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Shah, Zohal; Chen, Chen; Sonnert, Gerhard; Sadler, Philip M. – AERA Online Paper Repository, 2023
Computer gameplay and social media are the two most common forms of entertainment in the digital age. Many scholars share the assumption that leisure-time digital consumption is associated with CS affinity, but there is a dearth of research evidence for this relationship. Female students generally spend less time on gaming and more time on social…
Descriptors: Computer Science, Vocational Interests, Computer Use, Gender Differences
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
Ong, Nathan; Zhu, Jiaye; Mossé, Daniel – International Educational Data Mining Society, 2022
Student grade prediction is a popular task for learning analytics, given grades are the traditional form of student performance. However, no matter the learning environment, student background, or domain content, there are things in common across most experiences in learning. In most previous machine learning models, previous grades are considered…
Descriptors: Prediction, Grades (Scholastic), Learning Analytics, Student Characteristics
Hansen, Nils Kristian; Hadjerrouit, Said – International Association for Development of the Information Society, 2021
The purpose of this paper is to investigate students' engagement in computational thinking (CT) and programming with MATLAB when solving a mathematical task in a programming course at the undergraduate level. The data collection method is participant observation of three groups of three students presented with a mathematical task to solve. The…
Descriptors: Computer Science Education, Computer Software, Mathematics Instruction, Teaching Methods
Tan, Wee Lum; Venema, Sven – International Association for Development of the Information Society, 2019
One of the challenges that commencing university students in computing degree programs face is the difficulty in engaging with the abstract and complicated theories in the computing discipline. In particular, it is hard for beginner computer architecture students to visualise the link between the theory of digital logic and the behaviour of the…
Descriptors: Logical Thinking, Computer Science Education, Introductory Courses, Correlation
Broisin, Julien; Hérouard, Clément – International Educational Data Mining Society, 2019
How to support students in programming learning has been a great research challenge in the last years. To address this challenge, prior works have mainly focused on proposing solutions based on syntactic analysis to provide students with personalized feedback about their grammatical programming errors and misconceptions. However, syntactic…
Descriptors: Semantics, Programming, Syntax, Feedback (Response)
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
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
McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2016
Effective mining of data from online submission systems offers the potential to improve educational outcomes by identifying student habits and behaviours and their relationship with levels of achievement. In particular, it may assist in identifying students at risk of performing poorly, allowing for early intervention. In this paper we investigate…
Descriptors: Data Collection, Student Behavior, Academic Achievement, Correlation
Matthews, Paul – Information Research: An International Electronic Journal, 2015
Introduction: This study looked at the effect of community peripheral cues (specifically voting score and answerer's reputation) on the user's credibility rating of answers. Method: Students in technology and philosophy were asked to assess the credibility of answers to questions posted on a social question-answering platform. Through the use of a…
Descriptors: Credibility, Heuristics, College Students, Computer Science Education
Avancena, Aimee Theresa; Nishihara, Akinori; Vergara, John Paul – International Association for Development of the Information Society, 2012
This paper presents the online cognitive and algorithm tests, which were developed in order to determine if certain cognitive factors and fundamental algorithms correlate with the performance of students in their introductory computer science course. The tests were implemented among Management Information Systems majors from the Philippines and…
Descriptors: Foreign Countries, Computer Science Education, High School Students, College Students
Imai, Yoshiro; Imai, Masatoshi; Moritoh, Yoshio – International Association for Development of the Information Society, 2013
This paper presents trial evaluation of a visual computer simulator in 2009-2011, which has been developed to play some roles of both instruction facility and learning tool simultaneously. And it illustrates an example of Computer Architecture education for University students and usage of e-Learning tool for Assembly Programming in order to…
Descriptors: Computer Simulation, Teaching Methods, Cooperative Learning, Programming
Dixon, Victoria A. – 1987
The background of 197 university students from four introductory computer science classes at the State University of New York at Buffalo was investigated to determine factors contributing to academic success or failure in computer science. A background questionnaire, a test of computer science concepts (reading a simple program, symbol…
Descriptors: Academic Achievement, Cognitive Style, Computer Science Education, Correlation
Myers, J. Paul, Jr.; Munsinger, Brita – 1996
This paper investigates the relationship between learning style and programming achievement in two paradigms: imperative and functional. An imperative language achieves its effect by changing the value of variables by means of assignment statements while functional languages rely on evaluation of expressions rather than side-effects. Learning…
Descriptors: Achievement Gains, Cognitive Style, Computer Science Education, Correlation
Quade, Ann M. – 1996
This study examined the roles which note-taking method (either pencil and paper or an online computer notepad) and style (verbatim, paraphrasing, etc.) play in retention and depth of processing during computer-delivered instruction. Participants were 112 junior and senior undergraduates from a southern Minnesota university whose major was computer…
Descriptors: Cognitive Style, Computer Assisted Instruction, Computer Science Education, Correlation
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