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检索条件"主题词=programming process data"

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On the Opportunities of Large Language Models for programming process data 25

On the Opportunities of Large Language Models for Programmin...

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Proceedings of the 27th Australasian Computing Education Conference

作者： John Edwards Arto Hellas Juho Leinonen Computer Science Utah State University Utah USA Aalto University Espoo Finland

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ProgSnap2: A Flexible Format for programming process data 20

ProgSnap2: A Flexible Format for Programming Process Data

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25th Conference on Innovation and Technology in Computer Science Education

作者： Price, Thomas W. Hovemeyer, David Rivers, Kelly Gao, Ge Bart, Austin Cory Kazerouni, Ayaan M. Becker, Brett A. Petersen, Andrew Gusukuma, Luke Edwards, Stephen H. Babcock, David North Carolina State Univ Raleigh NC 27695 USA Johns Hopkins Univ Baltimore MD USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Delaware Newark DE USA Virginia Tech Blacksburg VA USA Univ Coll Dublin Dublin Ireland Univ Toronto Toronto ON Canada York Coll Penn Jamaica NY USA

ISBN: (纸本)9781450368742

In this paper, we introduce ProgSnap2, a standardized format for logging programming process data. ProgSnap2 is a tool for computing education researchers, with the goal of enabling collaboration by helping them to collect and share data, analysis code, and data-driven tools to support students. We give an overview of the format, including how events, event attributes, metadata, code snapshots and external resources are represented. We also present a case study to evaluate how ProgSnap2 can facilitate collaborative research. We investigated three metrics designed to quantify students' difficulty with compiler errors-the Error Quotient, Repeated Error Density and Watwin score-and compared their distributions and ability to predict students' performance. We analyzed five different ProgSnap2 datasets, spanning a variety of contexts and programming languages. We found that each error metric is mildly predictive of students' performance. We reflect on how the common data format allowed us to more easily investigate our research questions.

关键词： compiler error metrics data sharing programming process data

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Exploring Novice programming Behavior over Time 21

Exploring Novice Programming Behavior over Time

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26th Conference on Innovation and Technology in Computer Science Education

作者： Karvelas, Ioannis Dillane, Joe Becker, Brett A. Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450383974

This work focuses on the effect that programming time has on novice programmers' interaction with two versions of the BlueJ programming environment that differ in compilation mechanism and error message presentation. We utilize programming process data from users of both BlueJ versions, and those who used each one exclusively. Results indicate there is a threshold of approximately twenty hours of programming below and above which compilation and error message frequency changes. This indicates that being exposed to an environment for prolonged time can influence the programming interaction between novices and environments. This phenomenon is not yet understood.

关键词： Blackbox BlueJ compiler error messages CS1 environments novice programmers programming programming process data

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programming Versus Natural Language: On the Effect of Context on Typing in CS1 20

Programming Versus Natural Language: On the Effect of Contex...

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ACM Conference on International Computing Education Research (ICER)

作者： Edwards, John Leinonen, Juho Birthare, Chetan Zavgorodniaia, Albina Hellas, Arto Utah State Univ Logan UT 84322 USA Univ Helsinki Helsinki Finland Aalto Univ Espoo Finland

ISBN: (纸本)9781450370929

Analyzing keystroke data from students working on essay and programming tasks, we study to what extent the difference in task context influences performance in typing. Using data from two introductory programming courses offered at two separate institutions, we compare and contrast typing speed between programming and natural language tasks. We observe that students tend to be faster at typing (the same) character pairs when writing natural language text than when learning to write code. We show that students improve on typing character pairs that appear in frequently used words in programming languages, and that typing programming constructs also improves. We find that students are faster at detecting and erasing their mistakes when typing natural language text than when programming. Our results support theories regarding contextual memory, procedural memory, and practice, and have implications for course curriculum and pedagogy design.

关键词： keystroke data context digraphs programming process data

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Investigating Novice Programmers' Interaction with programming Environments 19

Investigating Novice Programmers' Interaction with Programmi...

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

作者： Karvelas, Ioannis Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450363013

Learning computer programming can be challenging for novices. Students have to deal with theoretical aspects of programming and problem solving in general, as well as mastering the syntax of a programming language. However, the feedback students receive from programming environments such as compiler error messages can be problematic. This work is aimed at better understanding the impact of these feedback mechanisms and working towards designing improved "novice-friendly" programming feedback to inform the development of pedagogical environments.

关键词： compiler error messages CS1 educational data mining novice programmers programming programming process data

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A Study of Keystroke data in Two Contexts: Written Language and programming Language Influence Predictability of Learning Outcomes 20

A Study of Keystroke Data in Two Contexts: Written Language ...

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

作者： Edwards, John Leinonen, Juho Hellas, Arto Utah State Univ Logan UT 84322 USA Univ Helsinki Helsinki Finland Aalto Univ Espoo Finland

ISBN: (纸本)9781450367936

We study programming process data from two introductory programming courses. Between the course contexts, the programming languages differ, the teaching approaches differ, and the spoken languages differ. In both courses, students' keystroke data - timestamps and the pressed keys - are recorded as students work on programming assignments. We study how the keystroke data differs between the contexts, and whether research on predicting course outcomes using keystroke latencies generalizes to other contexts. Our results show that there are differences between the contexts in terms of frequently used keys, which can be partially explained by the differences between the spoken languages and the programming languages. Further, our results suggest that programming process data that can be collected non-intrusive in-situ can be used for predicting course outcomes in multiple contexts. The predictive power, however, varies between contexts possibly because the frequently used keys differ between programming languages and spoken languages. Thus, context-specific fine-tuning of predictive models may be needed.

