Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 7 |
Since 2016 (last 10 years) | 9 |
Since 2006 (last 20 years) | 10 |
Descriptor
Classification | 11 |
Computer Science Education | 11 |
Programming Languages | 11 |
Programming | 10 |
Computer Software | 5 |
Novices | 4 |
Undergraduate Students | 4 |
Coding | 3 |
Evaluation Methods | 3 |
Foreign Countries | 3 |
Introductory Courses | 3 |
More ▼ |
Source
International Educational… | 4 |
ACM Transactions on Computing… | 2 |
Educational Technology &… | 1 |
Informatics in Education | 1 |
Journal of Educational Data… | 1 |
Journal of Information… | 1 |
Themes in Science and… | 1 |
Author
Barnes, Tiffany | 3 |
Chi, Min | 2 |
Shi, Yang | 2 |
Abel, Marie-Helene | 1 |
Barry, Catherine | 1 |
Beck, Florian | 1 |
Benayache, Ahcene | 1 |
Chaput, Brigitte | 1 |
Christian Dieter Schunn | 1 |
Fein, Benedikt | 1 |
Fraser, Gordon | 1 |
More ▼ |
Publication Type
Reports - Research | 10 |
Journal Articles | 7 |
Speeches/Meeting Papers | 4 |
Reports - Descriptive | 1 |
Tests/Questionnaires | 1 |
Education Level
Higher Education | 7 |
Postsecondary Education | 6 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Fein, Benedikt; Graßl, Isabella; Beck, Florian; Fraser, Gordon – International Educational Data Mining Society, 2022
The recent trend of embedding source code for machine learning applications also enables new opportunities in learning analytics in programming education, but which code embedding approach is most suitable for learning analytics remains an open question. A common approach to embedding source code lies in extracting syntactic information from a…
Descriptors: Artificial Intelligence, Learning Analytics, Programming, Programming Languages
Höppner, Frank – International Educational Data Mining Society, 2021
Various similarity measures for source code have been proposed, many rely on edit- or tree-distance. To support a lecturer in quickly assessing live or online exercises with respect to "approaches taken by the students," we compare source code on a more abstract, semantic level. Even if novice student's solutions follow the same idea,…
Descriptors: Coding, Classification, Programming, Computer Science Education
Gitinabard, Niki; Gao, Zhikai; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin F. – Journal of Educational Data Mining, 2023
Few studies have analyzed students' teamwork (pairwork) habits in programming projects due to the challenges and high cost of analyzing complex, long-term collaborative processes. In this work, we analyze student teamwork data collected from the GitHub platform with the goal of identifying specific pair teamwork styles. This analysis builds on an…
Descriptors: Cooperative Learning, Computer Science Education, Programming, Student Projects
Ragonis, Noa; Shmallo, Ronit – Informatics in Education, 2022
Object-oriented programming distinguishes between instance attributes and methods and class attributes and methods, annotated by the "static" modifier. Novices encounter difficulty understanding the means and implications of "static" attributes and methods. The paper has two outcomes: (a) a detailed classification of aspects of…
Descriptors: Programming, Computer Science Education, Concept Formation, Thinking Skills
Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
McCall, Davin; Kölling, Michael – ACM Transactions on Computing Education, 2019
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…
Descriptors: Computer Software, Programming, Error Patterns, Novices
Mao, Ye; Shi, Yang; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2021
As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…
Descriptors: Programming, Computer Science Education, Learning Processes, Learning Analytics
Karnalim, Oscar – Themes in Science and Technology Education, 2017
This paper empirically enlists Python plagiarism attacks that have been found on Introductory Programming course assignments for undergraduate students. According to our observation toward 400 plagiarism-suspected cases, there are 35 plagiarism attacks that have been conducted by students. It starts with comment & whitespace modification as…
Descriptors: Plagiarism, Introductory Courses, Programming Languages, Taxonomy
Rashkovits, Rami; Lavy, Ilana – Journal of Information Technology Education, 2011
This study discusses and presents various strategies employed by novice programmers concerning exception handling. The main contributions of this paper are as follows: we provide an analysis tool to measure the level of assimilation of exception handling mechanism; we present and analyse strategies to handle exceptions; we present and analyse…
Descriptors: Foreign Countries, Programming Languages, Computer Software, Computer Software Evaluation
Abel, Marie-Helene; Benayache, Ahcene; Lenne, Dominique; Moulin, Claude; Barry, Catherine; Chaput, Brigitte – Educational Technology & Society, 2004
E-learning leads to evolutions in the way of designing a course. Diffused through the web, the course content cannot be the direct transcription of a face to face course content. A course can be seen as an organization in which different actors are involved. These actors produce documents, information and knowledge that they often share. We…
Descriptors: Course Content, Internet, College Instruction, Models