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Pawan Kumar; Urvashi Tandon – Education and Information Technologies, 2024
This research aims to study the impact of Values enhanced technology adoption (VETA) in facilitating e-learning among academicians in Higher Education Institutions (HEIs) in North India. This research also validates the moderating role of digital technology by thoroughly understanding the impact of dimensions of VETA on behavioural intention. The…
Descriptors: Foreign Countries, Behavior Patterns, Electronic Learning, Higher Education
Hatice Yildiz Durak – Education and Information Technologies, 2025
Feedback is critical in providing personalized information about educational processes and supporting their performance in online collaborative learning environments. However, giving effective feedback and monitoring its effects, which is especially important in online environments, is a complex issue. Although providing feedback by analyzing…
Descriptors: Feedback (Response), Online Systems, Electronic Learning, Learning Analytics
Tlili, Ahmed; Wang, Huanhuan; Gao, Bojun; Shi, Yihong; Zhiying, Nian; Looi, Chee-Kit; Huang, Ronghuai – Interactive Learning Environments, 2023
Online and open learning has recently been made prevalent in many regions in order to mitigate educational inequality and to enhance students' learning experiences and outcomes. Previous studies showed that students perform differently in the learning process, where cultural differences matter. However, little is known about how cultural…
Descriptors: Diversity, Cultural Differences, Behavior Patterns, Electronic Learning
Jing Liu; Xuanyu Zhu; Chong Huang; Yujie Wang; Liyan Chang – Innovations in Education and Teaching International, 2024
With the widespread implementation of COVID-19 prevention and control measures during the pandemic, online classes have become a normal and indispensable part of college students' lives. Analysis of the factors affecting college students' behavioural intention towards online classes will help improve online class quality. This paper sets up a…
Descriptors: College Students, Student Motivation, Electronic Learning, Distance Education
Joe Hazzam; Stephen Wilkins; Bharati Singh; Blend Ibrahim – Innovations in Education and Teaching International, 2025
Social media educational tools represent an opportunity for higher education (HE) institutions to enhance postgraduate students' skills development. LinkedIn Learning can be used to complement classroom teaching and learning. However, the drivers and outcomes of this tool remain a gap in the literature. This study uses a cross-sectional research…
Descriptors: Foreign Countries, Graduate Students, Electronic Learning, Social Media
Kaliisa, Rogers; Dolonen, Jan Arild – Technology, Knowledge and Learning, 2023
Despite the potential of learning analytics (LA) to support teachers' everyday practice, its adoption has not been fully embraced due to the limited involvement of teachers as co-designers of LA systems and interventions. This is the focus of the study described in this paper. Following a design-based research (DBR) approach and guided by concepts…
Descriptors: College Faculty, Student Participation, Discourse Analysis, Behavior Patterns
Yang, Christopher C. Y.; Chen, Irene Y. L.; Ogata, Hiroaki – Educational Technology & Society, 2021
Precision education is now recognized as a new challenge of applying artificial intelligence, machine learning, and learning analytics to improve both learning performance and teaching quality. To promote precision education, digital learning platforms have been widely used to collect educational records of students' behavior, performance, and…
Descriptors: Learning Analytics, Individualized Instruction, Instructional Materials, Books
Zhao, Fuzheng; Hwang, Gwo-Jen; Yin, Chengjiu – Educational Technology & Society, 2021
Educational data mining and learning analytics have become a very important topic in the field of education technology. Many frameworks have been proposed for learning analytics which make it possible to identify learning behavior patterns or strategies. However, it is difficult to understand the reason why behavior patterns occur and why certain…
Descriptors: Behavior Patterns, Reading, Textbooks, Electronic Learning
Sachin Srivastava; Narender Singh Bhati – Journal of Information Technology Education: Research, 2024
Aim/Purpose: This research aims to examine the mobile learning (m-learning) intentions of students pursuing design courses at graduate and undergraduate levels in higher education institutions in a developing country like India. This study integrated the Technology Readiness Index (TRI 2.0) and the Unified Theory of Acceptance and Use of…
Descriptors: Electronic Learning, Handheld Devices, Telecommunications, Design
Milat, Iness Nedji; Seridi, Hassina; Moudjari, Abdelkader – International Journal of Distance Education Technologies, 2020
Recently, discovering learner behaviour has taken more attention in the field of e-learning. It aims to gain useful insights into the learning process of students despite the absence of direct interaction with teachers. In fact, the only available source of information in such environments is the log file that represents all possible interactions…
Descriptors: Student Behavior, Behavior Patterns, Electronic Learning, Learning Analytics
Getenet, Seyum; Tualaulelei, Eseta – Journal of Digital Learning in Teacher Education, 2023
The challenge addressed in this study is how the effectiveness of Padlet, Panopto video-embedded quizzes and Google Docs can be evaluated in terms of student engagement. Using a range of data sources, we discussed whether each technology influenced various dimensions of student engagement. The study found that certain technologies improved…
Descriptors: Educational Technology, Learner Engagement, Electronic Learning, Technology Uses in Education
Jieun Lim – Educational Technology & Society, 2024
This study compares the interaction patterns of a novice and an experienced instructor using Social Network Analysis (SNA) and content analysis and explores how students' interactions, degrees of satisfaction, and cognitive presence differ according to the different interaction patterns of the two instructors. Results showed some differences in…
Descriptors: Beginning Teachers, Experienced Teachers, Interaction, Student Satisfaction
Li, Yue; Jiang, Qiang; Xiong, Weiyan; Zhao, Wei – Education and Information Technologies, 2023
One of the recognized ways to enhance teaching and learning is having insights into the behavior patterns of students. Studies that explore behavior patterns in online self-directed learning (OSDL) are scant though. In addition, the focus is lacking on how high-achieving (HA) students' behavior patterns affect the academic performance of…
Descriptors: Student Behavior, Behavior Patterns, Electronic Learning, Online Courses
Zheng, Lanqin; Zhong, Lu; Niu, Jiayu – Assessment & Evaluation in Higher Education, 2022
Learning analytics has been widely used in the field of education. Most studies have adopted a learning analytics dashboard to present data on learning processes or learning outcomes. However, only presenting learning analytics results was not sufficient and lacked personalised feedback. In response to these gaps, this study proposed a learning…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Feedback (Response)
Kokoç, Mehmet; Akçapinar, Gökhan; Hasnine, Mohammad Nehal – Educational Technology & Society, 2021
This study analyzed students' online assignment submission behaviors from the perspectives of temporal learning analytics. This study aimed to model the time-dependent changes in the assignment submission behavior of university students by employing various machine learning methods. Precisely, clustering, Markov Chains, and association rule mining…
Descriptors: Electronic Learning, Assignments, Behavior Patterns, Learning Analytics