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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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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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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)
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Kunkle, Wanda M.; Allen, Robert B. – ACM Transactions on Computing Education, 2016
Learning to program, especially in the object-oriented paradigm, is a difficult undertaking for many students. As a result, computing educators have tried a variety of instructional methods to assist beginning programmers. These include developing approaches geared specifically toward novices and experimenting with different introductory…
Descriptors: Teaching Methods, Programming, Programming Languages, Computer Science Education
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Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D. – IEEE Transactions on Learning Technologies, 2014
In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…
Descriptors: Artificial Intelligence, Concept Mapping, Teaching Methods, Student Evaluation
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Laverty, David M.; Milliken, Jonny; Milford, Matthew; Cregan, Michael – European Journal of Engineering Education, 2012
This paper presents a new laboratory-based module for embedded systems teaching, which addresses the current lack of consideration for the link between hardware development, software implementation, course content and student evaluation in a laboratory environment. The course introduces second year undergraduate students to the interface between…
Descriptors: Foreign Countries, Engineering Education, Student Evaluation, Computer Assisted Instruction
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d'Amore, Roberto – ACM Transactions on Computing Education, 2010
This article proposes a VHDL language course that establishes a strong correlation between the language statements and their use in circuit synthesis. Two course modules are described: a basic module that contains the essential concepts of the language, sufficient for students to describe medium complexity circuits, followed by a second module…
Descriptors: Feedback (Response), Units of Study, Courses, Laboratories