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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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Çetinkaya-Rundel, Mine; Dogucu, Mine; Rummerfield, Wendy – Statistics Education Research Journal, 2022
Many data science applications involve generating questions, acquiring data and preparing it for analysis--be it exploratory, inferential, or modeling focused--and communicating findings. Most data science curricula address each of these steps as separate units in a course or as separate courses. Open-ended term projects, however, allow students…
Descriptors: Introductory Courses, Data Analysis, Statistics Education, Units of Study
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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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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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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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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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Orr, J. Walker; Russell, Nathaniel – International Educational Data Mining Society, 2021
The assessment of program functionality can generally be accomplished with straight-forward unit tests. However, assessing the design quality of a program is a much more difficult and nuanced problem. Design quality is an important consideration since it affects the readability and maintainability of programs. Assessing design quality and giving…
Descriptors: Programming Languages, Feedback (Response), Units of Study, Computer Science Education
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Lu, Owen H. T.; Huang, Anna Y. Q.; Tsai, Danny C. L.; Yang, Stephen J. H. – Educational Technology & Society, 2021
Human-guided machine learning can improve computing intelligence, and it can accurately assist humans in various tasks. In education research, artificial intelligence (AI) is applicable in many situations, such as predicting students' learning paths and strategies. In this study, we explore the benefits of repetitive practice of short-answer…
Descriptors: Test Items, Artificial Intelligence, Test Construction, Student Evaluation
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Troy, Jesse D.; Neely, Megan L.; Pomann, Gina-Maria; Grambow, Steven C.; Samsa, Gregory P. – Journal of Curriculum and Teaching, 2022
Student evaluation is a key consideration for educational program administrators because program success depends on students' ability to demonstrate successful development of core competencies. Student evaluations must therefore be aligned with learning objectives and overall program goals. Graduate level educational programs typically incorporate…
Descriptors: Student Evaluation, Evaluation Methods, Statistics Education, Alignment (Education)