NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 21 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Yin-Rong Zhang; Zhong-Mei Han; Tao He; Chang-Qin Huang; Fan Jiang; Gang Yang; Xue-Mei Wu – Journal of Computer Assisted Learning, 2025
Background: Collaborative programming is important and challenging for K12 students. Scaffolding is a vital method to support students' collaborative programming learning. However, conventional scaffolding that does not fade may lead students to become overly dependent, resulting in unsatisfactory programming performance. Objectives: This study…
Descriptors: Middle School Students, Grade 8, Scaffolding (Teaching Technique), Programming
Peer reviewed Peer reviewed
Direct linkDirect link
Du, Xiaoming; Ge, Shilun; Wang, Nianxin – International Journal of Information and Communication Technology Education, 2022
In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior…
Descriptors: Prediction, Data, Student Behavior, Academic Achievement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2022
The challenge of learning programming in a MOOC is twofold: acquiring programming skills and learning online, independently. Automated testing and feedback systems, often offered in programming courses, may scaffold MOOC learners by providing immediate feedback and unlimited re-submissions of code assignments. However, research still lacks…
Descriptors: Automation, Feedback (Response), Student Behavior, MOOCs
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
Peer reviewed Peer reviewed
Direct linkDirect link
Ghadeer Sawalha; Imran Taj; Abdulhadi Shoufan – Cogent Education, 2024
Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…
Descriptors: Cues, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Mohammed Alzaid – ProQuest LLC, 2022
Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…
Descriptors: Learning Analytics, Self Evaluation (Individuals), Programming, Problem Solving
Peer reviewed Peer reviewed
Direct linkDirect link
Celis Rangel, Jakeline G.; King, Melissa; Muldner, Kasia – ACM Transactions on Computing Education, 2020
Learning to program requires perseverance, practice, and the mindset that programming skills are improved through these activities (i.e., that everyone has the potential to become good at programming). In contrast to an entity mindset, individuals with an incremental mindset believe that ability is malleable and can be improved with effort. Prior…
Descriptors: Intervention, Cognitive Structures, Programming, Learning Activities
Peer reviewed Peer reviewed
Direct linkDirect link
Kokoç, Mehmet; Kara, Mehmet – Educational Technology & Society, 2021
The purposes of the two studies reported in this research are to adapt and validate the instrument of the Evaluation Framework for Learning Analytics (EFLA) for learners into the Turkish context, and to examine how metacognitive and behavioral factors predict learner performance. Study 1 was conducted with 83 online learners enrolled in a 16-week…
Descriptors: Learning Analytics, Electronic Learning, Measures (Individuals), Test Validity
Peer reviewed Peer reviewed
Direct linkDirect link
Cheng, Li-Chen; Chu, Hui-Chun – Interactive Learning Environments, 2019
Although computer-supported collaborative learning has been successfully applied in educational settings to improve group learning performance, most such systems still lack effective strategies for knowledge representation which could help reduce discussion time. In this study, concept mapping, already applied as a tool to help visualize and…
Descriptors: Cooperative Learning, Computer Uses in Education, Concept Mapping, Visual Aids
Peer reviewed Peer reviewed
Direct linkDirect link
Koulocheri, Eleni; Xenos, Michalis – International Journal of Web-Based Learning and Teaching Technologies, 2019
Social networks have undoubtedly penetrated into our daily life, in such a degree that educational life could not avoid this effect, as proven by the many education-oriented social networks that have emerged. The education-oriented social network environment named HOU2LEARN, used by the Hellenic Open University, is one of these networks, providing…
Descriptors: Foreign Countries, Social Networks, Open Universities, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Tomkins, Sabina; Ramesh, Arti; Getoor, Lise – International Educational Data Mining Society, 2016
With the success and proliferation of Massive Open Online Courses (MOOCs) for college curricula, there is demand for adapting this modern mode of education for high school courses. Online and open courses have the potential to fill a much needed gap in high school curricula, especially in fields such as computer science, where there is shortage of…
Descriptors: Prediction, Pretests Posttests, Electronic Learning, Student Behavior
Peer reviewed Peer reviewed
Direct linkDirect link
Pappas, Ilias O.; Giannakos, Michail N.; Jaccheri, Letizia; Sampson, Demetrios G. – ACM Transactions on Computing Education, 2017
This study uses complexity theory to understand the causal patterns of factors that stimulate students' intention to continue studies in computer science (CS). To this end, it identifies gains and barriers as essential factors in CS education, including motivation and learning performance, and proposes a conceptual model along with research…
Descriptors: Intention, Student Behavior, Computer Science Education, Barriers
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Alqahtani, Maha; Mohammad, Heba – Turkish Online Journal of Educational Technology - TOJET, 2015
Mobile applications are rapidly growing in importance and can be used for various purposes. They had been used widely in education. One of the educational purposes for which mobile applications can be used is learning the right way to read and pronounce the verses of the Holy Quran. There are many applications that translate the Quran into several…
Descriptors: Electronic Learning, Handheld Devices, Participant Satisfaction, Student Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
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
Previous Page | Next Page »
Pages: 1  |  2