NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 39 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Fein, Benedikt; Graßl, Isabella; Beck, Florian; Fraser, Gordon – International Educational Data Mining Society, 2022
The recent trend of embedding source code for machine learning applications also enables new opportunities in learning analytics in programming education, but which code embedding approach is most suitable for learning analytics remains an open question. A common approach to embedding source code lies in extracting syntactic information from a…
Descriptors: Artificial Intelligence, Learning Analytics, Programming, Programming Languages
Peer reviewed Peer reviewed
Direct linkDirect link
Xu, Weiqi; Wu, Yajuan; Ouyang, Fan – International Journal of Educational Technology in Higher Education, 2023
Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students' discourses, behaviors, and socio-emotions, it is of critical importance to examine…
Descriptors: Cooperative Learning, Problem Solving, Computer Science Education, Programming
Peer reviewed Peer reviewed
Direct linkDirect link
Ben-Yaacov, Anat; Hershkovitz, Arnon – Journal of Educational Computing Research, 2023
Block programming has been suggested as a way of engaging young learners with the foundations of programming and computational thinking in a syntax-free manner. Indeed, syntax errors--which form one of two broad categories of errors in programming, the other one being logic errors--are omitted while block programming. However, this does not mean…
Descriptors: Programming, Computation, Thinking Skills, Error Patterns
Peer reviewed Peer reviewed
Direct linkDirect link
Amanpreet Kaur; Kuljit Kaur Chahal – Education and Information Technologies, 2024
Research so far has overlooked the contribution of students' noncognitive factors to their performance in introductory programming in the context of personalized learning support. This study uses learning analytics to design and implement a Dashboard to understand the contribution of introductory programming students' learning motivation,…
Descriptors: Learning Analytics, Introductory Courses, Programming, Computer Science Education
Peer reviewed Peer reviewed
Direct linkDirect link
Dan Sun; Fan Ouyang; Yan Li; Chengcong Zhu; Yang Zhou – Journal of Computer Assisted Learning, 2024
Background: With the development of computational literacy, there has been a surge in both research and practice application of text-based and block-based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major…
Descriptors: Computer Science Education, Programming, Computer Literacy, Comparative Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Shaheen, Muhammad – Interactive Learning Environments, 2023
Outcome-based education (OBE) is uniquely adapted by most of the educators across the world for objective processing, evaluation and assessment of computing programs and its students. However, the extraction of knowledge from OBE in common is a challenging task because of the scattered nature of the data obtained through Program Educational…
Descriptors: Undergraduate Students, Programming, Computer Science Education, Educational Objectives
Peer reviewed Peer reviewed
Direct linkDirect link
Meier, Heidi; Lepp, Marina – Journal of Educational Computing Research, 2023
Especially in large courses, feedback is often given only on the final results; less attention is paid to the programming process. Today, however, some programming environments, e.g., Thonny, log activities during programming and have the functionality of replaying the programming process. This information can be used to provide feedback, and this…
Descriptors: Programming, Introductory Courses, Computer Science Education, Teaching Methods
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
Albó, Laia; Barria-Pineda, Jordan; Brusilovsky, Peter; Hernández-Leo, Davinia – International Journal of Artificial Intelligence in Education, 2022
Over the last 10 years, learning analytics have provided educators with both dashboards and tools to understand student behaviors within specific technological environments. However, there is a lack of work to support educators in making data-informed design decisions when designing a blended course and planning appropriate learning activities. In…
Descriptors: Learning Analytics, Visual Aids, Design, Learning Activities
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Zhang, Jingjing; Huang, Yicheng; Gao, Ming – Journal of Learning Analytics, 2022
Network analytics has the potential to examine new behaviour patterns that are often hidden by the complexity of online interactions. One of the varied network analytics approaches and methods, the model of collective attention, takes an ecological system perspective to exploring the dynamic process of participation patterns in online and flexible…
Descriptors: Network Analysis, Video Technology, MOOCs, Attention Control
Peer reviewed Peer reviewed
Direct linkDirect link
Amaya, Edna Johanna Chaparro; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2023
Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3)…
Descriptors: Learning Analytics, Guidelines, Student Attitudes, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Hsu, Ting-Chia; Abelson, Hal; Patton, Evan; Chen, Shih-Chu; Chang, Hsuan-Ning – International Journal of Computer-Supported Collaborative Learning, 2021
In order to promote the practice of co-creation, a real-time collaboration (RTC) version of the popular block-based programming (BBP) learning environment, MIT App Inventor (MAI), was proposed and implemented. RTC overcomes challenges related to non-collocated group work, thus lowering barriers to cross-region and multi-user collaborative software…
Descriptors: Self Efficacy, Behavior Patterns, Student Behavior, Programming
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Efremov, Aleksandr; Ghosh, Ahana; Singla, Adish – International Educational Data Mining Society, 2020
Intelligent tutoring systems for programming education can support students by providing personalized feedback when a student is stuck in a coding task. We study the problem of designing a hint policy to provide a next-step hint to students from their current partial solution, e.g., which line of code should be edited next. The state of the art…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Computer Science Education, Artificial Intelligence
Previous Page | Next Page »
Pages: 1  |  2  |  3