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Showing 1 to 15 of 27 results Save | Export
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Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
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Vance, Eric A. – Journal of Statistics and Data Science Education, 2021
Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative…
Descriptors: Cooperative Learning, Data Analysis, Statistics Education, Flipped Classroom
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Gitinabard, Niki; Okoilu, Ruth; Xu, Yiqao; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin – International Educational Data Mining Society, 2020
Teamwork, often mediated by version control systems such as Git and Apache Subversion (SVN), is central to professional programming. As a consequence, many colleges are incorporating both collaboration and online development environments into their curricula even in introductory courses. In this research, we collected GitHub logs from two…
Descriptors: Teamwork, Group Activities, Student Projects, Programming
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Schwab-McCoy, Aimee; Baker, Catherine M.; Gasper, Rebecca E. – Journal of Statistics and Data Science Education, 2021
In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…
Descriptors: Statistics Education, Higher Education, College Students, Teaching Methods
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Lin, Guan-Yu – Journal of Educational Computing Research, 2016
This study has two central purposes: First, it examines not only the roles of gender and persistence in undergraduate computing majors' learning self-efficacy, computer self-efficacy, and programming self-efficacy but also Bandura's hypothesized sources of self-efficacy; second, it examines the influence of sources of efficacy on the three…
Descriptors: Sex Role, Persistence, Self Efficacy, Beliefs
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Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
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Mangaroska, Katerina; Sharma, Kshitij; Giannakos, Michail; Træteberga, Hallvard; Dillenbourg, Pierre – Journal of Learning Analytics, 2018
This study investigates how multimodal user-generated data can be used to reinforce learner reflection, improve teaching practices, and close the learning analytics loop. In particular, the aim of the study is to utilize user gaze and action-based data to examine the role of a mirroring tool (i.e., Exercise View in Eclipse) in orchestrating basic…
Descriptors: Eye Movements, Student Behavior, Computer Science Education, Programming
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Ahadi, Alireza; Hellas, Arto; Lister, Raymond – ACM Transactions on Computing Education, 2017
We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online…
Descriptors: Data Analysis, Online Courses, Computer Science Education, Programming
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Mao, Ye; Zhi, Rui; Khoshnevisan, Farzaneh; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2019
Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…
Descriptors: Difficulty Level, Learning Activities, Prediction, Programming
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Hew, Khe Foon; Qiao, Chen; Tang, Ying – International Review of Research in Open and Distributed Learning, 2018
Although massive open online courses (MOOCs) have attracted much worldwide attention, scholars still understand little about the specific elements that students find engaging in these large open courses. This study offers a new original contribution by using a machine learning classifier to analyze 24,612 reflective sentences posted by 5,884…
Descriptors: Learner Engagement, Large Group Instruction, Online Courses, Man Machine Systems
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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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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
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Ivancevic, Vladimir – Journal of Learning Analytics, 2014
Tests targeting the upper limits of student ability could aid students in their learning. This article gives an overview of an approach to the construction of such tests in programming, together with ideas on how to implement and refine them within a learning management system.
Descriptors: Item Banks, Educational Research, Data Collection, Data Analysis
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Yang, Ya-Fei; Lee, Chien-I; Chang, Chih-Kai – Education for Information, 2016
Collaborative learning is an activity in which two or more students learn something together. Many studies have found that collaborative learning improve students' memory retention and motivation to learn. Peer Instruction (PI) is one of the most successful evidence-based collaborative learning methods. This article investigates issues of student…
Descriptors: Learning Motivation, Retention (Psychology), Computer Science Education, Programming
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