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Peng Chen; Rong Wang; Xiaoyi Chen – Education and Information Technologies, 2025
Collaborative learning is a widely used teaching model in programming education. A deeper understanding of the roles and behavior patterns within collaborative learning could improve its performance. In this study, an emergent role configuration and behavioral pattern are analyzed using audio and video data from 10 groups in a 7th-grade…
Descriptors: Middle School Students, Cooperative Learning, Behavior Patterns, Programming
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Aykut Durak; Vahide Bulut – Technology, Knowledge and Learning, 2025
The study uses the partial least squares-structural equation modeling (PLS-SEM) algorithm to predict the factors affecting the programming performance (PPE) (low, high) of the students receiving computer programming education. The participants of the study consist of 763 students who received programming education. In the analysis of the data, the…
Descriptors: Prediction, Low Achievement, High Achievement, Academic Achievement
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Domicián Máté; Judit T. Kiss; Mária Csernoch – Education and Information Technologies, 2025
The impact of cognitive biases, particularly biased self-assessment, on learning outcomes and decision-making in higher education is of great significance. This study delves into the confluence of cognitive biases and user experience in spreadsheet programming as a crucial IT skill across various academic disciplines. Through a quantitative…
Descriptors: Programming, Spreadsheets, Computer Science Education, STEM Education
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Lior Miller Markovitz; Roza Leikin; Gad M. Landau – International Journal of Science and Mathematics Education, 2025
Computer Science (CS), despite being an integral part of STEM education, remains less accessible to school students. This study examines the Challenge program, which enables high-achieving high school students to earn a B.Sc. degree in CS. Over two years, from 458 applicants, 160 passed the admission tests, but only 34 completed their degree. The…
Descriptors: STEM Education, Academic Achievement, Computer Science Education, High Achievement
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Milan Turcáni; Zoltan Balogh; Michal Kohútek – Smart Learning Environments, 2024
In this research, a mixed-method approach was employed to conduct large-scale eye-tracking measurements, traditionally associated with high costs and extensive time commitments. Utilizing consumer-grade webcams in conjunction with open-source software, data was collected from an expansive cohort of students, thereby demonstrating the scalability…
Descriptors: Computer Science Education, Eye Movements, Reading Comprehension, Knowledge Level
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Kadir Bahar; Erdogan Kaya; Xiaolu Zhang; Eter Mjavanadze – Journal of Advanced Academics, 2023
This study explores the direction and magnitude of racial disparities on three advanced placement (AP) computer science (CS) exams, namely AP CS Principles, AP CS A, and AP CS AB, based on the test scores of more than one million students who have taken AP CS exams between 1997 and 2020. Using Mann-Kendall test and Sen's slope procedures we found…
Descriptors: Educational Trends, Trend Analysis, Academic Achievement, High Achievement
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Sarah K. Mason; Matt Hancock; Izzy Thornton – Grantee Submission, 2024
Rural Mississippi schools often face challenges in providing equitable access to Advanced Placement (AP) courses, particularly in STEM fields. This lack of access limits opportunities for high-achieving students to pursue rigorous STEM coursework and related careers. The AP STEM program aims to improve access to AP STEM courses for high-achieving…
Descriptors: Rural Schools, STEM Education, Advanced Placement Programs, Access to Education
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Jegede, Philip Olu; Olajubu, Emmanuel Ajayi; Ejidokun, Adekunle Olugbenga; Elesemoyo, Isaac Oluwafemi – Journal of Information Technology Education: Innovations in Practice, 2019
Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However,…
Descriptors: Programming Languages, Programming, Low Achievement, High Achievement
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Lin, Che-Chern; Liu, Zi-Cheng; Chang, Chih-Lin; Lin, Yu-Wen – IEEE Transactions on Education, 2019
Contribution: An online genetic algorithm-based remedial learning system is presented in order to strengthen students' understanding of object-oriented programming (OOP) concepts by tailoring personalized learning materials according to each student's strengths and weaknesses. Background: Prior studies on computer programming education have…
Descriptors: Individualized Instruction, Remedial Instruction, Computer Science Education, Programming Languages
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Shah, Niral; Lewis, Colleen M. – Cognition and Instruction, 2019
Research on collaborative learning has focused on its potential to foster successful problem solving. Less attention, though, has been given to issues of equity. In this article, we investigate how inequity can become amplified and attenuated within collaborative learning through small interactional moves that accumulate to produce broader…
Descriptors: Cooperative Learning, Computer Science Education, Student Participation, Elementary School Students
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Wu, Bian; Hu, Yiling; Ruis, A. R.; Wang, Minhong – Journal of Computer Assisted Learning, 2019
Computational thinking (CT), the ability to devise computational solutions for real-life problems, has received growing attention from both educators and researchers. To better improve university students' CT competence, collaborative programming is regarded as an effective learning approach. However, how novice programmers develop CT competence…
Descriptors: Thinking Skills, Problem Solving, Teaching Methods, College Students
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Pertegal-Felices, María L.; Castejón-Costa, Juan L.; Gilar-Corbí, Raquel; Mora-Mora, Higinio – Journal of Education, 2017
Several studies have documented the benefits of emotional intelligence particularly in the workplace. The main objective of universities is to educate in terms of acquiring capacities, abilities, competencies, and values, with the ultimate aim of promoting employment. In some Spanish universities, High Academic Performance Groups (HAPs) have been…
Descriptors: Emotional Intelligence, Computer Science Education, Engineering Education, Academic Achievement
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Rodrigo, Ma. Mercedes T.; Andallaza, Thor Collin S.; Castro, Francisco Enrique Vicente G.; Armenta, Marc Lester V.; Dy, Thomas T.; Jadud, Matthew C. – Journal of Educational Computing Research, 2013
In this article we quantitatively and qualitatively analyze a sample of novice programmer compilation log data, exploring whether (or how) low-achieving, average, and high-achieving students vary in their grasp of these introductory concepts. High-achieving students self-reported having the easiest time learning the introductory programming…
Descriptors: Programming, High Achievement, Introductory Courses, Qualitative Research
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Hsieh, Pei-Hsuan; Chen, Nian-Shing – Turkish Online Journal of Educational Technology - TOJET, 2012
The purpose of this study is to examine the effects of reflective thinking effects in the process of designing software on students' learning performances. The study contends that reflective thinking is a useful teaching strategy to improve learning performance among lower achieving students. Participants were students from two groups: Higher…
Descriptors: Foreign Countries, Computer Software, Computer Software Evaluation, Programming
Trotter, Andrew – Education Week, 2008
U.S. students spend too little time and effort on academics in high school, compared with harder-working young people in China and India, according to a new documentary being shown to "thought leaders" in states holding presidential primaries this winter. The documentary, conceived and financed by high-tech entrepreneur Robert A.…
Descriptors: High Schools, High School Seniors, Cultural Differences, Time Factors (Learning)
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