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Draper, Steve; Maguire, Joseph – ACM Transactions on Computing Education, 2023
The overall aim of this article is to stimulate discussion about the activities within CER, and to develop a more thoughtful and explicit perspective on the different types of research activity within CER, and their relationships with each other. While theories may be the most valuable outputs of research to those wishing to apply them, for…
Descriptors: Computer Science Education, Educational Research, Computer Science, Classification
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Simao de Deus, William; Barbosa, Ellen Francine – IEEE Transactions on Education, 2022
Contribution: This study presents the results of a systematic mapping on the classification and organization of open educational resources (OERs) focused on Computer Science Education (CSEd) in digital sources. Background: The number of open resources (e.g., images, videos, and websites) available on the Internet for the teaching of Computer…
Descriptors: Classification, Open Educational Resources, Computer Science Education, Search Strategies
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Bayan Masarwa; Hagit Hel-Or; Sharona T. Levy – Journal of Research in Childhood Education, 2024
Computational thinking (CT) activities are increasingly being integrated into early childhood schools. We focus on studying children's learning using an "unplugged" (non-computational) learning unit that considers a teacher's knowledge and classroom space and affords seamless adaptation into the classroom given the objects used in the…
Descriptors: Kindergarten, Computation, Thinking Skills, Educational Games
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Carina Büscher – International Journal of Science and Mathematics Education, 2025
Computational thinking (CT) is becoming increasingly important as a learning content. Subject-integrated approaches aim to develop CT within other subjects like mathematics. The question is how exactly CT can be integrated and learned in mathematics classrooms. In a case study involving 12 sixth-grade learners, CT activities were explored that…
Descriptors: Mathematics Instruction, Thinking Skills, Teaching Methods, Computer Science Education
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O. S. Adewale; O. C. Agbonifo; E. O. Ibam; A. I. Makinde; O. K. Boyinbode; B. A. Ojokoh; O. Olabode; M. S. Omirin; S. O. Olatunji – Interactive Learning Environments, 2024
With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…
Descriptors: Cognitive Style, Individualized Instruction, Learning Processes, Preferences
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Jeff Hanson; Blair Taylor; Siddharth Kaza – Information Systems Education Journal, 2025
Cybersecurity content is typically taught and assessed using Bloom's Taxonomy to ensure that students acquire foundational and higher-order knowledge. In this study we show that when students are given the objectives written in the form of a competency-based statements, students have a more clearly defined outcome and are be able to exhibit their…
Descriptors: College Students, Universities, Competency Based Education, Educational Objectives
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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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Obeng, Asare Yaw – Cogent Education, 2023
The learning processes have been significantly impacted by technology. Numerous learners have adopted technology-based learning systems as the preferred form of learning. It is then necessary to identify the learning styles of learners to deliver appropriate resources, engage them, increase their motivation, and enhance their satisfaction and…
Descriptors: Predictor Variables, Cognitive Style, Electronic Learning, College Freshmen
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Fein, Benedikt; Graßl, Isabella; Beck, Florian; Fraser, Gordon – International Educational Data Mining Society, 2022
The recent trend of embedding source code for machine learning applications also enables new opportunities in learning analytics in programming education, but which code embedding approach is most suitable for learning analytics remains an open question. A common approach to embedding source code lies in extracting syntactic information from a…
Descriptors: Artificial Intelligence, Learning Analytics, Programming, Programming Languages
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Sara Ricci; Simon Parker; Jan Jerabek; Yianna Danidou; Argyro Chatzopoulou; Remi Badonnel; Imre Lendak; Vladimir Janout – IEEE Transactions on Education, 2024
Demand for cybersecurity professionals from industry and institutions is high, driven by an increasing digitization of society and the growing range of potential targets for cyber attacks. However, despite this pressing need a significant shortfall in the number of cybersecurity experts remains and a discrepancy has emerged between the skills…
Descriptors: Information Security, Computer Security, Classification, Barriers
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Anna Fergusson; Maxine Pfannkuch – Journal of Statistics and Data Science Education, 2024
Statistics teaching at the high school level needs modernizing to include digital sources of data that students interact with every day. Algorithmic modeling approaches are recommended, as they can support the teaching of data science and computational thinking. Research is needed about the design of tasks that support high school statistics…
Descriptors: High School Students, Statistics Education, Thinking Skills, Computer Science Education
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Ben-Yaacov, Anat; Hershkovitz, Arnon – Journal of Educational Computing Research, 2023
Block programming has been suggested as a way of engaging young learners with the foundations of programming and computational thinking in a syntax-free manner. Indeed, syntax errors--which form one of two broad categories of errors in programming, the other one being logic errors--are omitted while block programming. However, this does not mean…
Descriptors: Programming, Computation, Thinking Skills, Error Patterns
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Ryan, Zachary D.; DeLiema, David – Instructional Science: An International Journal of the Learning Sciences, 2023
This paper articulates an approach to incorporating instructor feedback in design-based research. Throughout the process of designing and implementing curriculum to support middle school students' debugging practices in a summer computer science workshop, our research and practice team utilized instructor-generated conjecture maps as boundary…
Descriptors: Teaching Methods, Feedback (Response), Teacher Attitudes, Computer Science Education
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Barbosa Rocha, Hemilis Joyse; Cabral De Azevedo Restelli Tedesco, Patrícia; De Barros Costa, Evandro – Informatics in Education, 2023
In programming problem solving activities, sometimes, students need feedback to progress in the course, being positively affected by the received feedback. This paper presents an overview of the state of the art and practice of the feedback approaches on introductory programming. To this end, we have carried out a systematic literature mapping to…
Descriptors: Classification, Computer Science Education, Feedback (Response), Problem Solving
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Gao, Zhikai; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2021
As Computer Science has increased in popularity so too have class sizes and demands on faculty to provide support. It is therefore more important than ever for us to identify new ways to triage student questions, identify common problems, target students who need the most help, and better manage instructors' time. By analyzing interaction data…
Descriptors: Automation, Classification, Help Seeking, Computer Science Education
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