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Showing 61 to 75 of 2,156 results Save | Export
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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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Chamindi Kavindya Samarasekara; Claudia Ott; Anthony Robins – Education and Information Technologies, 2024
A global concern in recent years has been the formal incorporation of computing and digital technology subjects into high school curricula. Despite many initiatives to make these subjects accessible to students, significant barriers to uptake remain in many countries. In this study we convened a panel of 32 academic, research, and other experts…
Descriptors: Secondary School Curriculum, Foreign Countries, Computer Science Education, Programming
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YungYu Zhuang; Yu-Hsuan Lin; Mahesh Liyanawatta; Andito Haryo Saputro; Yuniati Dwi Utami; Jen-Hang Wang – Interactive Learning Environments, 2024
Computer programming is essential nowadays but still challenging to learn due to its invisible thinking. Current programming environments are mostly designed for operating on computers directly to learn concrete programming, but this approach lacks the support for clarifying learners' thinking processes. On the other hand, using paper and pens…
Descriptors: Educational Environment, Thinking Skills, Programming, Computer Science Education
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Jens Dörpinghaus; Johanna Binnewitt; David Samray; Kristine Hein – ACM Transactions on Computing Education, 2024
Objectives: The purpose of this study is to reveal the importance of informatics in continuing vocational education in Germany. The labour market is a field with diverse data structures and multiple applications, for example connecting jobseekers and trainings or jobs. The labour market heavily relies on vocational education and training and…
Descriptors: Foreign Countries, Information Science Education, Computer Science Education, Vocational Education
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Torres Jiménez, Stephanie; Ramírez-Echeverry, Jhon Jairo; Restrepo-Calle, Felipe – Journal of Educational Computing Research, 2024
This article presents the design, construct validation, and reliability of a self-report instrument in Spanish that aims to characterize different types of strategies that students can use to learn computer programming. We provide a comprehensive overview of the identification of learning strategies in the existing literature, the design and…
Descriptors: Test Construction, Construct Validity, Test Reliability, Questionnaires
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Ruth Z. Hauzel; Tanuja Pattnaik; Ranjani Vara; Surya Prabha Mandela – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: Despite playing a critical role in shaping the future, 70% of undergraduate engineers report low levels of motivation. Student disengagement and a lack of ownership of their learning are significant challenges in higher education, specifically engineering students in the computer science department. This study investigates the various…
Descriptors: Undergraduate Students, Engineering Education, Learner Engagement, Student Attitudes
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Almabrok Musa Almdahem – International Journal of Computer Science Education in Schools, 2024
A national curriculum for the study of computing became compulsory in English secondary schools in September 2014, replacing the study of information and communications technology with computer science (CS). This posed difficulties for teachers and students who did not have knowledge or experience of programming. This study was designed to…
Descriptors: Secondary School Students, Computer Science Education, Programming, Student Attitudes
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Jacqueline Nijenhuis-Voogt; Durdane Bayram; Paulien C. Meijer; Erik Barendsen – International Journal of Computer Science Education in Schools, 2024
A context-based approach to education aims to improve students' meaningful learning and uses authentic situations in which scientific concepts are applied. The use of contexts may contribute to the learning of abstract concepts such as algorithms. The selection of appropriate contexts, however, is challenging for teachers. It is therefore…
Descriptors: Secondary Education, Computer Science Education, Secondary School Science, Algorithms
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Ella R. Kahu; Heather G. Thomas; Eva Heinrich – Active Learning in Higher Education, 2024
Whether by choice or pushed online by Covid, higher education is increasingly happening in digital spaces with digital tools forming a critical part of learning and teaching contexts. While reviews suggest such tools positively influence student engagement, research tends to be generic and more is needed to understand how and why specific tools…
Descriptors: Foreign Countries, Undergraduate Students, Computer Science Education, Information Networks
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Julia Tomanova; Martin Vozar; Dasa Munkova – International Journal of Education in Mathematics, Science and Technology, 2024
The study focuses on the identification of relationships and/or rules between computational thinking (CT) concepts among the undergraduate students of Applied Informatics due to their attitudes towards mathematics. We analyze three CT concepts -- decomposition, pattern recognition, and algorithmic thinking. We assume that students who have a…
Descriptors: Computation, Thinking Skills, Student Attitudes, Undergraduate Students
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André Coners; Benjamin Matthies; Carolin Vollenberg; Julian Koch – Journal of Statistics and Data Science Education, 2025
The proficient handling of data can undoubtedly be regarded as a key skill for the future. However, the need for data competencies is not limited to traditional professions in the information technology environment but is rather necessary across industries and work fields. Consequently, there is a call to integrate such Data Literacy and Data…
Descriptors: Statistics Education, Higher Education, Information Science Education, Computer Science Education
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Huang, Xiaodong – Education and Information Technologies, 2021
Cultivating students' key competencies contributes to students' adaptation to the fast developing intelligent era. Artificial intelligence education is an important way to cultivate students' key competencies. It is increasingly important to set up appropriate artificial intelligence courses at the fundamental education stage and cultivate…
Descriptors: Foreign Countries, Artificial Intelligence, Computer Science Education, Competence
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Akdur, Deniz – ACM Transactions on Computing Education, 2023
Many practitioners might struggle with becoming productive in different software engineering (SE) roles due to misalignment of the skills learnt during the university time with what is expected in the industry. Companies spend significant resources to train the personnel, whose academic backgrounds are not only based on "computing…
Descriptors: Computer Software, Computer Science Education, Skill Development, Employment Potential
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Alajlan, Hayat A. – Technology, Knowledge and Learning, 2023
The purpose of this quasi-experimental design study was to investigate and compare flipped learning (FL) and traditional learning (TL), and how FL impacts on student performance, participation and perceptions in higher education in Saudi Arabia. FL as an instructional approach has received much attention as a way to center learning on students in…
Descriptors: Flipped Classroom, Conventional Instruction, College Students, 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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