Publication Date
| In 2026 | 0 |
| Since 2025 | 57 |
| Since 2022 (last 5 years) | 232 |
| Since 2017 (last 10 years) | 544 |
| Since 2007 (last 20 years) | 975 |
Descriptor
| College Students | 1072 |
| Computer Science Education | 1072 |
| Foreign Countries | 493 |
| Student Attitudes | 336 |
| Programming | 330 |
| Teaching Methods | 257 |
| Computer Software | 205 |
| Instructional Effectiveness | 196 |
| Educational Technology | 150 |
| Introductory Courses | 136 |
| Electronic Learning | 133 |
| More ▼ | |
Source
Author
| Barnes, Tiffany | 9 |
| Heckman, Sarah | 6 |
| Laakso, Mikko-Jussi | 6 |
| Tsai, Chin-Chung | 5 |
| Apiola, Mikko | 4 |
| Frydenberg, Mark | 4 |
| Lynch, Collin | 4 |
| Mayer, Richard E. | 4 |
| Simon, Beth | 4 |
| Tsai, Chia-Wen | 4 |
| Woods, David M. | 4 |
| More ▼ | |
Publication Type
Education Level
Audience
| Teachers | 21 |
| Practitioners | 2 |
| Administrators | 1 |
| Researchers | 1 |
| Students | 1 |
Location
| Turkey | 44 |
| Taiwan | 37 |
| United Kingdom | 34 |
| Finland | 29 |
| Spain | 27 |
| Australia | 22 |
| China | 18 |
| Malaysia | 18 |
| Canada | 16 |
| Germany | 16 |
| Sweden | 16 |
| More ▼ | |
Laws, Policies, & Programs
| Higher Education Opportunity… | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
Muntasir Hoq; Ananya Rao; Reisha Jaishankar; Krish Piryani; Nithya Janapati; Jessica Vandenberg; Bradford Mott; Narges Norouzi; James Lester; Bita Akram – International Educational Data Mining Society, 2025
In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…
Descriptors: Computer Science Education, Programming, Misconceptions, Error Patterns
Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
Mouna Denden; Ahmed Mohamed Fahmy Yousef; Ahmed Tlili; Ronghuai Huang; Ahmed Hosny Saleh Metwally; Haijun Zeng; Huanhuan Wang; Rustam Shadiev – Open Praxis, 2025
Despite the importance of gamification in education, there is still ongoing debate in the literature about how to design effective and useful educational gamification. This is because gamification is a complex concept that requires combining various game elements together. To further contribute to this discussion, this study first develops a…
Descriptors: Gamification, Educational Games, Design, College Students
Molly Domino; Bob Edmison; Stephen H. Edwards; Rifat Sabbir Mansur; Alexandra Thompson; Clifford A. Shaffer – Computer Science Education, 2025
Background and Context: Self-regulated learning (SRL) skills are critical aspect of learning to program and are predictive of academic success. Early college students often struggle to use these skills, but can improve when given targeted instruction. However, it is not yet clear what skills are best to prioritize. Objective: We seek to create a…
Descriptors: Metacognition, Programming, Computer Science Education, College Students
Anna Rechtácková; Radek Pelánek; Tomáš Effenberger – ACM Transactions on Computing Education, 2025
Code quality is a critical aspect of programming, as high-quality code is easier to maintain, and code maintenance constitutes the majority of software costs. Consequently, code quality should be emphasized in programming education. While previous research has identified numerous code quality defects commonly made by students, the current state…
Descriptors: Programming, Computer Science Education, Error Patterns, Automation
Cheryl Resch – ProQuest LLC, 2024
Software vulnerabilities in commercial products are an issue of national importance. The most prevalent breaches are input validation vulnerabilities, and these are easily avoidable. This dissertation contributes to cybersecurity education with a set of hands-on interventions tailored for three CS courses, a set of reflection prompts to encourage…
Descriptors: College Students, Computer Science Education, Computer Security, Curriculum Development
Danielle Lottridge; Davis Dimalen; Gerald Weber – ACM Transactions on Computing Education, 2025
Automated assessment is well-established within computer science courses but largely absent from human--computer interaction courses. Automating the assessment of human--computer interaction (HCI) is challenging because the coursework tends not to be computational but rather highly creative, such as designing and implementing interactive…
Descriptors: Computer Science Education, Computer Assisted Testing, Automation, Man Machine Systems
Ville Isomöttönen; Antti Jussi Lakanen; Elina Valkonen – ACM Transactions on Computing Education, 2025
Identity has received ample attention in computing education research from the viewpoint of "computing identity" and broadening participation, while more attention has been called for to clarify its role. We looked into identity development in the context of Computer Science 1 (CS1) based on Marcia's identity statuses and subsequent…
Descriptors: Computer Science Education, Self Concept, Self Efficacy, College Students
Jiaci Lin; Qijiang Shu; Rong Chen; Chunlin Gao; Kaiqing Xu; Keli Yin; Fuhua Yang – International Journal of Technology and Design Education, 2025
Computational thinking (CT) is an essential component of critical skills for university students, representing the ability to analyze and solve problems. In accordance with constructivist learning theory and the core elements of cultivating CT, this research has developed a Project-Based Teaching approach with computational thinking as its focal…
Descriptors: Computation, Thinking Skills, College Students, Active Learning
Ibrahim Albluwi; Raghda Hriez; Raymond Lister – ACM Transactions on Computing Education, 2025
Explain-in-Plain-English (EiPE) questions are used by some researchers and educators to assess code reading skills. EiPE questions require students to briefly explain (in plain English) the purpose of a given piece of code, without restating what the code does line-by-line. The premise is that novices who can explain the purpose of a piece of code…
Descriptors: Questioning Techniques, Programming, Computer Science Education, Student Evaluation
Nilüfer Atman Uslu; Aytug Onan – Education and Information Technologies, 2025
Understanding the emotions experienced by programming students, particularly concerning gender and education level, is increasingly critical. However, only limited research has used text data to examine these differences within the context of programming education and emotions. This study aims to determine programming students' emotions and any…
Descriptors: Programming, Psychological Patterns, Student Attitudes, Secondary School Students
Antoni Wilinski; Joanna Olkowicz; Sebastian Agata; Alicja Szostkiewicz; Szymon Guzik; Arkadiusz Wojtak; Pawel Tomkiewicz – Informatics in Education, 2025
This paper presents survey results involving students from three fields of study (computer science, business, and pedagogy), positing that computer science students exhibit distinct patterns in the spectrum of multiple intelligences compared to students in social sciences disciplines. The study involved over 300 students, revealing statistically…
Descriptors: Computer Science Education, Intellectual Disciplines, Majors (Students), Multiple Intelligences
Kevin Slonka; Matthew North; Neelima Bhatnagar; Anthony Serapiglia – Information Systems Education Journal, 2025
Continuing to fill the literature gap, this research replicated and expands a prior study of student performance in database normalization in an introductory database course. The data was collected from four different universities, each having different prerequisite courses for their database course. Student performance on a database normalization…
Descriptors: Required Courses, Academic Achievement, Information Systems, Databases
Yoana Omarchevska; Anouschka van Leeuwen; Tim Mainhard – Journal of Computing in Higher Education, 2025
In the flipped classroom, students engage in preparatory activities to study the course materials prior to attending teacher-guided sessions. Students' success in the flipped classroom is directly related to their preparation and students tend to change their preparation activity over time. Few studies have investigated why students change their…
Descriptors: Blended Learning, College Students, Metacognition, Learning Motivation

Peer reviewed
Direct link
