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Showing 1 to 15 of 98 results Save | Export
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Chengliang Wang; Xiaojiao Chen; Yifei Li; Pengju Wang; Haoming Wang; Yuanyuan Li – Journal of Educational Computing Research, 2025
This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students' multidimensional development. Utilizing a quasi-experimental research design, this study compared students' programming learning achievements (PLA),…
Descriptors: Programming, Computer Science Education, Metacognition, Computer Simulation
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Zengqing Wu; Huizhong Liu; Chuan Xiao – IEEE Transactions on Education, 2024
Contribution: This research illuminates information entropy's efficacy as a pivotal educational tool in programming, enabling the precise quantification of algorithmic complexity and student abstraction levels for solving problems. This approach can provide students quantitative, comparative insights into the differences between optimal and…
Descriptors: Information Theory, Student Evaluation, Thinking Skills, Algorithms
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Metcalf, Shari J.; Reilly, Joseph M.; Jeon, Soobin; Wang, Annie; Pyers, Allyson; Brennan, Karen; Dede, Chris – Computer Science Education, 2021
Background and Context: This study looks at computational thinking (CT) assessment of programming artifacts within the context of CT integrated with science education through computational modeling. Objective: The goal is to explore methodologies for assessment of student-constructed computational models through two lenses: functionality and…
Descriptors: Evaluation Methods, Computation, Thinking Skills, Science Education
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Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
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Erkan Er; Gökhan Akçapinar; Alper Bayazit; Omid Noroozi; Seyyed Kazem Banihashem – British Journal of Educational Technology, 2025
Despite the growing research interest in the use of large language models for feedback provision, it still remains unknown how students perceive and use AI-generated feedback compared to instructor feedback in authentic settings. To address this gap, this study compared instructor and AI-generated feedback in a Java programming course through an…
Descriptors: Student Evaluation, Student Attitudes, Feedback (Response), Artificial Intelligence
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Chotika Wanglang; Kobkiat Sraubon; Pallop Piriyasurawong – Higher Education Studies, 2024
This research aims to develop a combining game-based learning with design thinking using block-based programming to enhance computational thinking and creative games for primary students and will be referred to as game-based learning from now on. The purpose of this research is to 1) develop a model for game-based learning, 2) develop the system…
Descriptors: Game Based Learning, Design, Thinking Skills, Programming
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Oscar Karnalim – Informatics in Education, 2024
Programming students need to be informed about plagiarism and collusion. Hence, we developed an assessment submission system to remind students about the matter. Each submission will be compared to others and any similarities that do not seem a result of coincidence will be reported along with their possible reasons. The system also employs…
Descriptors: Programming, Integrity, Academic Achievement, Plagiarism
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Ellie Lovellette; Dennis J. Bouvier; John Matta – ACM Transactions on Computing Education, 2024
In recent years, computing education researchers have investigated the impact of problem context on students' learning and programming performance. This work continues the investigation motivated, in part, by cognitive load theory and educational research in computer science and other disciplines. The results of this study could help inform…
Descriptors: Computer Science Education, Student Evaluation, Context Effect, Problem Solving
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Grethe Sandstrak; Bjorn Klefstad; Arne Styve; Kiran Raja – IEEE Transactions on Education, 2024
Teaching programming efficiently to students in the first year of computer science education is challenging. It is especially cumbersome to retain the interest of both groups, when the student group consists of novice (i.e., those who have never programmed before) and expert programmers in the same crowd. Thus, individualized teaching cannot be…
Descriptors: Computer Science Education, Programming, Teaching Methods, College Freshmen
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Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
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Vesin, Boban; Mangaroska, Katerina; Akhuseyinoglu, Kamil; Giannakos, Michail – ACM Transactions on Computing Education, 2022
Online learning systems should support students preparedness for professional practice by equipping them with the necessary skills while keeping them engaged and active. In that regard, the development of online learning systems that support students' development and engagement with programming is a challenging process. Early career computer…
Descriptors: Adaptive Testing, Online Courses, Programming, Computer Science Education
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Hijón Neira, Raquel; García-Iruela, Miguel; Connolly, Cornelia – International Journal of Computer Science Education in Schools, 2021
Effective and reliable assessment approaches to computational thinking in secondary education are in demand. This paper uses a guided technological pedagogical content knowledge (TPACK) framework, incorporating a visual execution environment (VEE) and Scratch project for secondary school students as a method to teach and assess computational…
Descriptors: Computation, Thinking Skills, Pedagogical Content Knowledge, Technological Literacy
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Yang, Fan; Akanbi, Temitope; Chong, Oscar Wong; Zhang, Jiansong; Debs, Luciana; Chen, Yunfeng; Hubbard, Bryan J. – Journal of Civil Engineering Education, 2024
Computing technology is reshaping the way in which professionals in the architecture, engineering, and construction industries conduct their business. The execution of construction tasks is changing from traditional 2D to 3D building information modeling (BIM)-based concepts. The use of BIM is expanded and enriched by the introduction of advanced…
Descriptors: Civil Engineering, Engineering Education, Programming Languages, Construction Management
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Gwo-Haur Hwang; Beyin Chen; Shih-Pei Chen – Interactive Learning Environments, 2024
This study proposed a game-based flipped teaching approach and applied it to a HTML (HyperText Markup Language) course. We developed two versions of the pre-class content testing, one of which was game-based, using a "looking-through" game, and the other which was traditional, using a multiple-choice test. We conducted a teaching…
Descriptors: Flipped Classroom, Instructional Effectiveness, Teaching Methods, Prior Learning
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Jui-Hung Chang; Chi-Jane Wang; Hua-Xu Zhong; Hsiu-Chen Weng; Yu-Kai Zhou; Hoe-Yuan Ong; Chin-Feng Lai – Educational Technology Research and Development, 2024
Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students' learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study…
Descriptors: Artificial Intelligence, Technological Advancement, Student Evaluation, Models
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