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Yangyang Luo; Xibin Han; Chaoyang Zhang – Asia Pacific Education Review, 2024
Learning outcomes can be predicted with machine learning algorithms that assess students' online behavior data. However, there have been few generalized predictive models for a large number of blended courses in different disciplines and in different cohorts. In this study, we examined learning outcomes in terms of learning data in all of the…
Descriptors: Prediction, Learning Management Systems, Blended Learning, Classification
Marton McGowin, Brooke; Lockee, Barbara B. – Distance Learning, 2022
As higher education institutions begin to reemerge from the global pandemic, they are reimagining how multimodal learning environments (MMLE) can be used to help shape future delivery modes. This article explores definitions for multimodal learning environments in terms of pedagogy, implementation, and management. According to this study,…
Descriptors: Higher Education, Blended Learning, Educational Environment, Delivery Systems
Debbie A. Sanders; Shirley S. Mukhari – Education and Information Technologies, 2024
The purpose of this research is to analyse the support that lecturers need to be able to implement a blended learning approach successfully. Blended learning is now seen as an approach that can create engaging learning environments, to enhance students' self-directed learning and improve the whole learning experience. The study investigated the…
Descriptors: Teacher Attitudes, Blended Learning, Correlation, Foreign Countries
Self-Regulation Strategies in Blended Learning Environments in Higher Education: A Systematic Review
Eggers, Jan Hein; Oostdam, Ron; Voogt, Joke – Australasian Journal of Educational Technology, 2021
Although self-regulation is an important feature related to students' study success as reflected in higher grades and less academic course delay, little is known about the role of self-regulation in blended learning environments in higher education. For this review, we analysed 21 studies in which self-regulation strategies were taught in the…
Descriptors: Metacognition, Blended Learning, Teaching Methods, Learning Strategies
Ali, Amira D.; Hanna, Wael K. – Journal of Educational Computing Research, 2022
With the spread of the COVID-19 pandemic, many universities adopted a hybrid learning model as a substitute for a traditional one. Predicting students' performance in hybrid environments is a complex task because it depends on extracting and analyzing different types of data: log data, self-reports, and face-to-face interactions. Students must…
Descriptors: Predictor Variables, Academic Achievement, Blended Learning, Independent Study
Zamborova, Katarina; Klimova, Blanka – Contemporary Educational Technology, 2023
The article presents the research of empirical mixed methods on the use of a modern mobile reading app compared to traditional forms of teaching in English business classes in higher education in Slovakia. The research belongs to the theoretical frame of the mobile assisted language learning field that has generated an interest since the early…
Descriptors: Business English, English for Special Purposes, Computer Software, Computer Assisted Instruction
Lu, Dang-Nhac; Le, Hong-Quang; Vu, Tuan-Ha – Education Sciences, 2020
The COVID-19 epidemic is affecting all areas of life, including the training activities of universities around the world. Therefore, the online learning method is an effective method in the present time and is used by many universities. However, not all training institutions have sufficient conditions, resources, and experience to carry out online…
Descriptors: Electronic Learning, Adoption (Ideas), Higher Education, Evaluation Methods
de Carvalho, Walisson Ferreira; Zárate, Luis Enrique – International Journal of Information and Learning Technology, 2021
Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…
Descriptors: Causal Models, Algorithms, Learning Analytics, Correlation
Mirmoghtadaie, Zohresadat; Keshavarz, Mohsen; Mohammadimehr, Mojgan; Rasouli, Davood – International Review of Research in Open and Distributed Learning, 2023
In peer observation of teaching, an experienced colleague in the educational environment of a faculty member observes the educational performance of that faculty member and provides appropriate feedback. The use of peer review as an alternative source of evidence of teaching effectiveness is increasing. However, no research has been done in the…
Descriptors: Learning Management Systems, Academic Achievement, Peer Evaluation, Teacher Evaluation
Julia, J.; Afrianti, Nurul; Soomro, Kamal Ahmed; Supriyadi, Tedi; Dolifah, Dewi; Isrokatun, I.; Erhamwilda, E.; Ningrum, Dedah – European Journal of Educational Research, 2020
Nowadays, teaching and learning activity employing the flipped classroom model has an important position in the process of providing education. This research aimed at identifying and analyzing articles examining the flipped classroom model that has been published in several reputable international journals issued in the 2010-2019 timeframe, which…
Descriptors: Teaching Methods, Bibliometrics, Models, Journal Articles
Raman, Preeti; Avery, Teresa; Brett, Clare; Hewitt, James – International Journal of E-Learning & Distance Education, 2020
Growing interest in online learning has instructors looking for new ways to engage learners in asynchronous discussions. Building on experiences with hashtag use to connect on social media platforms, the purpose of this study is to investigate the contexts of hashtag use and its associated impact on learner engagement in asynchronous online…
Descriptors: Social Media, Computer Mediated Communication, Asynchronous Communication, Discussion
Owusu-Agyeman, Yaw; Larbi-Siaw, Otu – Education and Information Technologies, 2017
This study argues that in developing a robust framework for students in a blended learning environment, Structural Alignment (SA) becomes the third principle of specialisation in addition to Epistemic Relation (ER) and Social Relation (SR). We provide an extended code: (ER+/-, SR+/-, SA+/-) that present strong classification and framing to the…
Descriptors: Blended Learning, Specialization, Educational Policy, Guidelines
Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel – Journal of Educational Computing Research, 2019
Several studies have focused on identifying the significant behavioral predictors of learning performances in web-based courses by examining the log data variables of learning management systems, including time spent on lectures, the number of assignments submitted, and so forth. However, such studies fail to quantify the impact of emotional,…
Descriptors: Predictor Variables, Correlation, Student Motivation, Metacognition
Avogadro, Paolo; Calegari, Silvia; Dominoni, Matteo Alessandro – Interactive Technology and Smart Education, 2016
Purpose: A social learning management system (social LMS) is a tool which favors social interactions and allows scholastic institutions to supervise and guide the learning process. The inclusion of the social feature to a "normal" LMS leads to the creation of educational social networks (EduSN), where the students interact and learn. The…
Descriptors: Management Systems, Learning Processes, Socialization, Classification
Galanti, Terrie McLaughlin; Baker, Courtney Katharine; Morrow-Leong, Kimberly; Kraft, Tammy – Interactive Technology and Smart Education, 2021
Purpose: In spring 2020, educators throughout the world abruptly shifted to emergency remote teaching in response to an emerging pandemic. The instructors of a graduate-level synchronous online geometry and measurement course for practicing school teachers redesigned their summative assessments. Their goals were to reduce outside-of-class work and…
Descriptors: Technological Literacy, Pedagogical Content Knowledge, Teaching Methods, Mathematics Instruction