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Nkomo, Larian M.; Nat, Muesser – TechTrends: Linking Research and Practice to Improve Learning, 2021
With various digital technologies increasingly integrated into higher education, understanding how students engage with such technologies has become vital. There are different ways to measure student engagement; however, self-reported measures such as questionnaires are predominantly used to understand student engagement. In contrast, this study…
Descriptors: Learner Engagement, Blended Learning, Educational Environment, Data Collection
Region 9 Comprehensive Center, 2021
The COVID-19 pandemic has created an unprecedented challenge for state, district, and school leaders across the country. Whether states and districts mandate or choose an in-person or remote model or a hybrid model, which includes some aspect of virtual learning, ensuring that vulnerable students and teachers have a remote learning option has…
Descriptors: Distance Education, Blended Learning, Educational Quality, Learner Engagement
Krasodomska, Joanna; Godawska, Justyna – Accounting Education, 2021
In this study, we examined the relationship between university students' engagement in a blended learning course and their performance. We also explored the roles which gender and nationality may play in the learning process. Our sample consisted of 335 students of International Accounting course. We used 23,796 student access computer logs as a…
Descriptors: Accounting, Electronic Learning, Correlation, Blended Learning
Gelan, Anouk; Fastré, Greet; Verjans, Martine; Martin, Niels; Janssenswillen, Gert; Creemers, Mathijs; Lieben, Jonas; Depaire, Benoît; Thomas, Michael – Computer Assisted Language Learning, 2018
Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date,…
Descriptors: Data Collection, Data Analysis, Computer Assisted Instruction, Second Language Instruction
Wan, Han; Liu, Kangxu; Yu, Qiaoye; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2019
Most educational institutions adopted the hybrid teaching mode through learning management systems. The logging data/clickstream could describe learners' online behavior. Many researchers have used them to predict students' performance, which has led to a diverse set of findings, but how to use insights from captured data to enhance learning…
Descriptors: Educational Practices, Learner Engagement, Identification, Study Habits
Willans, Fiona; Fonolahi, Aluwesi; Buadromo, Ralph; Bryce, Tilisi; Prasad, Rajendra; Kumari, Sandhya – Journal of University Teaching and Learning Practice, 2019
This paper reports on the evaluation of an ambitious attempt to embed academic literacy support within a core content course for first-year students at the University of the South Pacific. The course is offered in both blended and online modes, catering for on-campus and off-campus students, respectively, using Moodle as the virtual learning…
Descriptors: Learner Engagement, Academic Language, Instructional Design, Management Systems
Baker, Ariana – Journal of Library & Information Services In Distance Learning, 2016
Distance learning programs across the country continue to grow and evolve. In order to support these programs, librarians are often expected to convert face-to-face classes and reference sessions to the online environment. Due to the necessity of explaining information literacy concepts and demonstrating the access and use of library resources,…
Descriptors: Active Learning, Interactive Video, Distance Education, Blended Learning
Shahnaz, Sherina Mohamed Fauzi; Hussain, Raja Maznah Raja – Malaysian Journal of Learning and Instruction, 2016
Purpose: This paper proposes a framework of instructional strategies that would facilitate active and reflective learning processes in the flipped classroom It is aimed at allowing one's maximum potential to be reached regardless of any individual learning style. As tertiary classrooms increasingly needs to be as active and social as possible, the…
Descriptors: Instructional Design, Active Learning, Reflection, Learning Processes
Pardo, Abelardo; Han, Feifei; Ellis, Robert A. – IEEE Transactions on Learning Technologies, 2017
Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…
Descriptors: Student Centered Learning, Learning Theories, College Students, Academic Achievement
Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan – IEEE Transactions on Learning Technologies, 2017
Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students…
Descriptors: Student Behavior, Integrated Learning Systems, Personality, Educational Research
Montgomery, Amanda P.; Hayward, Denyse V.; Dunn, William; Carbonaro, Mike; Amrhein, Carl G. – Australasian Journal of Educational Technology, 2015
The purpose of this ongoing, three-year action research study is to explore the digital challenges of student engagement in higher education within the experimental platform of blended learning. Research questions examine the role of digital innovation in supporting diverse learners, as well as building meaningful connections with technology for…
Descriptors: Blended Learning, Learner Engagement, Online Courses, Class Size
McDonald, Paige L.; Lyons, Laurie B.; Straker, Howard O.; Barnett, Jacqueline S.; Schlumpf, Karen S.; Cotton, Linda; Corcoran, Mary A. – Online Learning, 2014
For disciplines heavily reliant upon traditional classroom teaching, such as medicine and health sciences, incorporating new learning models may pose challenges for students and faculty. In an effort to innovate curricula, better align courses to required student learning outcomes, and address the call to redesign health professions education,…
Descriptors: Health Sciences, Medical Education, Blended Learning, Faculty Development
Simonson, Michael, Ed.; Seepersaud, Deborah, Ed. – Association for Educational Communications and Technology, 2019
For the forty-second time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Las Vegas, Nevada. The Proceedings of AECT's Convention are published in two volumes. Volume 1 contains 37 papers dealing…
Descriptors: Educational Technology, Technology Uses in Education, Research and Development, Elementary Education
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Lim, Doo Hun; Morris, Michael Lane – Educational Technology & Society, 2009
Among the many studies focusing on the effect of learner and instructional variables on learning outcomes, few studies have investigated the effect of these variables and their mediating mechanisms influencing students' learning within a blended learning environment. This study examined the influence of instructional and learner variables on…
Descriptors: Undergraduate Students, College Instruction, Data Analysis, Student Characteristics
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