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Guajardo Leal, Brenda Edith; Valenzuela González, Jaime Ricardo – Online Learning, 2019
MOOCs are characterized as being courses to which a large number of students enroll, but only a small fraction completes them. An understanding of students' engagement construct is essential to minimize dropout rates. This research is of a quantitative design and exploratory in nature and investigates the interaction between contextual factors…
Descriptors: Learner Engagement, Predictor Variables, Online Courses, Energy Conservation
Ramli, Izzat S. Mohd; Maat, Siti M.; Khalid, Fariza – Pegem Journal of Education and Instruction, 2022
The boom of the 4.0 industrial revolution and the Covid-19 pandemic have changed the teaching and learning process, where digital learning environments have become increasingly necessary and convenient. The application of game-based learning (GBL) provides many benefits, such as helping to improve the quality of the mathematics teaching and…
Descriptors: Computer Games, Educational Games, Game Based Learning, Learning Analytics
Nguyen, Quan; Rienties, Bart; Whitelock, Denise – Journal of Learning Analytics, 2020
The use of analytical methods from learning analytics (LA) research combined with visualizations of learning activities using learning design (LD) tools and frameworks has provided important insight into how instructors design for learning. Nonetheless, there are many subtle nuances in instructors' design decisions that might not easily be…
Descriptors: Instructional Design, Online Courses, Distance Education, Electronic Learning
Walsh, Chris; Mital, Abhinav; Ratcliff, Michael; Yap, Ana; Jamaledine, Zeina – Australasian Journal of Educational Technology, 2020
Online education often struggles to maintain a consistent, high quality academic experience. High attrition rates and low student satisfaction continue to challenge higher education providers. We present an innovative public-private partnership that delivers a resources-sufficient model of fully online postgraduate education with high levels of…
Descriptors: Partnerships in Education, Electronic Learning, Distance Education, Academic Support Services
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals
Victor Manuel Corza-Vargas; Roberto Martinez-Maldonado; Boris Escalante-Ramirez; Jimena Olveres – Journal of Learning Analytics, 2024
While teachers often monitor and adjust their learning design based on students' emotional states in physical classrooms, synchronous online environments often limit their ability to perceive the emotional climate of the class. Drawing from the concept of social translucence, it is suggested that making students' emotional states…
Descriptors: Foreign Countries, Undergraduate Students, Privacy, Cultural Awareness
Guzsvinecz, Tibor; Szucs, Judit – Education Sciences, 2021
Face-to-face education has changed to blended or distance teaching due to the COVID-19 pandemic. Since education took a digital format, it can be investigated when course materials are accessed relative to online exams: are they opened before exams or during them? Therefore, four subjects were chosen for investigation at the University of…
Descriptors: Learning Analytics, Instructional Materials, Computer Assisted Testing, Electronic Learning
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
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
Jayashanka, Rangana; Hettiarachchi, E.; Hewagamage, K. P. – Electronic Journal of e-Learning, 2022
During the COVID-19 pandemic period, all the Sri Lankan universities delivered lectures in fully online mode using Virtual Learning Environments. In fully online mode, students cannot track their performance level, their progress in the course, and their performances compared to the rest of the class. This paper presents research work conducted at…
Descriptors: Foreign Countries, Technology Uses in Education, Learning Analytics, Electronic Learning
Devlin, Maura; Bushey, Heather – Change: The Magazine of Higher Learning, 2019
With national graduation rates that range from 32% among open enrollment institutions to 66% among private not-for-profits, higher education institutions have a moral imperative to improve the success of their students. Interventions to support today's students must consider the student holistically, be just-in-time, and come from a…
Descriptors: Data Use, Academic Achievement, Outcomes of Education, Holistic Approach
Herodotou, Christothea; Hlosta, Martin; Boroowa, Avinash; Rienties, Bart; Zdrahal, Zdenek; Mangafa, Chrysoula – British Journal of Educational Technology, 2019
This study presents an advanced predictive learning analytics system, OU Analyse (OUA), and evidence from its evaluation with online teachers at a distance learning university. OUA is a predictive system that uses machine learning methods for the early identification of students at risk of not submitting (or failing) their next assignment.…
Descriptors: Learning Analytics, Teacher Empowerment, Distance Education, College Faculty
Jill Lawrence; Alice Brown; Petrea Redmond; Marita Basson – Student Success, 2019
Universities increasingly implement online delivery to strengthen students' access and flexibility. However, they often do so with limited understanding of the impact of online pedagogy on student engagement. To explore these issues, a research project was conducted investigating the use of course-specific learning analytics to 'nudge' students…
Descriptors: Learner Engagement, Learning Analytics, Data Use, Electronic Learning
Šaric-Grgic, Ines; Grubišic, Ani; Šeric, Ljiljana; Robinson, Timothy J. – International Journal of Distance Education Technologies, 2020
The idea of clustering students according to their online learning behavior has the potential of providing more adaptive scaffolding by the intelligent tutoring system itself or by a human teacher. With the aim of identifying student groups who would benefit from the same intervention in AC-ware Tutor, this research examined online learning…
Descriptors: Learning Analytics, Intelligent Tutoring Systems, Grouping (Instructional Purposes), Undergraduate Students
Hernández-Lara, Ana Beatriz; Perera-Lluna, Alexandre; Serradell-López, Enric – Education & Training, 2021
Purpose: With the growth of digital education, students increasingly interact in a variety of ways. The potential effects of these interactions on their learning process are not fully understood and the outcomes may depend on the tool used. This study explores the communication patterns and learning effectiveness developed by students using two…
Descriptors: Game Based Learning, Learning Analytics, Computer Mediated Communication, Asynchronous Communication

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