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Maloney, Suzanne; Axelsen, Megan; Galligan, Linda; Turner, Joanna; Redmond, Petrea; Brown, Alice; Basson, Marita; Lawrence, Jill – Online Learning, 2022
Driven by the increased availability of Learning Management System data, this study explored its value and sought understanding of student behaviour through the information contained in activity level log data. Specifically, this study examined analytics data to understand students' engagement with online videos. Learning analytics data from the…
Descriptors: Learning Analytics, Video Technology, Learning Management Systems, Comparative Analysis
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Chavan, Pankaj; Mitra, Ritayan – Journal of Learning Analytics, 2022
The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…
Descriptors: Learning Analytics, Video Technology, Lecture Method, Online Courses
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Jongile, Sonwabo – International Journal on E-Learning, 2022
The identification of predictor variables for students at-risk of dropping out of university has received increased attention in higher education settings internationally concerning the context of origin in which they are developed and the different academic context in which they are introduced, often lacking schema-theoretic perspectives to offer…
Descriptors: Predictor Variables, At Risk Students, Potential Dropouts, College Students
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Cukurova, Mutlu; Khan-Galaria, Madiha; Millán, Eva; Luckin, Rose – Journal of Learning Analytics, 2022
One-to-one online tutoring provided by human tutors can improve students' learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach to monitoring online one-to-one tutoring quality. The approach analyzes teacher behaviours and classifies tutoring sessions…
Descriptors: Learning Analytics, Tutoring, Educational Quality, Behavior Patterns
Mohammed Alzaid – ProQuest LLC, 2022
Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…
Descriptors: Learning Analytics, Self Evaluation (Individuals), Programming, Problem Solving
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Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gasevic, Dragan – Journal of Learning Analytics, 2021
The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust in data and difficulties in scaling LA. This paper presents a study that investigated areas of distrust and threats to trustworthy LA through a series of consultations with teaching staff and…
Descriptors: Learning Analytics, Program Implementation, Trust (Psychology), Higher Education
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Maslo, Irina – Journal of Educational Sciences, 2021
In the context of the smart specialization of national economies and the creation of smart societies in the digital age, general, vocational, adult, and higher education reforms have a decisive horizontal effect on the transition to smart education. A smart pedagogical approach that has evolved in recent years is frequently seen as merely focused…
Descriptors: Educational Philosophy, Educational Change, Educational Technology, Learning Analytics
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Kärner, Tobias; Warwas, Julia; Schumann, Stephan – Technology, Knowledge and Learning, 2021
Addressing heterogeneity in the classroom by adapting instruction to learners' needs challenges teachers in their daily work. To provide adaptive instruction in the most flexible way, teachers face the problem of assessing students' individual characteristics (learning prerequisites and learning needs) and situational states (learning experiences…
Descriptors: Learning Analytics, Heterogeneous Grouping, Computer Uses in Education, Client Server Architecture
Saqr, Mohammed; Peeters, Ward; Viberg, Olga – Research and Practice in Technology Enhanced Learning, 2021
Writing in an academic context often requires students in higher education to acquire a new set of skills while familiarising themselves with the goals, objectives and requirements of the new learning environment. Students' ability to continuously self-regulate their writing process, therefore, is seen as a determining factor in their learning…
Descriptors: Academic Language, Self Management, Learning Strategies, Student Behavior
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Orji, Fidelia A.; Vassileva, Julita; Greer, Jim – International Journal of Artificial Intelligence in Education, 2021
Persuasive Technologies (PT) are computational methods, strategies, and design techniques, grounded in social psychology to change user attitudes/behaviours. PTs have been applied in diverse areas, such as eCommerce, health, workplace, vehicles, urban and ambient environments. A kind of PT that has become popular in eLearning is known under the…
Descriptors: Intervention, Program Effectiveness, Learner Engagement, Class Size
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Ladino Nocua, Andrea Catalina; Cruz Gonzalez, Joan Paola; Castiblanco Jimenez, Ivonne Angelica; Gomez Acevedo, Juan Sebastian; Marcolin, Federica; Vezzetti, Enrico – Education Sciences, 2021
Student engagement allows educational institutions to make better decisions regarding teaching methodologies, methods for evaluating the quality of education, and ways to provide timely feedback. Due to the COVID-19 pandemic, identifying cognitive student engagement in distance learning has been a challenge in higher education institutions. In…
Descriptors: Learner Engagement, Cognitive Processes, Metabolism, Physiology
Liang, Changhao; Majumdar, Rwitajit; Ogata, Hiroaki – Research and Practice in Technology Enhanced Learning, 2021
Collaborative learning in the form of group work is becoming increasingly significant in education since interpersonal skills count in modern society. However, teachers often get overwhelmed by the logistics involved in conducting any group work. Valid support for executing and managing such activities in a timely and informed manner becomes…
Descriptors: Automation, Cooperative Learning, Grouping (Instructional Purposes), Computer Assisted Instruction
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Sridharan, Shwetha; Saravanan, Deepti; Srinivasan, Akshaya Kesarimangalam; Murugan, Brindha – Education and Information Technologies, 2021
There exist numerous resources online to gain the desired level of knowledge on any topic. However, this complicates the process of selecting the most appropriate resources. Every learner differs in terms of their learning speed, proficiency, and preferred mode of learning. This paper develops an adaptive learning management system to tackle this…
Descriptors: Integrated Learning Systems, Computer Assisted Instruction, Individualized Instruction, Learning Analytics
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Rajabalee, Yousra Banoor; Santally, Mohammad Issack – Education and Information Technologies, 2021
There has been debates related to online and blended learning from a perspective of learner experiences in terms of student satisfaction, engagement and performances. In this paper, we analyze student feedback and report the findings of a study of the relationships between student satisfaction and their engagement in an online course with their…
Descriptors: Student Satisfaction, Electronic Learning, College Freshmen, Engineering Education
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Gurcan, Fatih; Ozyurt, Ozcan; Cagiltay, Nergiz Ercil – International Review of Research in Open and Distributed Learning, 2021
E-learning studies are becoming very important today as they provide alternatives and support to all types of teaching and learning programs. The effect of the COVID-19 pandemic on educational systems has further increased the significance of e-learning. Accordingly, gaining a full understanding of the general topics and trends in e-learning…
Descriptors: Educational Trends, Electronic Learning, Models, Learning Analytics
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