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Prihar, Ethan; Vanacore, Kirk; Sales, Adam; Heffernan, Neil – International Educational Data Mining Society, 2023
There is a growing need to empirically evaluate the quality of online instructional interventions at scale. In response, some online learning platforms have begun to implement rapid A/B testing of instructional interventions. In these scenarios, students participate in series of randomized experiments that evaluate problem-level interventions in…
Descriptors: Electronic Learning, Intervention, Instructional Effectiveness, Data Collection
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Bimal Aklesh Kumar; Sailesh Saras Chand; Munil Shiva Goundar – International Journal of Information and Learning Technology, 2024
Purpose: Mobile learning has seen tremendous growth over the years. Like any other software application, usability is one of the key concerns in its successful implementation. There is a lack of study that provides a comprehensive overview of usability testing of mobile learning applications. Motivated by this a mapping study is conducted.…
Descriptors: Usability, Electronic Learning, Computer Software, Computer Oriented Programs
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Xia, Xiaona; Qi, Wanxue – Education and Information Technologies, 2023
Interactive learning is a two-way learning method of learners independently by using computer and network technology. In the interactive relationships, interactive learning plays a role for learners to achieve the learning purpose, interactive learning has become an important effect of online learning, but it also has many problems that need to be…
Descriptors: Foreign Countries, Identification, Interaction, Learning Processes
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Nayak, Padmalaya; Vaheed, Sk.; Gupta, Surbhi; Mohan, Neeraj – Education and Information Technologies, 2023
Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…
Descriptors: Predictor Variables, Academic Achievement, Data Collection, Information Retrieval
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David P. Reid; Timothy D. Drysdale – IEEE Transactions on Learning Technologies, 2024
The designs of many student-facing learning analytics (SFLA) dashboards are insufficiently informed by educational research and lack rigorous evaluation in authentic learning contexts, including during remote laboratory practical work. In this article, we present and evaluate an SFLA dashboard designed using the principles of formative assessment…
Descriptors: Learning Analytics, Laboratory Experiments, Electronic Learning, Feedback (Response)
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Saba Sareminia; Vida Mohammadi Dehcheshmeh – International Journal of Information and Learning Technology, 2024
Purpose: Although E-learning has been in use for over two decades, running parallel to traditional learning systems, it has gained increased attention due to its vital role in universities in the wake of the COVID-19 pandemic. The primary challenge within E-learning pertains to the maintenance of sustainable effectiveness and the assurance of…
Descriptors: Educational Improvement, Electronic Learning, Personality Traits, Models
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Yavuz Akbulut; Abdullah Saykili; Aylin Öztürk; Aras Bozkurt – International Review of Research in Open and Distributed Learning, 2023
Online surveys are widely used in social science research as well as in empirical studies of open, online, and distance education. However, students' responses are likely to be at odds with their actual behavior. In this context, we examined the discrepancies between self-reported use and actual use (i.e., learning analytics data) among 20,646…
Descriptors: Measurement Techniques, Electronic Learning, Distance Education, Open Education
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Xing, Wanli; Du, Dongping; Bakhshi, Ali; Chiu, Kuo-Chun; Du, Hanxiang – IEEE Transactions on Learning Technologies, 2021
Predictive modeling in online education is a popular topic in learning analytics research and practice. This study proposes a novel predictive modeling method to improve model transferability over time within the same course and across different courses. The research gaps addressed are limited evidence showing whether a predictive model built on…
Descriptors: Electronic Learning, Bayesian Statistics, Prediction, Models
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Mahsood Shah; Fion Choon Boey Lim – Perspectives: Policy and Practice in Higher Education, 2024
This paper is a retrospective look at the last ten years of development in online third-party arrangements within the Australian higher education sector. A total of 42 higher education providers are reviewed. The analysis initially focuses on the state of online third-party arrangements in Australian higher education. It then investigates the…
Descriptors: Foreign Countries, Higher Education, Partnerships in Education, Electronic Learning
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Korkmaz, Elif; Morali, Hasibe Sevgi – International Electronic Journal of Mathematics Education, 2022
Augmented reality (AR) helps three dimensional, virtual objects to be viewed, interactively, in a real-world setting. AR technology is used in many fields such as medicine, advertisement, military, industry, and increasingly in education. AR has an importantrole in concretizing educational platforms and achieving permanentlearning. This study aims…
Descriptors: Meta Analysis, Computer Simulation, Electronic Learning, Mathematics Education
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Portnoff, Lucy; Gustafson, Erin; Rollinson, Joseph; Bicknell, Klinton – International Educational Data Mining Society, 2021
Students using self-directed learning platforms, such as Duolingo, cannot be adequately assessed relying solely on responses to standard learning exercises due to a lack of control over learners' choices in how to utilize the platform: for example, how learners choose to sequence their studying and how much they choose to revisit old material. To…
Descriptors: Second Language Learning, Language Tests, Educational Technology, Electronic Learning
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da Silva, Lidia M.; Dias, Lucas P. S.; Barbosa, Jorge L. V.; Rigo, Sandro J.; dos Anjos, Julio C. S.; Geyer, Claudio F. R.; Leithardt, Valderi R. Q. – Informatics in Education, 2022
Advances in information and communication technologies have contributed to the increasing use of virtual learning environments as support tools in teaching and learning processes. Virtual platforms generate a large volume of educational data, and the analysis of this data allows useful information discoveries to improve learning and assist…
Descriptors: Learning Analytics, Cooperative Learning, Distance Education, Electronic Learning
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Sales, Adam C.; Prihar, Ethan B.; Gagnon-Bartsch, Johann A.; Heffernan, Neil T. – Journal of Educational Data Mining, 2023
Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without confounding bias and exact statistical inference even in small samples. However, often experimental samples and/or treatment effects are small, A/B tests are underpowered,…
Descriptors: Data Use, Research Methodology, Randomized Controlled Trials, Educational Technology
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Sahin, Muhittin; Ulucan, Aydin; Yurdugül, Halil – Education and Information Technologies, 2021
E-learning environments can store huge amounts of data on the interaction of learners with the content, assessment and discussion. Yet, after the identification of meaningful patterns or learning behaviour in the data, it is necessary to use these patterns to improve learning environments. It is notable that designs to benefit from these patterns…
Descriptors: Electronic Learning, Data Collection, Decision Making, Evaluation Criteria
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Kathryn Lanouette; Sarah Van Wart; Tapan S. Parikh – Journal of Science Education and Technology, 2025
Over the last two decades, there has been an increasing focus on spatial technologies in teaching and learning, revealing the potential to support new forms of youth sensemaking across varied settings and modalities. Recent scholarship has shown the possibilities of participatory digital mapping technologies, enabling young people to collect data…
Descriptors: Science Education, Grade 5, Concept Mapping, Electronic Learning
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