CodeProcess Charts: Visualizing the Process of Writing Code

Shrestha, Raj; Leinonen, Juho; Hellas, Arto; Ihantola, Petri; Edwards, John

doi:10.1145/3511861.3511867

Cited by 7 publications

(3 citation statements)

References 43 publications

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“…For example, if it was clear from the logs that many students had difficulty understanding the loop while doing homework, it was explained in class in more detail how to use the print function to understand the loop and focus on the examples, which helped clarify the problems seen in the logs. Previous research (Matsuzawa et al, 2013; Shrestha et al, 2022; Yan et al, 2019) that has used feedback based on visualization of the programming process has shown its usefulness, especially in improving students' problem-solving style.…”

Section: Methodsmentioning

confidence: 99%

“…They also point out that using such a tool reduces plagiarism, as it is much harder to cheat if you need to present your programming process. Shrestha et al (2022) created a tool visualizing the programming process to help instructors understand students’ problem-solving styles and indicate whether a student is struggling. They also said that the tool is useful for students' self-reflection.…”

Section: Literature Reviewmentioning

confidence: 99%

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Effectiveness of Feedback Based on Log File Analysis in Introductory Programming Courses

Meier

Lepp

2022

Journal of Educational Computing Research

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Especially in large courses, feedback is often given only on the final results; less attention is paid to the programming process. Today, however, some programming environments, e.g., Thonny, log activities during programming and have the functionality of replaying the programming process. This information can be used to provide feedback, and this knowledge can be integrated into practical sessions in the classroom. This study aimed to analyse how feedback based on logs affects exam results, task completion time, the number of runs, error messages, and pastes (of the whole group and beginners and non-beginners separately). An experiment was conducted in 2020 and 2021 in the course “Introduction to Programming”. Some groups received additional feedback on homework throughout the course based on log information; the remaining groups worked as usual. Based on the information received from the logs, general recommendations were also offered in the practical sessions. Our study showed that feedback based on logs improved mainly exam test results and programming task solving time among beginners. Therefore, it would be a good method to use, especially in beginner groups.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Effectiveness of Feedback Based on Log File Analysis in Introductory Programming Courses

Meier

Lepp

2022

Journal of Educational Computing Research

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“…In general, it is possible to convert from a very fine-grained step size to a more course granularity but not vice versa, so we prefer finer-grained collection. Using data with keystroke-level granularity ensures the data are compatible with other code analysis tools (e.g., CodeProcess Charts [60]), which can be useful in the investigation of students' programming processes.…”

Section: Stepmentioning

confidence: 99%

Towards Giving Timely Formative Feedback and Hints to Novice Programmers

Jeuring

Keuning

Marwan

et al. 2022

Proceedings of the 2022 Working Group Reports on Innovation and Technology in Computer Science Education

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Every year, millions of students learn how to write programs. Learning activities for beginners almost always include programming tasks that require a student to write a program to solve a particular problem. When learning how to solve such a task, many students need feedback on their previous actions, and hints on how to proceed. For tasks such as programming, which are most often solved stepwise, the feedback should take the steps a student has taken towards implementing a solution into account, and the hints should help a student to complete or improve a possibly partial solution.This paper investigates how previous research on feedback is translated to when and how to give feedback and hints on steps a student takes when solving a programming task. We have selected datasets consisting of sequences of steps students take when working on a programming problem, and annotated these datasets at those places at which experts would intervene, and how they would intervene. We have used these datasets to compare expert feedback * co-leader †

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