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Yong-Woon Choi; In-gyu Go; Yeong-Jae Gil – International Journal of Technology and Design Education, 2024
The purpose of this study is to derive a correlation between the technological thinking disposition and the computational thinking ability of gifted students in Korea. The correlation between each element was analyzed by looking at the sub-elements of computational thinking according to the components of technological thinking disposition. The…
Descriptors: Thinking Skills, Mental Computation, Gifted, Correlation
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Shabrina, Preya; Mostafavi, Behrooz; Tithi, Sutapa Dey; Chi, Min; Barnes, Tiffany – International Educational Data Mining Society, 2023
Problem decomposition into sub-problems or subgoals and recomposition of the solutions to the subgoals into one complete solution is a common strategy to reduce difficulties in structured problem solving. In this study, we use a datadriven graph-mining-based method to decompose historical student solutions of logic-proof problems into Chunks. We…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Graphs, Data Analysis
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Hundhausen, C. D.; Conrad, P. T.; Carter, A. S.; Adesope, O. – Computer Science Education, 2022
Background and Context: Assessing team members' indivdiual contributions to software development projects poses a key problem for computing instructors. While instructors typically rely on subjective assessments, objective assessments could provide a more robust picture. To explore this possibility, In a 2020 paper, Buffardi presented a…
Descriptors: Computer Software, Computer Science Education, Correlation, Engineering Education
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Legacy, Chelsey; Zieffler, Andrew; Fry, Elizabeth Brondos; Le, Laura – Statistics Education Research Journal, 2022
The influx of data and the advances in computing have led to calls to update the introductory statistics curriculum to better meet the needs of the contemporary workforce. To this end, we developed the COMputational Practices in Undergraduate TEaching of Statistics (COMPUTES) instrument, which can be used to measure the extent to which computation…
Descriptors: Statistics Education, Introductory Courses, Undergraduate Students, Teaching Methods
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Loftus, Mary; Madden, Michael G. – Teaching in Higher Education, 2020
How do we teach and learn with our students about data literacy, at the same time as Biesta (2015) calls for an emphasis on 'subjectification' i.e. 'the coming into presence of unique individual beings'? (Good Education in an Age of Measurement: Ethics, Politics, Democracy. Routledge) Our response to these challenges and the datafication of higher…
Descriptors: Teaching Methods, Data Analysis, Literacy, Learning Processes
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Reilly, Joseph M.; Schneider, Bertrand – International Educational Data Mining Society, 2019
Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…
Descriptors: Problem Solving, Discourse Analysis, Cooperative Learning, Computer Assisted Instruction
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Atapattu, Thushari; Falkner, Katrina – Journal of Learning Analytics, 2018
Lecture videos are amongst the most widely used instructional methods within present Massive Open Online Courses (MOOCs) and other digital educational platforms. As the main form of instruction, student engagement behaviour, including interaction with videos, directly impacts the student success or failure and accordingly, in-video dropouts…
Descriptors: Lecture Method, Video Technology, Online Courses, Mass Instruction
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Casola, Linda – National Academies Press, 2020
Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and…
Descriptors: Meetings, Data Analysis, Postsecondary Education, Statistics Education
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Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis
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Miller, L. Dee; Soh, Leen-Kiat; Samal, Ashok; Kupzyk, Kevin; Nugent, Gwen – Journal of Educational Data Mining, 2015
Learning objects (LOs) are important online resources for both learners and instructors and usage for LOs is growing. Automatic LO tracking collects large amounts of metadata about individual students as well as data aggregated across courses, learning objects, and other demographic characteristics (e.g. gender). The challenge becomes identifying…
Descriptors: Comparative Analysis, Data Analysis, Hierarchical Linear Modeling, Electronic Learning
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Saarela, Mirka; Karkkainen, Tommi – Journal of Educational Data Mining, 2015
Curricula for Computer Science (CS) degrees are characterized by the strong occupational orientation of the discipline. In the BSc degree structure, with clearly separate CS core studies, the learning skills for these and other required courses may vary a lot, which is shown in students' overall performance. To analyze this situation, we apply…
Descriptors: Data Analysis, Academic Achievement, Undergraduate Students, Core Curriculum
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McMaster, Kirby; Hadfield, Steven; Wolthuis, Stuart; Sambasivam, Samuel – Information Systems Education Journal, 2012
This research examines the frameworks used by Computer Science and Information Systems students at the conclusion of their first semester of study of Software Engineering. A questionnaire listing 64 Software Engineering concepts was given to students upon completion of their first Software Engineering course. This survey was given to samples of…
Descriptors: Computer Software, Computer Science Education, Engineering, Models
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Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
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Kadijevich, Djordje M. – Journal of Educational Computing Research, 2012
By using a sample of 1st-year undergraduate business students, this study dealt with the development of simple (deterministic and non-optimization) spreadsheet models of income statements within an introductory course on business informatics. The study examined students' errors in doing this for business situations of their choice and found three…
Descriptors: Foreign Countries, Spreadsheets, Decision Support Systems, Teaching Methods
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Wee, Mee-Chin; Abrizah, A.; Por, Lip Yee – Journal of Educational Computing Research, 2012
A CMI-based online forum is designed to address the need for a system to manage students' online participation. The proposed system may reduce the time required to manage online participation. The system was evaluated by a total of 64 students enrolled in an academic semester. The evaluation has two objectives. The first was to determine the…
Descriptors: Foreign Countries, Discussion, Computer Software Evaluation, Computer Software
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