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Jennifer L. Maeng; Timothy Konold; Khushbu Singh – Grantee Submission, 2025
The study examined the Advancing Rural Computer Science (ARCS) program, a professional development initiative designed to improve elementary teachers' computer science (CS) content knowledge, pedagogical practices, and self-efficacy, with the goal of enhancing K-5 students' interest in and knowledge of CS. ARCS was funded through USED EIR…
Descriptors: Rural Schools, Computer Science Education, Faculty Development, Elementary School Teachers
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Liargkovas, Georgios; Papadopoulou, Angeliki; Kotti, Zoe; Spinellis, Diomidis – IEEE Transactions on Education, 2022
Contribution: Determine and analyze the gap between software practitioners' education outlined in the 2014 IEEE/ACM software engineering education knowledge (SEEK) and industrial needs pointed by Wikipedia articles referenced in Stack Overflow (SO) posts. Background: Previous work has uncovered deficiencies in the coverage of computer…
Descriptors: Industry, Knowledge Level, Computer Software, Computer Science
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Herminio Bodon; Vishesh Kumar; Marcelo Worsley – ACM Transactions on Computing Education, 2025
Objectives: Athletics and sports represent a focal part of adolescence for millions of youth around the world. However, opportunities to engage in computer science (CS) learning experiences are less prevalent, particularly among Hispanic and low-income communities. Recently, researchers have explored ways to bridge these, seemingly, disparate…
Descriptors: Design, Computer Science Education, Physical Education, Athletics
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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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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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Eunsang Lee – Education and Information Technologies, 2025
This study addresses challenges in digital logic circuit practices by introducing an Arduino-based digital logic circuit practice board module (DLCPBM) designed to improve learning efficiency and sustainability. The DLCPBM comprises three module types that integrate theoretical knowledge with hands-on application, enabling students to intuitively…
Descriptors: Computer Science Education, Units of Study, Experiential Learning, Electronic Equipment
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Aadarsh Padiyath – ACM Transactions on Computing Education, 2024
As computing educators begin to recognize that their students need strong ethical foundations, there is a growing interest to integrate meaningful ethics education into undergraduate computing curricula. To achieve this, it is crucial to understand how students respond to ethical interventions in the classroom. This review examines the acceptance…
Descriptors: Undergraduate Students, Student Attitudes, Ethics, Intervention
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Muhammad Fawad Akbar Khan; Max Ramsdell; Erik Falor; Hamid Karimi – International Educational Data Mining Society, 2024
This paper undertakes a thorough evaluation of ChatGPT's code generation capabilities, contrasting them with those of human programmers from both educational and software engineering standpoints. The emphasis is placed on elucidating its importance in these intertwined domains. To facilitate a robust analysis, we curated a novel dataset comprising…
Descriptors: Artificial Intelligence, Automation, Computer Science Education, Programming
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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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Hamer, Jessica M. M.; Kemp, Peter E. J.; Wong, Billy; Copsey-Blake, Meggie – International Journal of Science Education, 2023
Despite being in a digital age, the diversity of young people choosing to study and work in computing is of ongoing concern, especially low numbers of girls. This paper aims to determine the profile of students who are more likely to aspire to be computer scientists and provide insights into the key factors that shape their aspirations in this…
Descriptors: Foreign Countries, Secondary School Students, Student Attitudes, Occupational Aspiration
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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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