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Ülker, Ezgi Deniz – Cypriot Journal of Educational Sciences, 2020
The ability of analysing and designing an algorithm is quite essential for computer science education. The students in the Analysis and Design of Algorithms (ADA) course are expected to be able to solve problems by choosing one of the proper design methods and to analyse the algorithm's performance in terms of various aspects. Instead of using…
Descriptors: Computer Science Education, Design, Mathematics, Programming
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Gökoglu, Seyfullah; Kilic, Servet – E-Learning and Digital Media, 2023
This study investigates pre-service computer science (CS) teachers' perspectives on the factors affecting their programming abilities, concerns about their future professional lives, and pedagogical suggestions for effective programming teaching. The participants of the study were twenty-eight pre-service CS teachers studying at eighteen different…
Descriptors: Programming, Computer Science Education, Preservice Teachers, Teaching Methods
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Geerts, Nelly; Schirmer, Werner; Vercruyssen, Anina; Glorieux, Ignace – International Journal of Lifelong Education, 2023
Existing research on digital inclusion has shown that older adults (65+) are, in general, less digitally skilled than other age groups. While older adults can gain digital skills through 'cold' (formal) training by ICT instructors or through 'warm' (informal) support from family and friends, studies have suggested that formal training is more…
Descriptors: Older Adults, Technological Literacy, Teacher Role, Computer Science Education
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Chen, Peggy P. – New Directions for Teaching and Learning, 2023
Many introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross-cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in…
Descriptors: Introductory Courses, Computer Science Education, Computer Literacy, Thinking Skills
Alannah Oleson – ProQuest LLC, 2023
To realize more equitable technology futures, it is not enough to simply adapt technology to be more inclusive "after" it is created. We will also need to equip technology creators with the skills they need to critically reflect upon bias and exclusion "during" the technology design process. The question of how to best to…
Descriptors: Computation, Computer Science Education, Inclusion, Decision Making
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Amoudi, Ghada; Tbaishat, Dina – Education and Information Technologies, 2023
Social network analysis involves delicate and sophisticated mathematical concepts which are abstract and challenging to acquire by traditional methods. Many studies show that female students perform poorly in computer science-related courses compared to male students. To address these issues, this research investigates the impact of employing a…
Descriptors: Computer Science, Graduate Students, Outcomes of Education, Educational Technology
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C. Florou; G. Stamoulis; A. Xenakis; A. Plageras – Education and Information Technologies, 2025
This study focuses on students' self-assessment during their learning process related to computer programming concepts, taking into account challenges and obstacles both teachers and students face, with the aim to contribute to the development of guiding principles and practices and enhance the teaching process of computer programming in primary…
Descriptors: Teacher Role, Self Evaluation (Individuals), Computer Science Education, Programming
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Karen Woo; Garry Falloon – Computer Science Education, 2025
Background and context: Coding and computational thinking are often taught through integrated curricula, despite a paucity of classroom-based research on their effectiveness. Objective: To investigate evidence of learning resulting from cross-curricular coding tasks in middle-school classrooms, and the school environment factors that impact upon…
Descriptors: Coding, Computer Science Education, Curriculum Development, Thinking Skills
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Guangrui Fan; Dandan Liu; Rui Zhang; Lihu Pan – International Journal of STEM Education, 2025
Purpose: This study investigates the impact of AI-assisted pair programming on undergraduate students' intrinsic motivation, programming anxiety, and performance, relative to both human-human pair programming and individual programming approaches. Methods: A quasi-experimental design was conducted over two academic years (2023-2024) with 234…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Programming
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K. Ann Renninger; Ruth C. Elias; Mariko J. Kamiya; Jennifer N. Paige; Raymond A. Youngblood – Computer Science Education, 2025
Background and Context: Integrating computer science (CS) and math in classrooms is an increasingly recognized way for schools to address national CS mandates. There is a need to understand how professional development (PD) can support teachers to integrate. Objective: We examined math teachers' interest, and confidence, in math, CS, and student…
Descriptors: Faculty Development, Teacher Workshops, Computer Science Education, Mathematics Instruction
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Rita Garcia; Michelle Craig – ACM Transactions on Computing Education, 2025
Introduction: Computer Science Education does not have a universally defined set of concepts consistently covered in all introductory courses (CS1). One approach to understanding the concepts covered in CS1 is to ask educators. In 2004, Nell Dale did just this. She also collected their perceptions on challenging topics to teach. Dale mused how the…
Descriptors: Replication (Evaluation), Teaching Methods, Computer Science Education, Introductory Courses
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Christian Basil Omeh; Musa Adekunle Ayanwale; Lindelani E. Mnguni; Chijioke Jonathan Olelewe – Journal of New Approaches in Educational Research, 2025
Despite the increasing emphasis on computational literacy in higher education, we observed that many undergraduate students particularly in developing contexts struggle to master fundamental programming skills and develop critical thinking. Conventional instructional approaches often lack interactivity and personalized scaffolding, which are…
Descriptors: Skill Development, Programming, Computer Science Education, Critical Thinking
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Furkan Yucel; Hasret Sultan Unal; Elif Surer; Nejan Huvaj – IEEE Transactions on Learning Technologies, 2024
Laboratory experience is an integral part of the undergraduate curriculum in most engineering courses. When physical learning is not feasible, and when the demand cannot be met through actual hands-on laboratory sessions, as has been during the COVID-19 pandemic, virtual laboratory courses can be considered as an alternative education medium. This…
Descriptors: Electronic Learning, Engineering Education, COVID-19, Pandemics
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Jim Marquardson – Information Systems Education Journal, 2024
Generative artificial intelligence (AI) tools were met with a mix of enthusiasm, skepticism, and fear. AI adoption soared as people discovered compelling use cases--developers wrote code, realtors generated narratives for their websites, students wrote essays, and much more. Calls for caution attempted to temper AI enthusiasm. Experts highlighted…
Descriptors: Artificial Intelligence, Capstone Experiences, Computer Security, Information Security
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Shonn Cheng; Hsuan-Pu Chang; Sheng-Shiang Tseng – European Journal of Psychology of Education, 2024
The goal of the present study was to explore the relations among perceived psychosocial learning environments, instructional modality, motivation, self-regulated learning, and academic achievement in blended computer science education. The participants were 207 undergraduate students enrolled in a blended online and face-to-face design course. We…
Descriptors: Undergraduate Students, Computer Science Education, Blended Learning, Student Motivation
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