关键词： keystroke analysis digraphs keystroke data programming process data predicting performance educational data mining

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Pausing While programming: Insights From Keystroke Analysis 44

Pausing While Programming: Insights From Keystroke Analysis

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ACM/IEEE 44th International Conference on Software Engineering - Software Engineering Education and Training (ICSE-SEET)

作者： Shrestha, Raj Leinonen, Juho Zavgorodniaia, Albina Hellas, Arto Edwards, John Utah State Univ Logan UT 84322 USA Aalto Univ Espoo Finland

ISBN: (纸本)9781665495929

Pauses in typing are generally considered to indicate cognitive processing and so are of interest in educational contexts. While much prior work has looked at typing behavior of Computer Science students, this paper presents results of a study specifically on the pausing behavior of students in Introductory Computer programming. We investigate the frequency of pauses of different lengths, what last actions students take before pausing, and whether there is a correlation between pause length and performance in the course. We find evidence that frequency of pauses of all lengths is negatively correlated with performance, and that, while some keystrokes initiate pauses consistently across pause lengths, other keystrokes more commonly initiate short or long pauses. Clustering analysis discovers two groups of students, one that takes relatively fewer mid-to-long pauses and performs better on exams than the other.

关键词： pauses pausing breaks keystroke data digraphs programming process data

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Plagiarism in Take-home Exams: Help-seeking, Collaboration, and Systematic Cheating 17

Plagiarism in Take-home Exams: Help-seeking, Collaboration, ...

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

作者： Hellas, Arto Leinonen, Juho Ihantola, Petri Univ Helsinki Dept Comp Sci Helsinki Finland Tampere Univ Technol Dept Pervas Comp Tampere Finland

ISBN: (纸本)9781450347044

Due to the increased enrollments in Computer Science education programs, institutions have sought ways to automate and streamline parts of course assessment in order to be able to invest more time in guiding students' work. This article presents a study of plagiarism behavior in an introductory programming course, where a traditional pen-and-paper exam was replaced with multiple take-home exams. The students who took the take-home exam enabled a software plugin that recorded their programming process. During an analysis of the students' submissions, potential plagiarism cases were highlighted, and students were invited to interviews. The interviews with the candidates for plagiarism highlighted three types of plagiarism behaviors: help-seeking, collaboration, and systematic cheating. Analysis of programming process traces indicates that parts of such behavior are detectable directly from programming process data.

关键词： plagiarism programming process data educational data mining

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Sympathy for the (Novice) Developer: programming Activity When Compilation Mechanism Varies 2022

Sympathy for the (Novice) Developer: Programming Activity Wh...

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53rd Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Karvelas, Ioannis Becker, Brett A. Univ Coll Dublin Dublin Ireland

ISBN: (纸本)9781450390705

In this work we investigate compilation behavior and error resolution time of thousands of novice programmers using two different versions of the BlueJ pedagogical Java programming environment. The two versions feature different compilation and error message presentation mechanisms. BlueJ 3 is a click-to-compile environment with enforced first error message presentation whereas BlueJ 4 features automatic compilation and on-demand error message presentation. We provide an overview of compilation activity based on novices' programming time spent in different compilation states and also present differences in the time it takes students to reach successful compilation states in each version. We find that compilation activity differs for each version and that students reach successful compilations faster in BlueJ 4. Based on our findings, we discuss the effectiveness of each version and argue against the constant red underlining of code - an error indicator mechanism present in BlueJ 4 - as this can lead to false positive errors that may mislead novices during their programming tasks.

关键词： Blackbox BlueJ compilation compiler error messages CS1 environments novice programmers programming programming behavior programming process data

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InsProg: Supporting Teaching Through Visual Analysis of Students' programming processes 24

InsProg: Supporting Teaching Through Visual Analysis of Stud...

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17th International Conference on Advanced Visual Interfaces (AVI)

作者： Zhong, Hongyan Niu, Jun Li, Junjie Ningbo Univ Ningbo Peoples R China

ISBN: (纸本)9798400717642

Teachers commonly assess students' knowledge mastery through their submitted programming assignments. However, programming is a dynamic process that involves editing and debugging, and this evaluation may overlook the actual abilities exhibited by students during the programming process. Therefore, understanding students' programming processes becomes crucial for teachers to grasp their programming abilities. While previous studies have focused on students' programming processes, they predominantly concentrate on the evolution of source code content for individual student, neglecting a comprehensive analysis and visual representation of the entire programming pathway, including the debugging process. In this paper, we propose InsProg, a novel visual analysis system for programming process. By collecting students' keystroke data and source code snapshots, InsProg not only enables teachers to trace students' complete programming processes, but it also provides insights into their editing progress and the correctness of their solutions in two-dimensional coordinates. Preliminary experimental results demonstrate that InsProg effectively visualizes students' programming processes, facilitating teachers' efficient assessment of students' programming abilities. This offers valuable support for teachers in assisting with programming instruction.

关键词： visual analysis CS education programming process data educational data mining

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