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Taihe Cao; Zhaoli Zhang; Wenli Chen; Jiangbo Shu – Interactive Learning Environments, 2023
Online learning with the characteristics of flexibility and autonomy has become a widespread and popular mode of higher education in which students need to engage in self-regulated learning (SRL) to achieve success. The purpose of this study is to utilize clickstream data to reveal the time management of SRL. This study adopts learning analytics…
Descriptors: Time Management, Self Management, Online Courses, Learning Analytics
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Wong, Billy Tak-ming; Li, Kam Cheong; Cheung, Simon K. S. – Journal of Computing in Higher Education, 2023
This paper presents an analysis of learning analytics practices which aimed to achieve personalised learning. It addresses the need for a systematic analysis of the increasing amount of practices of learning analytics which are targeted at personalised learning. The paper summarises and highlights the characteristics and trends in relevant…
Descriptors: Learning Analytics, Individualized Instruction, Context Effect, Stakeholders
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Brown, Alice; Lawrence, Jill; Basson, Marita; Axelsen, Megan; Redmond, Petrea; Turner, Joanna; Maloney, Suzanne; Galligan, Linda – Active Learning in Higher Education, 2023
Combining nudge theory with learning analytics, 'nudge analytics', is a relatively recent phenomenon in the educational context. Used, for example, to address such issues as concerns with student (dis)engagement, nudging students to take certain action or to change a behaviour towards active learning, can make a difference. However, knowing who to…
Descriptors: Online Courses, Learner Engagement, Learning Analytics, Intervention
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Bulut, Okan; Gorgun, Guher; Yildirim-Erbasli, Seyma N.; Wongvorachan, Tarid; Daniels, Lia M.; Gao, Yizhu; Lai, Ka Wing; Shin, Jinnie – British Journal of Educational Technology, 2023
As universities around the world have begun to use learning management systems (LMSs), more learning data have become available to gain deeper insights into students' learning processes and make data-driven decisions to improve student learning. With the availability of rich data extracted from the LMS, researchers have turned much of their…
Descriptors: Formative Evaluation, Learning Analytics, Models, Learning Management Systems
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Juan Antonio Martinez-Carrascal; Jorge Munoz-Gama; Teresa Sancho-Vinuesa – IEEE Transactions on Learning Technologies, 2024
Academic institutions dedicate a substantial effort to ensure the academic success of their students. At the course level, teachers recommend learning paths (RLPs) for students to guarantee the achievement of their learning outcomes. In terms of performance, these kinds of approaches are deemed more effective than others based uniquely on…
Descriptors: Online Courses, Mathematics Instruction, Undergraduate Students, Mathematics Achievement
Wood, Emily – ProQuest LLC, 2023
This study examined higher education instructors' lived experiences using learning analytics data to make sense of and improve their online course design. Mishra and Koehler's (2006) Technological, Pedagogical, and Content Knowledge (TPACK) served as the theoretical framework for this study, providing a lens for understanding how faculty apply…
Descriptors: Teaching Experience, Learning Analytics, Educational Improvement, Online Courses
Van Campenhout, Rachel – ProQuest LLC, 2022
Online courseware is an emerging educational technology that has the potential to reach students at scale. Designed with cognitive and learning science principles, courseware utilizes effective methods to maximize learning outcomes for students. Mindset (implicit theories of ability) and self-efficacy are two widely researched self-belief topics…
Descriptors: Student Attitudes, Beliefs, Online Courses, Courseware
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Lu, Chang; Cutumisu, Maria – International Journal of Educational Technology in Higher Education, 2022
In traditional school-based learning, attendance was regarded as a proxy for engagement and key indicator for performance. However, few studies have explored the effect of in-class attendance in technology-enhanced courses that are increasingly provided by secondary institutions. This study collected n = 367 undergraduate students' log files from…
Descriptors: Learner Engagement, Academic Achievement, Formative Evaluation, Attendance Patterns
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Lee, Hakeoung Hannah; Gargroetzi, Emma C. – Journal of Learning Analytics, 2023
Data-driven learning analytics (LA) exploits artificial intelligence, data-mining, and emerging technologies, rapidly expanding the collection and uses of learner data. Considerations of potential harm and ethical implications have not kept pace, raising concerns about ethical and privacy issues (Holstein & Doroudi, 2019; Prinsloo & Slade,…
Descriptors: Learning Analytics, Mentors, Ethics, Responsibility
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Murad, Dina Fitria; Murad, Silvia Ayunda; Irsan, Muhamad – Journal of Educators Online, 2023
This study discusses the use of an online learning recommendation system as a smart solution related to changing the face-to-face learning process to online. This study uses user-based collaborative filtering, item-based collaborative filtering, and hybrid collaborative filtering. This research was conducted in two stages using the KNN machine…
Descriptors: Online Courses, Grades (Scholastic), Prediction, Context Effect
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Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
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Mohammad Khalil; Paraskevi Topali; Alejandro Ortega-Arranz; Erkan Er; Gökhan Akçapinar; Gleb Belokrys – Technology, Knowledge and Learning, 2024
The use of videos in teaching has gained impetus in recent years, especially after the increased attention towards remote learning. Understanding students' video-related behaviour through learning (and video) analytics can offer instructors significant potential to intervene and enhance course designs. Previous studies explored students' video…
Descriptors: Foreign Countries, MOOCs, Distance Education, Online Courses
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Mustafa Tepgec; Joana Heil; Dirk Ifenthaler – Assessment & Evaluation in Higher Education, 2025
Despite the widespread implementation of learning analytics (LA)-based feedback systems, there exists a gap in empirical investigations regarding their influence on learning outcomes. Moreover, existing research primarily focuses on individual differences, such as self-regulation and motivation, overlooking the potential of feedback literacy (FL).…
Descriptors: Feedback (Response), Learning Analytics, Outcomes of Education, Transfer of Training
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Veluvali, Parimala; Surisetti, Jayesh – Higher Education for the Future, 2022
Online education helped resume learning that had come to a momentary and uncertain pause with the onset of COVID-19 pandemic across the globe. Since then, learning in many educational institutions continued through synchronous and asynchronous modes, with teaching being undertaken remotely on digital platforms. In this large-scale migration…
Descriptors: Integrated Learning Systems, Learner Engagement, Higher Education, Literature Reviews
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Yawen Yu; Yang Tao; Gaowei Chen; Can Sun – Journal of Computer Assisted Learning, 2024
Background: Deep discussions play an important role in students' online learning. However, researchers have largely focused on engaging students in deep discussions in online asynchronous forums. Few studies have investigated how to promote deep discussion via mobile instant messaging (MIM). Objectives: In this study, we applied learning…
Descriptors: Learning Analytics, College Students, Epistemology, Computer Mediated Communication
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