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Moubayed, Abdallah; Injadat, Mohammadnoor; Shami, Abdallah; Lutfiyya, Hanan – American Journal of Distance Education, 2020
E-learning platforms and processes face several challenges, among which is the idea of personalizing the e-learning experience and to keep students motivated and engaged. This work is part of a larger study that aims to tackle these two challenges using a variety of machine learning techniques. To that end, this paper proposes the use of k-means…
Descriptors: Learner Engagement, Electronic Learning, Individualized Instruction, Undergraduate Students
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Fischer, Gerhard; Lundin, Johan; Lindberg, J. Ola – International Journal of Information and Learning Technology, 2020
Purpose: The digitalization of society results in challenges and opportunities for learning and education. This paper describes exemplary transformations from current to future practices. It illustrates multi-dimensional aspects of learning which complement and transcend current frameworks of learning focused on schools. While digital technologies…
Descriptors: Information Technology, Educational Cooperation, Educational Practices, Transformative Learning
Craig, Scotty D.; Li, Siyuan; Prewitt, Deborah; Morgan, Laurie A.; Schroeder, Noah L. – Advanced Distributed Learning Initiative, 2020
The Science of Learning and Readiness (SoLaR) project seeks to demonstrate to Defense and other Government stakeholders the "art of the possible" for high-quality distributed learning and to create a practical guide for how to infuse such qualities into the broader Department of Defense (DoD) distributed learning ecosystem. This report…
Descriptors: Distance Education, Educational Technology, Learning Analytics, Data Collection
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Fingerson, Laura; Troutman, David R. – New Directions for Institutional Research, 2019
This chapter addresses how IR/IE both responds to and leads in our institutions and across higher education in measuring and improving student success. We introduce a new student success measurement framework in the context of internal and external facing needs, we define the importance of actionable information to inform decision-making, and we…
Descriptors: Institutional Research, Organizational Effectiveness, Higher Education, Academic Achievement
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Codish, David; Rabin, Eyal; Ravid, Gilad – Interactive Learning Environments, 2019
Process mining methodologies are designed to uncover underlying business processes, deviations from them, and in general, usage patterns. One of the key limitations of these methodologies is that they struggle in cases in which there is no structured process, or when a process can be performed in many ways. Learning Management Systems are a…
Descriptors: Integrated Learning Systems, Case Studies, Behavior Patterns, Learning Analytics
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Zilvinskis, John; Willis, James E., III – InSight: A Journal of Scholarly Teaching, 2019
The idea of learning analytics has become popularized within higher education, yet many educators are uncertain about what is entailed when implementing these technologies into practice. The following article serves as an overview to the field of learning analytics for faculty, educators for whom the expectations to use these technologies…
Descriptors: Learning Analytics, Higher Education, Definitions, Student Evaluation
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Eradze, Maka; Rodríguez-Triana, María Jesús; Laanpere, Mart – Education Sciences, 2019
Learning Design, as a field of research, provides practitioners with guidelines towards more effective teaching and learning. In parallel, observational methods (manual or automated) have been used in the classroom to reflect on and refine teaching and learning, often in combination with other data sources (such as surveys and interviews). Despite…
Descriptors: Literature Reviews, Instructional Design, Learning Analytics, Classroom Observation Techniques
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Volungeviciene, Airina; Duart, Josep Maria; Naujokaitiene, Justina; Tamoliune, Giedre; Rita Misiuliene, – Journal of Educators Online, 2019
The research aims at a specific analysis of how learning analytics as a metacognitive tool can be used as a method by teachers as reflective professionals and how it can help teachers learn to think and come down to decisions about learning design and curriculum, learning and teaching process, and its success. Not only does it build on previous…
Descriptors: Learning Analytics, Reflective Teaching, Metacognition, Decision Making
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Korkmaz, Ceren; Correia, Ana-Paula – Educational Media International, 2019
The purpose of this review is to investigate the trends in the body of research on machine learning in educational technologies, published between 2007 and 2017. The criteria for article selection were as follows: (1) study on machine learning in educational/learning technologies, (2) published between 2007-2017, (3) published in a peer-reviewed…
Descriptors: Electronic Learning, Educational Technology, Educational Trends, Automation
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Prinsloo, Paul – British Journal of Educational Technology, 2019
Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…
Descriptors: Learning Analytics, Data Collection, Data Analysis, Measurement
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Klein, Carrie; Lester, Jaime; Rangwala, Huzefa; Johri, Aditya – Journal of Computing in Higher Education, 2019
Learning analytics (LA) tools promise to improve student learning and retention. However, adoption and use of LA tools in higher education is often uneven. In this case study, part of a larger exploratory research project, we interviewed and observed 32 faculty and advisors at a public research university to understand the technological incentives…
Descriptors: Learning Analytics, Barriers, Incentives, Adoption (Ideas)
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Gupta, Shivangi; Sabitha, A. Sai – Education and Information Technologies, 2019
Aimed at a massive outreach and open access education, Massive Open Online Courses (MOOC) has evolved incredibly engaging millions of learners' over the years. These courses provide an opportunity for learning analytics with respect to the diversity in learning activity. Inspite of its growth, high dropout rate of the learners', it is examined to…
Descriptors: Retention (Psychology), Online Courses, Learner Engagement, Electronic Learning
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Bozkurt, Aras; Sharma, Ramesh C. – Asian Journal of Distance Education, 2022
Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…
Descriptors: Learning Analytics, Teaching Methods, Learning Processes, Prediction
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Zeng, Shuang; Zhang, Jingjing; Gao, Ming; Xu, Kate M.; Zhang, Jiang – Computer Assisted Language Learning, 2022
Learning analytics (LA) has the potential to generate new insights into the complexities of learning behaviours in language massive open online courses (LMOOCs). In LA, the collective attention model takes an ecological system view of the dynamic process of unequal participation patterns in online and flexible learning environments. In this study,…
Descriptors: Learning Analytics, MOOCs, Oral Language, English (Second Language)
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Barragán, Sandra; González, Leandro; Calderón, Gloria – Interchange: A Quarterly Review of Education, 2022
A combination of mathematical and statistical modelling techniques may be used to analyse student dropout behaviour. The aim of this study is to combine Survival Analysis and Analytic Hierarchy Process methodologies when identifying students at-risk of dropping out. This combination favours the institutional understanding of dropout as a dynamic…
Descriptors: Undergraduate Students, Gender Differences, Age Differences, Decision Making
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