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Showing 16 to 30 of 431 results Save | Export
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Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
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Muntasir Hoq; Ananya Rao; Reisha Jaishankar; Krish Piryani; Nithya Janapati; Jessica Vandenberg; Bradford Mott; Narges Norouzi; James Lester; Bita Akram – International Educational Data Mining Society, 2025
In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…
Descriptors: Computer Science Education, Programming, Misconceptions, Error Patterns
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Haoze Du; Richard Li; Edward Gehringer – International Educational Data Mining Society, 2025
Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a framework for leveraging subjective metrics derived from the class textual materials across different semesters to assess LLM outputs across various tasks. By utilizing…
Descriptors: Artificial Intelligence, Performance, Evaluation, Automation
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Jesper Dannath; Alina Deriyeva; Benjamin Paaßen – International Educational Data Mining Society, 2025
Research on the effectiveness of Intelligent Tutoring Systems (ITSs) suggests that automatic hint generation has the best effect on learning outcomes when hints are provided on the level of intermediate steps. However, ITSs for programming tasks face the challenge to decide on the granularity of steps for feedback, since it is not a priori clear…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Undergraduate Students
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Radek Pelánek – ACM Transactions on Computing Education, 2025
Learning environments for programming education need a comprehensive task set that guides students from basic programming concepts to complex challenges. For creating such a task set, it is beneficial to utilize the concept of a design space--a systematic mapping of design dimensions and choices along these dimensions. We propose an iterative…
Descriptors: Computer Science Education, Programming, Design, Task Analysis
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Jérôme Brender; Laila El-Hamamsy; Christian Giang; Laura Mathex; Tanja Käser; Francesco Mondada – Educational Technology Research and Development, 2025
Generalist primary school computer science (CS) teachers are often reluctant to introduce CS activities that go beyond CS unplugged tasks. To address this challenge, we drew from constructive alignment principles to implement a new programming modality for primary school: the handwriting programming language (HPL). HPL brings programming…
Descriptors: Handwriting, Programming Languages, Computer Science Education, Teaching Methods
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Mehmet Basaran; Ömer Faruk Vural; Sermin Metin; Sabiha Tamur – International Journal of Early Childhood, 2025
This study investigates ChatGPT's perspectives on coding education for preschool children to provide a comprehensive understanding that is valuable for educators in early childhood education. An instrumental case study approach was employed, utilizing qualitative research design and case study methods. Data were gathered using a structured…
Descriptors: Preschool Education, Computer Science Education, Coding, Artificial Intelligence
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Brayan Díaz; Collin Lynch; Cesar Delgado; Kevin Han – International Journal of STEM Education, 2025
Background: This paper describes research into two pedagogical approaches to foster transdisciplinarity in a graduate engineering course that involves education and computer science. Leveraging the Communities of Practice framework, we examine how students majoring in computer science can integrate new knowledge from education and computer science…
Descriptors: Graduate Study, Engineering Education, Computer Science, Interdisciplinary Approach
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Manuel B. Garcia – Education and Information Technologies, 2025
The global shortage of skilled programmers remains a persistent challenge. High dropout rates in introductory programming courses pose a significant obstacle to graduation. Previous studies highlighted learning difficulties in programming students, but their specific weaknesses remained unclear. This gap exists due to the predominant focus on the…
Descriptors: Programming, Introductory Courses, Computer Science Education, Mastery Learning
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Ruohan Liu; Jennifer L. Maeng; Shanan C. Moots; Joanna K. Garner – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2025
This randomized control trial evaluated the impact of a year-long professional development (PD) program on elementary teachers' CS content knowledge, self-efficacy, and CS implementation. It also investigated teachers' PD experiences and expectations. The findings suggest that treatment teachers' self-efficacy for teaching CS significantly…
Descriptors: Elementary School Teachers, Capacity Building, Faculty Development, Computer Science Education
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Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
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Aoife Hennessy; Kieran Murphy – Irish Educational Studies, 2025
The importance of student engagement is long recognised. Students who are more engaged will be more motivated and inclined to complete their studies. The aim of this study is to understand barriers to engagement for first-year computing students, a cohort that traditionally have high non-progression rates. A qualitative descriptive design was…
Descriptors: Barriers, Learner Engagement, Computer Science Education, College Freshmen
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Sarah Matthews; Maria Nicholas; Lisa Kervin; Louise Paatsch; Peta Wyeth – Education and Information Technologies, 2025
Computational Thinking (CT) is recognised as an essential foundational skill that enhances problem-solving abilities and is a crucial learning area for effective engagement in an increasingly digital society. This paper highlights the significance of screen-less tangible tools in promoting young children's exploration and open-ended play with…
Descriptors: Thinking Skills, Computer Science Education, Infants, Toddlers
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Kaie Maennel; Olaf Maennel – ACM Transactions on Computing Education, 2025
The human aspects of cyber security are fundamental as these are interlinked with processes and technology in building resilience against an evolving and complex threat landscape. It is vital to teach future cyber security specialists sufficient knowledge about human aspects in order to strengthen the defences and defend against malicious actors.…
Descriptors: Computer Security, Computer Science Education, College Curriculum, Teaching Methods
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Neil C. C. Brown; Pierre Weill-Tessier; Juho Leinonen; Paul Denny; Michael Kölling – ACM Transactions on Computing Education, 2025
Motivation: Students learning to program often reach states where they are stuck and can make no forward progress--but this may be outside the classroom where no instructor is available to help. In this situation, an automatically generated next-step hint can help them make forward progress and support their learning. It is important to know what…
Descriptors: Artificial Intelligence, Programming, Novices, Technology Uses in Education
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