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Direct linkLihui Sun; Junjie Liu – Journal of Educational Computing Research, 2024
Computational thinking (CT), as a new future-oriented literacy, has gained attention at the basic education level. Graphical programming is the common way to develop CT in primary students, but this drag-and-drop programming may weaken students' understanding of programming's abstract concepts and code logic. Text-based programming approaches can…
Descriptors: Thinking Skills, Computation, Programming, Gamification
Xue Zhang; Chao Qin; Yanjia Liu; Haipeng Wan – ACM Transactions on Computing Education, 2024
Pair programming is an effective instructional format in programming education for adolescents. Within pair programming, three potential gender combinations may arise: Boy-Boy (BB), Girl-Girl (GG), and Boy-Girl (BG). This study explores the impact of different gender pairings on the programming self-efficacy and collaborative attitudes of…
Descriptors: Programming, Gender Differences, Cooperative Learning, Self Efficacy
Jiang, Shan; Wong, Gary K. W. – Journal of Computer Assisted Learning, 2022
Over the past decade, the call to foster computational thinking (CT) in every child has received considerable attention. However, there is little understanding of whether children are developmentally ready to think computationally and what specific CT concepts and skills can be developed at various ages. This study explored the developmental and…
Descriptors: Age Differences, Gender Differences, Thinking Skills, Computation
Polat, Elif; Hopcan, Sinan; Kucuk, Sevda; Sisman, Burak – British Journal of Educational Technology, 2021
Performance in and perceptions of computational thinking (CT) are considered vital dimensions for comprehensively assessing CT skills of students. In this study, secondary school students' CT performance and their perceptions were examined in terms of certain variables including gender, grade level, achievement and self-efficacy.…
Descriptors: Secondary School Students, Computation, Thinking Skills, Gender Differences
Chao Qin; Mengli Zhang; Zhixin Li; Luxin Chen – Education and Information Technologies, 2025
Artificial intelligence (AI) is being deeply integrated into human society. In the future, human collaboration with AI is inevitable. Therefore, exploring the attitudes of future workers--represented by current K-12 children--towards AI has become crucial. Robots stand as typical representatives of AI. Robot programming education is an important…
Descriptors: Foreign Countries, Rural Schools, Elementary School Students, Grade 6
Wu, Sheng-Yi; Su, Yu-Sheng – Journal of Educational Computing Research, 2021
Currently, many countries actively cultivate students to develop computational thinking ability. Many visual programming environments (VPEs) and physical robot courses have been integrated into computational thinking learning in the elementary education stage. This study explores the relationship between the programming learning environment…
Descriptors: Programming, Computation, Thinking Skills, Grade 5
Camila Porto; Emiliano Pereiro; María Eugenia Curi; Victor Koleszar; Alar Urruticoechea – Journal of Research on Technology in Education, 2025
The Uruguayan computational thinking (CT) program promotes CT skills for students in fourth, fifth, and sixth grades. Since 2017, it has reached over 70,000 students, with participation and Bebras challenge performance equally distributed by gender. This study examines gender perspectives in the program, focusing on teacher perceptions, student…
Descriptors: Computation, Thinking Skills, Foreign Countries, Teacher Attitudes
Teresa M. Ober; Ying Cheng; Meghan R. Coggins; Paul Brenner; Janice Zdankus; Philip Gonsalves; Emmanuel Johnson; Tim Urdan – Computer Science Education, 2024
Background and Context: Differences in children's and adolescents' initial attitudes about computing and other STEM fields may form during middle school and shape decisions leading to career entry. Early emerging differences in career interest may propagate a lack of diversity in computer science and programming fields. Objective: Though middle…
Descriptors: Middle School Students, Student Attitudes, Computer Science Education, STEM Education
Download full textIbrahim Bastug; Kagan Kircaburun – Journal of Pedagogical Research, 2017
In recent years, the number of students who have chosen computer science related undergraduate departments has decreased rapidly. Moreover, students who prefer computer science and programming departments appear to be unsuccessful in programming classes due to the complexity and frustrating difficulties of programming learning. One of the…
Descriptors: Student Attitudes, Programming, Computer Science Education, Middle School Students
Noh, Jiyae; Lee, Jeongmin – Educational Technology Research and Development, 2020
Around the world, programming education is actively promoted by such factors as economic and technical requirements. The use of a robot in programming education could help students understand computer-science concepts more easily. In this study we designed a course in programming a robot for elementary school students and investigated its…
Descriptors: Thinking Skills, Elementary School Students, Robotics, Programming
Gronhoj, Alice; Bech-Larsen, Tino; Chan, Kara; Tsang, Lennon – Health Education, 2013
Purpose: The purpose of the study was to apply the theory of planned behavior to predict Danish adolescents' behavioral intention for healthy eating. Design/methodology/approach: A cluster sample survey of 410 students aged 11 to 16 years studying in Grade 6 to Grade 10 was conducted in Denmark. Findings: Perceived behavioral control followed by…
Descriptors: Adolescents, Teaching Methods, Body Composition, Foreign Countries
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
