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Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
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Serap Çimsir; Filiz Kalelioglu; Yasemin Gülbahar – Informatics in Education, 2024
This study aims to examine the impact of interdisciplinary computational thinking (CT) skills training on primary school teachers' perceptions of CT skills. The sample of the study consisted of 30 primary school teachers in Istanbul. In this study, where quantitative and qualitative methods were used together, qualitative data were obtained from…
Descriptors: Teacher Attitudes, Computer Science Education, Interdisciplinary Approach, Thinking Skills
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Muhammed Murat Gümüs; Volkan Kukul; Özgen Korkmaz – Informatics in Education, 2024
This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to…
Descriptors: Correlation, Middle School Students, Thinking Skills, Digital Literacy
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Mariyam Abdulhadi; Fred Awaah; Deborah Agbanimu; Emmanuel Okyere Ekwam; Emmanuella Sefiamor Heloo – Journal of Research in Innovative Teaching & Learning, 2024
Purpose: The lecture method has been compared with teaching methods such as flip learning, cooperative learning and simulations to establish which holds the key to students' understanding of concepts. What is bereft in the education literature is its comparative efficiency with the culturo-techno contextual approach (CTCA) in the teaching of…
Descriptors: Foreign Countries, Developing Nations, Computer Science Education, Cultural Context
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Dalia Khairy; Nouf Alharbi; Mohamed A. Amasha; Marwa F. Areed; Salem Alkhalaf; Rania A. Abougalala – Education and Information Technologies, 2024
Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…
Descriptors: Prediction, Tests, Scores, Information Retrieval
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Ella Christiaans; So Yeon Lee; Kristy A. Robinson – Educational Psychology, 2024
Students want to learn computer science due to its usefulness for future careers, however they often meet challenges in introductory courses. In the increasingly digital world, it is important to understand some important psychological consequences of such challenges: perceived costs of pursuing computer science. This study thus investigated…
Descriptors: Undergraduate Students, Computer Science Education, Psychological Patterns, Student Attitudes
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Zachary M. Savelson; Kasia Muldner – Computer Science Education, 2024
Background and Context: Productive failure (PF) is a learning paradigm that flips the order of instruction: students work on a problem, then receive a lesson. PF increases learning, but less is known about student emotions and collaboration during PF, particularly in a computer science context. Objective: To provide insight on students' emotions…
Descriptors: Student Attitudes, Psychological Patterns, Fear, Failure
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Oscar Karnalim; Simon; William Chivers – Computer Science Education, 2024
Background and Context: To educate students about programming plagiarism and collusion, we introduced an approach that automatically reports how similar a submitted program is to others. However, as most students receive similar feedback, those who engage in plagiarism and collusion might feel inadequately warned. Objective: When students are…
Descriptors: Teaching Methods, Plagiarism, Computer Science Education, Programming
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Wilson Libardo Pantoja Yépez; Julio Ariel Hurtado Alegría; Ajay Bandi; Arvind W. Kiwelekar – Education and Information Technologies, 2024
The ability to define, evaluate, and implement software architectures is a fundamental skill for software engineers. However, teaching software architecture can be challenging as it requires students to be involved in real-context projects with high degrees of complexity. This involves making trade-off decisions among several quality attributes.…
Descriptors: Computer Software, Training, Computer Science Education, Teaching Methods
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Jin Wei-Kocsis; Moein Sabounchi; Gihan J. Mendis; Praveen Fernando; Baijian Yang; Tonglin Zhang – IEEE Transactions on Education, 2024
Contribution: A novel proactive and collaborative learning paradigm was proposed to engage learners with different backgrounds and enable effective retention and transfer of the multidisciplinary artificial intelligence (AI)-cybersecurity knowledge. Specifically, the proposed learning paradigm contains: 1) an immersive learning environment to…
Descriptors: Computer Security, Artificial Intelligence, Interdisciplinary Approach, Models
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Nicole D. Martin; Stephanie N. Baker; Madeline Haynes; Jayce R. Warner – Computer Science Education, 2024
Background and Context: As computer science (CS) education expands and the need for well-prepared CS teachers grows, understanding what motivates teachers to teach CS can help address challenges to recruiting, preparing, and retaining teachers. Objective: The goal of this work was to develop and validate a scale that measures teachers' motivation…
Descriptors: Computer Science Education, Teacher Motivation, Measurement Techniques, Construct Validity
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Niklas Humble – International Journal of Educational Technology in Higher Education, 2024
The idea of Artificial intelligence (AI) has a long history in both research and fiction and has been applied in educational settings since the 1970s. However, the topic of AI underwent a huge increase of interest with the release of ChatGPT in late 2022, and more people were talking about generative AI (GenAI or GAI). According to some estimates,…
Descriptors: Risk Management, Artificial Intelligence, Computer Software, Barriers
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Lukas Höper; Carsten Schulte – Information and Learning Sciences, 2024
Purpose: In today's digital world, data-driven digital artefacts pose challenges for education, as many students lack an understanding of data and feel powerless when interacting with them. This paper aims to address these challenges and introduces the data awareness framework. It focuses on understanding data-driven technologies and reflecting on…
Descriptors: Information Literacy, Elementary Secondary Education, Data, Grade 6
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Michael Karlin; Anne Ottenbreit-Leftwich; Yin-Chan Janet Liao – International Journal of Computer Science Education in Schools, 2024
A significant gender gap continues to exist within computer science (CS) education, despite nationwide emphasis in the U.S. on improving CS education equity and access. To explore this issue, we conducted an ethnographic case study within a classroom at Forest View High School (FVHS, pseudonym) where girls' participation in CS was consistently…
Descriptors: Computer Science Education, Student Experience, Teaching Experience, High School Students
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Loïs Vanhée; Karin Danielsson; Lena Enqvist; Kalle Grill; Melania Borit – European Journal of Education, 2024
Whereas hackathons are widespread within and outside academia and have been argued to be a valid pedagogical method for teaching interdisciplinarity, no detailed frameworks or methods are available for conceptualizing and organizing educational hackathons, i.e., hackathons dedicated to best achieving pedagogic objectives. This paper is dedicated…
Descriptors: Interdisciplinary Approach, Learning Activities, Programming, Computer Security
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