NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 13 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Weijuan Li – European Journal of Education, 2025
In recent years, the integration of big data and learning analytics has emerged as a significant trend across educational systems worldwide. The implementation of such technologies within universities -- particularly in China -- holds considerable potential for transforming teaching and learning practices. By enabling personalised, data-driven…
Descriptors: Universities, Learning Analytics, Educational Practices, Foreign Countries
Peer reviewed Peer reviewed
Direct linkDirect link
Yuxiao Xie; Ziyi Xie; Siyu Chen; Lei Shen; Zhizhuang Duan – Education and Information Technologies, 2025
The National College English Test Band 4 (CET-4) is a key test to assess the English language ability of Chinese university students, and the success rate of the test is important to improve the quality of their English learning. Artificial intelligence technology can be used to predict and explore the factors influencing the success rate. This…
Descriptors: Language Tests, English (Second Language), Second Language Learning, Second Language Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Sahin, Muhittin; Ifenthaler, Dirk – International Association for Development of the Information Society, 2022
Within digitally-supported learning environments, learners need to observe themselves so that they can reflect on their strengths and weaknesses and take a step toward autonomous learning. Within the scope of this research, a technology and analytics enhanced assessment environment in which students can assess themselves was implemented and…
Descriptors: Foreign Countries, College Students, Behavior Patterns, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Shuang; Wang, Shuang; Du, Junlei; Pei, Yu; Shen, Xinyi – Journal of Computer Assisted Learning, 2022
Background: Failure to effectively organize and manage learning time is an important factor influencing online learners' performance. Investigation of time-investment patterns for online learning will provide educators with useful knowledge of how learners engage in and regulate their online learning and support them in tailoring online course…
Descriptors: Online Courses, Time Management, Time Factors (Learning), Learning Strategies
Peer reviewed Peer reviewed
Direct linkDirect link
Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Pardo, Abelardo; Fudge, Anthea; Gentili, Sheridan – Assessment & Evaluation in Higher Education, 2021
Research and development in learning analytics has established viable solutions for scaling personalised feedback to all students. However, questions remain regarding how such feedback is perceived, interpreted and acted upon by stakeholders. The present study reports on the analysis of focus group data from four courses to understand students'…
Descriptors: Student Attitudes, College Students, Emotional Response, Individualized Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Joseph-Richard, Paul; Uhomoibhi, James; Jaffrey, Andrew – International Journal of Information and Learning Technology, 2021
Purpose: The aims of this study are to examine affective responses of university students when viewing their own predictive learning analytics (PLA) dashboards, and to analyse how those responses are perceived to affect their self-regulated learning behaviour. Design/methodology/approach: A total of 42 Northern Irish students were shown their own…
Descriptors: Prediction, Learning Analytics, Student Behavior, Affective Behavior
Peer reviewed Peer reviewed
Direct linkDirect link
Jaeho Jeon – Computer Assisted Language Learning, 2024
Professionals within the field of language learning have predicted that chatbots would provide new opportunities for the teaching and learning of language. Despite the assumed benefits of utilizing chatbots in language classrooms, such as providing interactional chances or helping to create an anxiety-free atmosphere, little is known about…
Descriptors: Computer Assisted Instruction, Artificial Intelligence, Learning Analytics, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
Tempelaar, Dirk – Assessment & Evaluation in Higher Education, 2020
How can we best facilitate students most in need of learning support, entering a challenging quantitative methods module at the start of their bachelor programme? In this empirical study into blended learning and the role of assessment for and as learning, we investigate learning processes of students with different learning profiles.…
Descriptors: Learning Analytics, Formative Evaluation, Blended Learning, Undergraduate Students
Peer reviewed Peer reviewed
Direct linkDirect link
Zhang, Jia-Hua; Zou, Liu-cong; Miao, Jia-jia; Zhang, Ye-Xing; Hwang, Gwo-Jen; Zhu, Yue – Interactive Learning Environments, 2020
Extensive studies have been conducted to diagnose and predict students' academic performance by analyzing a large amount of data related to their learning behaviors in a blended learning environment. But there is a lack of research examining how individualized learning interventions could improve students' academic performance in such a learning…
Descriptors: Individualized Instruction, Academic Achievement, Interaction, Blended Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Shabbir, Shahzad; Ayub, Muhammad Adnan; Khan, Farman Ali; Davis, Jeffrey – Interactive Technology and Smart Education, 2021
Purpose: Short-term motivation encompasses specific, challenging and attainable goals that develop in the limited timespan. On the other hand, long-term motivation indicates a sort of continuing commitment that is required to complete assigned task. As short-term motivational problems span for a limited period of time, such as a session,…
Descriptors: Learning Motivation, Electronic Learning, Time Factors (Learning), Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Cheng, Ching-Hsue; Chen, Chung-Hsi – Computer Assisted Language Learning, 2022
Many scholars have highlighted the importance of motivation and anxiety in language learning. They have also indicated the advantages of integrating learning content into a mobile-assisted English learning system environment. Meanwhile, a few studies have explored the impacts of a mobile-assisted English learning system on the motivation and…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Student Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
P. Rose, Simon; Habgood, M. P. Jacob; Jay, Tim – Journal of Educational Computing Research, 2020
The recent shift in compulsory education from ICT-focused computing curricula to informatics, digital literacy and computer science, has resulted in children being taught computing using block-based programming tools such as Scratch, with teaching that is often limited by school resources and teacher expertise. Even without these limitations,…
Descriptors: Programming Languages, Computer Science Education, Game Based Learning, Educational Games
Peer reviewed Peer reviewed
Direct linkDirect link
Arslanbay, Goshnag; Ersanli, Ceylan Yangin – Journal on English Language Teaching, 2023
Data-Driven Learning (DDL) is a method for learning languages that involves analyzing language usage trends and finding patterns in language data, utilizing technology and statistics. One of the key benefits of DDL is that it allows students to focus on the most relevant and useful language data for their needs. Data-driven learning is an…
Descriptors: English (Second Language), English for Academic Purposes, Second Language Learning, Second Language Instruction