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Zhang, Yingbin; Paquette, Luc; Pinto, Juan D.; Liu, Qianhui; Fan, Aysa Xuemo – Education and Information Technologies, 2023
It is widely recognized that debugging is challenging for novice programmers and, as such, computing educators and researchers have called for explicit debugging instruction. Debugging requires various knowledge and skills, and different students may show different strengths and weaknesses. An understanding of such individual differences is…
Descriptors: Undergraduate Students, Programming, Novices, Troubleshooting
Zhaojun Duo; Jianan Zhang; Yonggong Ren; Xiaolu Xu – Education and Information Technologies, 2025
"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…
Descriptors: Students, Programming, Problem Solving, Self Management
Wei Li; Cheng-Ye Liu; Judy C. R. Tseng – British Journal of Educational Technology, 2024
Collaborative programming helps improve students' computational thinking and increases their confidence in solving programming problems. However, the effect of collaborative learning is not ideal because it is difficult for students to mobilize metacognition to regulate learning spontaneously. To guide students to effectively regulate the learning…
Descriptors: Foreign Countries, Junior High School Students, Metacognition, Academic Achievement
Weisberg, Steven M.; Schinazi, Victor R.; Ferrario, Andrea; Newcombe, Nora S. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Relying on shared tasks and stimuli to conduct research can enhance the replicability of findings and allow a community of researchers to collect large data sets across multiple experiments. This approach is particularly relevant for experiments in spatial navigation, which often require the development of unfamiliar large-scale virtual…
Descriptors: Programming, Error Patterns, Computer Simulation, Spatial Ability
Kocaman, Berrak – International Journal of Educational Methodology, 2023
This research aims to examine the effect of coding education on the analytical thinking skills of gifted students. The participants are 18 students, 11 to 12 years old. An embedded experimental mixed design was used in the research. The data collection was carried out with the Analytical Thinking Skill Scale to determine the difference in the…
Descriptors: Programming, Computer Science Education, Thinking Skills, Academically Gifted
Hugo G. Lapierre; Patrick Charland; Pierre-Majorique Léger – Computer Science Education, 2024
Background and Context: Current programming learning research often compares novices and experienced programmers, leaving early learning stages and emotional and cognitive states under-explored. Objective: Our study investigates relationships between cognitive and emotional states and learning performance in early stage programming learners with…
Descriptors: Programming, Computer Science Education, Psychological Patterns, Cognitive Processes
Emre Eçier; Serkan Izmirli – Journal of Educational Technology and Online Learning, 2024
The primary aim of this research is to assess the digital fluency levels of high school students and to investigate how digital fluency varies according to different variables. The study employed a descriptive research design using survey methodology. A total of 698 students from various high schools in Çanakkale province, Türkiye, representing…
Descriptors: High School Students, Foreign Countries, Gender Differences, Grade Level Differences
Jennings, Jay; Muldner, Kasia – International Journal of Artificial Intelligence in Education, 2021
When students are first learning to program, they not only have to learn to write programs, but also how to trace them. Code tracing involves stepping through a program step-by-step, which helps to predict the output of the program and identify bugs. Students routinely struggle with this activity, as evidenced by prior work and our own experiences…
Descriptors: Scaffolding (Teaching Technique), Tutors, Tutoring, Programming
Xu, Zhen; Ritzhaupt, Albert D.; Umapathy, Karthikeyan; Ning, Yang; Tsai, Chin-Chung – Computer Science Education, 2021
Background and context: Researchers have been looking into the complexity of computer science (CS) education and tried to apply rigorous and relevant educational research methods to understand and facilitate the learning experience of students. Objective: The purpose of this study was to explore college students' conceptions of learning CS to shed…
Descriptors: College Students, Student Attitudes, Computer Science Education, Freehand Drawing
Lihui Sun; Zhen Guo; Danhua Zhou – Interactive Learning Environments, 2024
Coding ability has become an essential digital skill for young children. The graphical programming environment is valuable carrier for cultivating children's coding ability. The purpose of this study is to develop a coding ability test for children, to conduct a graphic coding intervention, and to further explore the impact of multiple factors on…
Descriptors: Programming, Skill Development, Intervention, Student Experience
I-Fan Liu; Hui-Chun Hung; Che-Tien Liang – Interactive Learning Environments, 2024
With the rise of big data, artificial intelligence, and other emerging information technologies, an increasing number of students without computer science (CS) backgrounds have begun to learn programming. Programming is considered a complex task for beginners, and instructors find it difficult to quickly address all the problems that students…
Descriptors: Programming, Student Attitudes, Blended Learning, Video Technology
Demir, Ömer; Seferoglu, Süleyman Sadi – Journal of Educational Computing Research, 2021
This study's goal was to investigate the effect of homogeneous and heterogeneous pairs in terms of individual differences on group compatibility, flow, and coding performance in pair programming. In line with this goal, five individual difference variables of gender, learning style, friendship, the conscientiousness component of personality…
Descriptors: College Students, Programming, Coding, Cooperative Learning
Sapounidis, Theodosios; Stamovlasis, Dimitrios; Demetriadis, Stavros – IEEE Transactions on Education, 2019
Contribution: Prior studies on tangible versus graphical user interfaces have reported controversial findings concerning children's preferences. This paper shows that their preference profiles in the domain of introductory programming are associated with gender and age for both interfaces. Background: The relevant literature mainly consists of…
Descriptors: Preferences, Profiles, Robotics, Introductory Courses
Akar, Sacide Guzin Mazman; Altun, Arif – Contemporary Educational Technology, 2017
The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…
Descriptors: Individual Differences, Learning Processes, Programming, Self Efficacy
Tsai, Chih-Cheng; Cheng, Yuh-Min; Tsai, Yu-Shan; Lou, Shi-Jer – Education Sciences, 2021
In this study, experimental teaching was conducted through the artificial intelligence of things (AIOT) practical course, and the 4D (discover, define, develop, deliver) double diamond shape was used to design the course and plan the teaching content to observe the students' self-efficacy and learning anxiety. The technology acceptance model (TAM)…
Descriptors: High School Students, Student Satisfaction, Value Judgment, Usability
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