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Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Fudge, Anthea; Pardo, Abelardo; Gentili, Sheridan – Australasian Journal of Educational Technology, 2020
Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students' sense-making of…
Descriptors: Individualized Instruction, Learning Analytics, Data Collection, Student Attitudes
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Oz, Omer; Ozdamar, Nilgun – Asian Journal of Distance Education, 2020
The main purpose of this study is to explore the effects of Industry 4.0 on resources (specialization, rationalization, preparatory work, and capital-intensive techniques) in the field of open and distance learning. Industry 4.0 is a period in which a great and rapid change is experienced, has a wide and deep impact that can affect business lines…
Descriptors: College Faculty, Expertise, Teacher Attitudes, Open Education
Sungjin Nam – ProQuest LLC, 2020
This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…
Descriptors: Vocabulary Development, Intelligent Tutoring Systems, Student Evaluation, Learning Analytics
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Olive, David Monllao; Huynh, Du Q.; Reynolds, Mark; Dougiamas, Martin; Wiese, Damyon – IEEE Transactions on Learning Technologies, 2019
A significant amount of research effort has been put into finding variables that can identify students at risk based on activity records available in learning management systems (LMS). These variables often depend on the context, for example, the course structure, how the activities are assessed or whether the course is entirely online or a…
Descriptors: Prediction, Identification, At Risk Students, Online Courses
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Rehrey, George; Shepard, Linda; Hostetter, Carol; Reynolds, Amberly; Groth, Dennis – Journal of Learning Analytics, 2019
To successfully implement Learning Analytics (LA) systems within higher education, we need to engage administrators, faculty, and staff alike. This paper is by and primarily for practitioners. We suggest implementation strategies that consider the human factor in adopting new technologies by analyzing the viability of our Learning Analytics…
Descriptors: Learning Analytics, Change Agents, School Culture, Technology Integration
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Tate, Tamara P.; Warschauer, Mark – Technology, Knowledge and Learning, 2019
The quality of students' writing skills continues to concern educators. Because writing is essential to success in both college and career, poor writing can have lifelong consequences. Writing is now primarily done digitally, but students receive limited explicit instruction in digital writing. This lack of instruction means that students fail to…
Descriptors: Writing Tests, Computer Assisted Testing, Writing Skills, Writing Processes
Wang, Yan; Ostrow, Korinn; Beck, Joseph; Heffernan, Neil – Grantee Submission, 2016
The focus of the learning analytics community bridges the gap between controlled educational research and data mining. Online learning platforms can be used to conduct randomized controlled trials to assist in the development of interventions that increase learning gains; datasets from such research can act as a treasure trove for inquisitive data…
Descriptors: Learning Analytics, Educational Research, Randomized Controlled Trials, Information Retrieval
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Blumenstein, Marion – Journal of Learning Analytics, 2020
The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD). Despite the growing potential of LA in higher education (HE), the benefits are not yet convincing to the practitioner, in particular aspects of…
Descriptors: Learning Analytics, Instructional Design, Effect Size, Higher Education
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Matcha, Wannisa; Gasevic, Dragan; Uzir, Nora'ayu Ahmad; Jovanovic, Jelena; Pardo, Abelardo; Lim, Lisa; Maldonado-Mahauad, Jorge; Gentili, Sheridan; Perez-Sanagustin, Mar; Tsai, Yi-Shan – Journal of Learning Analytics, 2020
Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning…
Descriptors: Learning Analytics, Learning Strategies, Instructional Design, Delivery Systems
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Herodotou, Christothea; Naydenova, Galina; Boroowa, Avi; Gilmour, Alison; Rienties, Bart – Journal of Learning Analytics, 2020
Despite the potential of Predictive Learning Analytics (PLAs) to identify students at risk of failing their studies, research demonstrating effective application of PLAs to higher education is relatively limited. The aims of this study are: (1) to identify whether and how PLAs can inform the design of motivational interventions; and (2) to capture…
Descriptors: Learning Analytics, Predictive Measurement, Student Motivation, Intervention
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Peffer, Melanie E.; Ramezani, Niloofar; Quigley, David; Royse, Emily; Bruce, Chloe – CBE - Life Sciences Education, 2020
Epistemological beliefs about science (EBAS) or beliefs about the nature of science knowledge, and how that knowledge is generated during inquiry, are an essential yet difficult to assess component of science literacy. Leveraging learning analytics to capture and analyze student practices in simulated or game-based authentic science activities is…
Descriptors: Learning Analytics, Beliefs, Scientific Principles, Inquiry
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Baker, Ryan S.; Berning, Andrew W.; Gowda, Sujith M.; Zhang, Shizhu; Hawn, Aaron – Journal of Education for Students Placed at Risk, 2020
Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students' discipline, attendance, course-taking,…
Descriptors: At Risk Students, High School Students, Dropout Prevention, Student Diversity
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Calvo-Morata, Antonio; Rotaru, Dan Cristian; Alonso-Fernandez, Cristina; Freire-Moran, Manuel; Martinez-Ortiz, Ivan; Fernandez-Manjon, Baltasar – IEEE Transactions on Learning Technologies, 2020
Bullying is a serious social problem at schools, very prevalent independently of culture and country, and particularly acute for teenagers. With the irruption of always-on communications technology, the problem, now termed cyberbullying, is no longer restricted to school premises and hours. There are many different approaches to address…
Descriptors: Educational Games, Bullying, Computer Mediated Communication, Learning Analytics
Miller, Gary E., Ed.; Ives, Kathleen S., Ed. – Stylus Publishing LLC, 2020
eLearning has entered the mainstream of higher education as an agent of strategic change. This transformation requires eLearning leaders to develop the skills to innovate successfully at a time of heightened competition and rapid technological change. In this environment eLearning leaders must act within their institutions as much more than…
Descriptors: Electronic Learning, Higher Education, Change Strategies, Leadership Effectiveness
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Isaias, Pedro, Ed.; Sampson, Demetrios G., Ed.; Ifenthaler, Dirk, Ed. – Cognition and Exploratory Learning in the Digital Age, 2020
This book explores a variety of facets of online learning environments to understand how learning occurs and succeeds in digital contexts and what teaching strategies and technologies are most suited to this format. Business, health, government and education are some of the core sectors of society which have been experiencing deep transformations…
Descriptors: Electronic Learning, Higher Education, College Instruction, Teaching Methods
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