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Murai, Yumiko; Ikejiri, Ryohei; Yamauchi, Yuhei; Tanaka, Ai; Nakano, Seiko – Interactive Learning Environments, 2023
Cultivating children's creativity and imagination is fundamental to preparing them for an increasingly complex and uncertain future. Engaging in creative learning enables children to think independently and critically, work cooperatively, and take risks while actively engaged in meaningful projects. While current trends in education, such as maker…
Descriptors: Creativity, Imagination, Teaching Methods, Computer Science Education
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Baosen Zhang; Ariana Frkonja-Kuczin; Zhong-Hui Duan; Aliaksei Boika – Journal of Chemical Education, 2023
Computer vision (CV) is a subfield of artificial intelligence (AI) that trains computers to understand our visual world based on digital images. There are many successful applications of CV including face and hand gesture detection, weather recording, smart farming, and self-driving cars. Recent advances in computer vision with machine learning…
Descriptors: Classification, Laboratory Equipment, Visual Aids, Optics
Qian, Yizhou – ProQuest LLC, 2018
With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. This exploratory design-based research (DBR) study implemented a data-driven approach to identify secondary school…
Descriptors: Misconceptions, Data, Decision Making, Computer Science Education
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Tuomi, Pauliina; Multisilta, Jari Antero; Saarikoski, Petri; Suominen, Jaakko – Education and Information Technologies, 2018
Digitalization is one of the most promising ways to increase productivity in the public sector and is needed to reform the economy by creating new innovation related jobs. The implementation of digital services requires problem solving, design skills, logical thinking, an understanding of how computers and networks operate, and programming…
Descriptors: Foreign Countries, Coding, Programming, Computer Science Education
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Li, Jie; van der Linden, Wim J. – Journal of Educational Measurement, 2018
The final step of the typical process of developing educational and psychological tests is to place the selected test items in a formatted form. The step involves the grouping and ordering of the items to meet a variety of formatting constraints. As this activity tends to be time-intensive, the use of mixed-integer programming (MIP) has been…
Descriptors: Programming, Automation, Test Items, Test Format
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Umar Shehzad; Jody Clarke-Midura; Mimi Recker – ACM Transactions on Computing Education, 2024
Objectives: The increasing demand for computing skills has led to a rapid rise in the development of new computer science (CS) curricula, many with the goal of equitably broadening the participation of underrepresented students in CS. While such initiatives are vital, factors outside of the school environment also play a role in influencing…
Descriptors: Parent Child Relationship, Computer Science Education, Programming, Equal Education
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Katharine Childs; Sue Sentance – International Journal of Computer Science Education in Schools, 2024
Gender balance in computing education is a decades-old issue that has been the focus of much previous research. In K-12, the introduction of mandatory computing education goes some way to giving all learners the opportunity to engage with computing throughout school, but a gender imbalance still persists when computer science becomes an elective…
Descriptors: Computer Science Education, Females, Student Attitudes, Elementary School Students
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Sally McHugh; Noel Carroll; Cornelia Connolly – Computers in the Schools, 2024
Citizen Development (CD) is a method of delivering low-code no-code (LCNC) development that empowers subject matter experts to design, develop, and deploy applications into production as though they were full-on, experienced coders. This paper explores teachers' perceptions around the potential for, and enactment of LCNC in our education system.…
Descriptors: Secondary School Teachers, Teacher Empowerment, Teacher Attitudes, Technology Uses in Education
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Balaton, M. C.; Da Silva, L. F.; Carvalho, P. S. – Physics Education, 2020
In this paper, we aim to show strategies for improving graph interpretation skills at middle and high school students using OZOBOT® BIT, a small and relatively low-cost programmable robot which had been used to teach programming to young children. OZOBOT's speed can be controlled by drawing lines with colour codes, as well as through a visual…
Descriptors: Middle School Students, High School Students, Skill Development, Graphs
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Gallego-Romero, Jesús Manuel; Alario-Hoyos, Carlos; Estévez-Ayres, Iria; Delgado Kloos, Carlos – Educational Technology Research and Development, 2020
Massive Open Online Courses (MOOCs) can be enhanced with the so-called learning-by-doing, designing the courses in a way that the learners are involved in a more active way in the learning process. Within the options for increasing learners' interaction in MOOCs, it is possible to integrate (third-party) external tools as part of the instructional…
Descriptors: Learner Engagement, Student Behavior, Learning Analytics, Online Courses
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Daleiden, Patrick; Stefik, Andreas; Uesbeck, P. Merlin; Pedersen, Jan – ACM Transactions on Computing Education, 2020
There are many paradigms available to address the unique and complex problems introduced with parallel programming. These complexities have implications for computer science education as ubiquitous multi-core computers drive the need for programmers to understand parallelism. One major obstacle to student learning of parallel programming is that…
Descriptors: Randomized Controlled Trials, Performance Factors, Programming, Computer Science Education
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Türker, Pinar Mihci; Pala, Ferhat Kadir – International Journal of Computer Science Education in Schools, 2020
In this study, the effect of algorithm education on pre-service teachers' computational thinking skills and computer programming self-efficacy perceptions were examined. In the study, one group pretest posttest experimental design was employed. The participants consisted of 24 (14 males and 10 females) pre-service teachers, majoring in Computer…
Descriptors: Mathematics, Computation, Computer Science Education, Programming
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Kenney, Rachael; An, Tuyin; Kim, Sung-Hee; Uhan, Nelson A.; Yi, Ji Soo; Shamsul, Aiman – International Journal of Science and Mathematics Education, 2020
In linear programming, many students find it difficult to translate a verbal description of a problem into a valid mathematical model. To better understand this, we examine the existing characteristics of college engineering students' errors across linear programming (LP) problems. We examined textbooks to identify the types of problems typically…
Descriptors: Programming, Error Patterns, Engineering Education, Word Problems (Mathematics)
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Grubišic, Ani; Žitko, Branko; Stankov, Slavomir – Journal of Technology and Science Education, 2020
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is…
Descriptors: Electronic Learning, Educational Technology, Models, Intelligent Tutoring Systems
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Margulieux, Lauren E.; Morrison, Briana B.; Decker, Adrienne – International Journal of STEM Education, 2020
Background: Programming a computer is an increasingly valuable skill, but dropout and failure rates in introductory programming courses are regularly as high as 50%. Like many fields, programming requires students to learn complex problem-solving procedures from instructors who tend to have tacit knowledge about low-level procedures that they have…
Descriptors: Programming, Computer Science Education, Introductory Courses, Withdrawal (Education)
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