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Jun Rao – ProQuest LLC, 2021
In recent years, not only has there been a dramatic drop in the number of students enrolling in computer science courses, and attrition from computer science courses continues to be significant. Traditionally, computer programming courses have high failure rates, and as they tend to be core to computer science courses can be a roadblock for many…
Descriptors: Self Efficacy, Student Evaluation, Grading, Computer Science Education
Shao-Chen Chang; Charoenchai Wongwatkit – Education and Information Technologies, 2024
As computational thinking becomes increasingly essential, the challenge of designing effective teaching approaches to foster students' abilities in this area persists, especially for higher order thinking skills. This study addresses this challenge by proposing and implementing a peer assessment-based Scrum project (PA-SP) learning approach in…
Descriptors: Peer Evaluation, Computer Science Education, Programming, Mental Computation
Mehmet Firat; Saniye Kuleli – Journal of Educational Technology and Online Learning, 2024
This research investigates the comparative effectiveness of the ChatGPT and the Google search engine in facilitating the self-learning of JavaScript functions among undergraduate open and distance learning students. The study employed a quasi-experimental post-test control group design to analyze the variables of disorientation, satisfaction,…
Descriptors: Comparative Analysis, Web Sites, Computer Software, Artificial Intelligence
Zhanxia Yang; Marina Bers – Computer Science Education, 2024
Background and Context: Historically, women have been underrepresented in computer science. To address this gender gap, researchers advocate for high-quality computer science programs for early childhood. Objectives: This study examines gender differences in coding performance before and after implementing a 24-lesson visual programming curriculum…
Descriptors: Gender Differences, Grade 1, Elementary School Students, Programming
David E. Platt – ProQuest LLC, 2024
This qualitative, phenomenological research study explores the best practices that secondary Grades 6-12 educators employ when using microcontrollers in the classroom. Governmental and private organizations have investigated and promoted the importance of Science, Technology, Engineering, Math (STEM) and computer science in education (Code…
Descriptors: Best Practices, Teaching Methods, Computer Science Education, Programming
Mohsen Asgari; Fong-Chun Tsai; Linda Mannila; Filip Strömbäck; Kazi Masum Sadique – Discover Education, 2024
As programming emerges as a critical skill in the digital age and digital tools continue to evolve, understanding students' perspectives on the integration of such technologies into their education is crucial. This empirical study explores the perspectives of students in Sweden and Taiwan on the use of digital tools in their programming courses.…
Descriptors: Foreign Countries, Comparative Education, Student Attitudes, Technology Uses in Education
Roba Hrisseh – ProQuest LLC, 2024
The push to teach coding in schools continues to gain momentum. Coding helps students develop skills in problem-solving, critical thinking, and creativity, as well as improve overall academic performance. However, students with disabilities often face challenges in areas such as problem-solving, mathematics, and multistep reasoning when learning…
Descriptors: Programming, Computer Science Education, Writing Instruction, Literacy
Chengliang Wang; Xiaojiao Chen; Yifei Li; Pengju Wang; Haoming Wang; Yuanyuan Li – Journal of Educational Computing Research, 2025
This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students' multidimensional development. Utilizing a quasi-experimental research design, this study compared students' programming learning achievements (PLA),…
Descriptors: Programming, Computer Science Education, Metacognition, Computer Simulation
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
Lavy, Ilana – Informatics in Education, 2023
This paper describes a pilot study that explores students learning how to program via a multi-disciplinary approach. The study participants were eleven 6th grade students who learned programming fundamentals via music activities in a Scratch 3.0 environment. These activities included the programming of familiar melodies and the development of…
Descriptors: Computer Science Education, Programming, Grade 6, Music
Garcia, Fabrício Wickey da Silva; Oliveira, Sandro Ronaldo Bezerra; Carvalho, Elielton da Costa – Informatics in Education, 2023
The contents taught in the programming subjects have a great relevance in the formation of computing students. However, these subjects are characterized by high failure rates, as they require logical reasoning and mathematical knowledge. Thus, establishing knowledge through the subject of algorithms can help students to overcome these difficulties…
Descriptors: Teaching Methods, Algorithms, Undergraduate Students, Computer Science Education
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
Margulieux, Lauren; Parker, Miranda C.; Cetin Uzun, Gozde; Cohen, Jonathan D. – Journal of Technology and Teacher Education, 2023
Educators across disciplines are implementing lessons and activities that integrate computing concepts into their curriculum to broaden participation in computing. Out of myriad important introductory computing skills, it is unknown which--and to what extent--these concepts are included in these integrated experiences, especially when compared to…
Descriptors: Programming, Programming Languages, Computer Science Education, Age Differences
Guney, Zafer – Malaysian Online Journal of Educational Technology, 2019
The aim of this study is to introduce the four-component instructional design (4C/ID) model in teaching loops for programming by using the model, which is defined in programming instruction, with the principles of the model for teaching technical skills and to discuss the differences in instructional planning and to discuss in the process of…
Descriptors: Instructional Design, Computer Science Education, Programming, Models

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