errors and reduce costs associated with such errors. (C) 2013 Elsevier Ireland Ltd. All rights reserved.

关键词： Smart pumps Cost-effectiveness programming errors Safety Pediatric intensive care

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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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To Code Is Human

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IEEE SOFTWARE 2015年第1期32卷 14-17页

作者： Holzmann, Gerard J. Jet Prop Lab Pasadena CA 91109 USA

Programmers have found creative ways around programming rules. However, such tactics have a cost.

关键词： Encoding Software reliability Computer programs Software engineering Reliability engineering program processors software engineering computer programming programming errors compilers

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Implementation of smart pump technology in a paediatric intensive care unit

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HEALTH INFORMATICS JOURNAL 2015年第3期21卷 209-222页

作者： Manrique-Rodriguez, Silvia Sanchez-Galindo, Amelia C. de Lorenzo-Pinto, Ana Gonzalez-Vives, Leticia Lopez-Herce, Jesus Carrillo-Alvarez, Angel Sanjurjo-Saez, Maria Fernandez-Llamazares, Cecilia M. Gregorio Maranon Gen & Teaching Hosp Madrid 28007 Spain

Patient safety is a matter of major concern that involves every health professional. Nowadays, emerging technologies such as smart pumps can diminish medication errors as well as standardise and improve clinical practice with the subsequent benefits for patients. The aim of this paper was to describe the smart pump implementation process in a paediatric intensive care unit (PICU) and to present the most relevant infusion-related programming errors that were prevented. This was a comparative study between CareFusion Alaris Guardrails((R)) and Hospira MedNet((R)) systems, as well as a prospective and intervention study with analytical components carried out in the PICU of Gregorio Maranon General and Teaching Hospital. All intravenous infusions programmed with a pump in the eleven beds of the unit were analyzed. A drug library was developed and subsequently loaded into CareFusion and Hospira pumps that were used during a three month period each. The most suitable system for implementation was selected according to their differences in features and users' acceptance. Data stored in the pumps were analyzed to assess user compliance with the technology, health care setting and type of errors intercepted. The implementation process was carried out with CareFusion systems. Compliance with the technology was 92% and user acceptance was high. Vacation substitution and drug administration periods were significantly associated with a greater number of infusion-related programming errors. High risk drugs were involved in 48% of intercepted errors. Based on these results we can conclude that implementation of smart pumps proved effective in intercepting infusion-related programming errors from reaching patients. User awareness of the importance of programming infusions with the drug library is the key to succeed in the implementation process.

关键词： drug library intravenous administration programming errors safety smart pumps

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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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