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Elena Drugova; Irina Zhuravleva; Ulyana Zakharova; Adel Latipov – Journal of Computer Assisted Learning, 2024
Background: Driven by the ongoing need to provide high-quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to…
Descriptors: Learning Analytics, Instructional Design, Higher Education, Instructional Improvement
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)
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
Yan, Hongxin; Lin, Fuhua; Kinshuk – International Journal of Artificial Intelligence in Education, 2021
Online education is growing because of its benefits and advantages that students enjoy. Educational technologies (e.g., learning analytics, student modelling, and intelligent tutoring systems) bring great potential to online education. Many online courses, particularly in self-paced online learning (SPOL), face some inherent barriers such as…
Descriptors: Learning Analytics, Independent Study, Online Courses, Electronic Learning
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
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
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
Construction and Analysis of a Decision Tree-Based Predictive Model for Learning Intervention Advice
Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
Araka, Eric; Maina, Elizaphan; Gitonga, Rhoda; Oboko, Robert – Research and Practice in Technology Enhanced Learning, 2020
For the last one decade, research in self-regulated learning (SRL) and educational psychology has proliferated. Researchers and educators have focused on how to support leaners grow their SRL skills on both face-to-face and e-learning environments. In addition, recent studies and meta-analysis have greatly contributed to the domain knowledge on…
Descriptors: Educational Trends, Educational Research, Independent Study, Electronic Learning
Leung, Javier – Quarterly Review of Distance Education, 2022
This study aimed to visualize self-regulated learning (SRL) behaviors performed by users from an online teacher professional development platform called the EdHub Library using the pm4py algorithm in Python to parse event data during the first 30 days of the school year and the first 90 days of the COVID-19 pandemic in March 2020. Process mining…
Descriptors: Self Management, Learning Strategies, Electronic Learning, Faculty Development
Danielle S. McNamara; Tracy Arner; Elizabeth Reilley; Paul Alvarado; Chani Clark; Thomas Fikes; Annie Hale; Betheny Weigele – Grantee Submission, 2022
Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…
Descriptors: Electronic Learning, Educational Technology, Networks, Learning Analytics
Rwitajit Majumdar; Huiyong Li; Yuanyuan Yang; Hiroaki Ogata – Educational Technology & Society, 2024
Self-direction skill (SDS) is an essential 21st-century skill that can help learners be independent and organized in their quest for knowledge acquisition. While some studies considered learners from higher education levels as the target audience, providing opportunities to start the SDS practice by K12 learners is still rare. Further, practicing…
Descriptors: 21st Century Skills, Skill Development, Electronic Learning, Physical Activity Level
Charitopoulos, Angelos; Rangoussi, Maria; Koulouriotis, Dimitrios – International Journal of Artificial Intelligence in Education, 2020
The aim of this paper is to survey recent research publications that use Soft Computing methods to answer education-related problems based on the analysis of educational data 'mined' mainly from interactive/e-learning systems. Such systems are known to generate and store large volumes of data that can be exploited to assess the learner, the system…
Descriptors: Data Collection, Learning Analytics, Educational Research, Artificial Intelligence
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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