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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
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
Mahzoon, Mohammad Javad; Maher, Mary Lou; Eltayeby, Omar; Dou, Wenwen; Grace, Kazjon – Journal of Learning Analytics, 2018
Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a model based on temporal relationships of heterogeneous data as the basis for building predictive models. We show how within- and between-semester temporal patterns can provide insight into the…
Descriptors: Data Analysis, Learning, Models, Time
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
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
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
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
Wan, Han; Liu, Kangxu; Yu, Qiaoye; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2019
Most educational institutions adopted the hybrid teaching mode through learning management systems. The logging data/clickstream could describe learners' online behavior. Many researchers have used them to predict students' performance, which has led to a diverse set of findings, but how to use insights from captured data to enhance learning…
Descriptors: Educational Practices, Learner Engagement, Identification, Study Habits
Kjelvik, Melissa K.; Schultheis, Elizabeth H. – CBE - Life Sciences Education, 2019
Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise…
Descriptors: Data Use, Scientific Research, Information Literacy, STEM Education
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
Bahargam, Sanaz; Erdos, Dóra; Bestavros, Azer; Terzi, Evimaria – International Educational Data Mining Society, 2015
Whether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective; (1) group students so that they can maximally benefit from peer interaction and (2) find an optimal schedule of the educational…
Descriptors: Grouping (Instructional Purposes), Scheduling, Time Factors (Learning), Individualized Instruction
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
Molluzzo, John C.; Lawler, James P. – Information Systems Education Journal, 2015
Big Data is becoming a critical component of the Information Systems curriculum. Educators are enhancing gradually the concentration curriculum for Big Data in schools of computer science and information systems. This paper proposes a creative curriculum design for Big Data Analytics for a program at a major metropolitan university. The design…
Descriptors: Curriculum Design, Data Analysis, Data Collection, Information Systems
Hatun Atas, Amine; Delialioglu, Ömer – Interactive Learning Environments, 2018
The aim of this study was to explore the opinions, perceptions and evaluations of students about their experiences with a question-answer system used on mobile devices in a lecture-based course. Basic qualitative research method was employed in this study to understand how students made sense of their experiences during the instruction. The…
Descriptors: Foreign Countries, College Students, Computer Science Education, Audience Response Systems
Magdin, Martin; Turcáni, Milan – Turkish Online Journal of Educational Technology - TOJET, 2015
Individualization of learning through ICT [Information and Communication Technology] allows to students not only the possibility choose the time and place to study, but especially pace adoption of new knowledge on the basis of preferred learning styles. Analysis of learning processes should give the answer to difficult questions from pedagogical…
Descriptors: Management Systems, Information Technology, Electronic Learning, Cognitive Style