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Ghai, Akanksha; Tandon, Urvashi – Education and Information Technologies, 2023
The current study investigates the interaction of Gamification, and Instructional Design to enhance the Usability of e-Learning in higher education programs. The study also examines the mediating role of Instructional design. Data were collected from a self-structured questionnaire from the academicians and was analyzed through Structural Equation…
Descriptors: Gamification, Instructional Design, Usability, Electronic Learning
Dee Crowe Thornton – ProQuest LLC, 2024
The community of inquiry (CoI) framework is commonly used to study online learners' engagement and satisfaction. However, few studies have examined CoI's ability to predict online undergraduate students' end-of-course grades. The purpose of this quantitative hierarchical multiple regression study was to determine the ability of the CoI framework…
Descriptors: Communities of Practice, Predictor Variables, Grades (Scholastic), Undergraduate Students
Xingsu Wu; Chunyang Xu – Education and Information Technologies, 2025
This study, anchored in the empirical domain of student learning experiences, employs the Chaoxing Fanya network teaching platform to delineate a comprehensive model of factors that influence student learning experiences within the framework of blended collaborative learning. Through a rigorous synthesis of extant literature and qualitative…
Descriptors: Learning Experience, Blended Learning, Cooperative Learning, College Students
Emami, M. Reza; Bazzocchi, Michael C. F.; Hakima, Houman – International Journal of Technology and Design Education, 2020
Cornerstone design courses have become a major part of engineering curricula, where students with different personality types and learning styles work together to design, develop, build, and demonstrate the functionality of a prototype within the duration of a term. This study analyzes student and team performance against gender, personality…
Descriptors: Undergraduate Students, Engineering Education, Design, Personality Measures
Libor Juhanák; Vojtech Jurík; Nicol Dostálová; Zuzana Juríková – Australasian Journal of Educational Technology, 2025
The use of metacognitive prompting to support self-regulated learning is a well-established area of research in education. Despite receiving considerable attention, the precise mechanism of prompting and its effects on the learning process remain unclear, especially in the context of multimedia learning. This study employed a controlled laboratory…
Descriptors: Metacognition, Cues, Outcomes of Education, Undergraduate Students
Using Analytics to Predict Students' Interactions with Learning Management Systems in Online Courses
Ali Alshammari – Education and Information Technologies, 2024
In online education, it is widely recognized that interaction and engagement have an impact on students' academic performance. While previous research has extensively explored interactions between students, instructors, and content, there has been limited exploration of course design elements that promote the fourth type of interaction:…
Descriptors: Learning Analytics, Learning Management Systems, Academic Achievement, Correlation
Hoffman, Daniel L.; Furutomo, Faye; Eichelberger, Ariana; McKimmy, Paul – Innovative Higher Education, 2023
Many models of online student engagement posit a "more is better" relationship between students' course-related actions and their engagement. However, recent research indicates that the timing of engagement is also an important consideration. In addition to the frequency (how often) of engagement, two other constructs of timing were…
Descriptors: Learner Engagement, Online Courses, Asynchronous Communication, Time Factors (Learning)
Abdullah, M. Almanie – Cypriot Journal of Educational Sciences, 2022
The aim was to investigate the role of online stakeholder groups, Instructional Design and Student satisfaction in predicting Quality of distance education during the COVID-19 pandemic. A survey method was used. The online stakeholder groups, Instructional Design and Student satisfaction are the IVs, while the dependent variable is Quality of…
Descriptors: Predictor Variables, Educational Quality, Distance Education, COVID-19
Tomás Hyland; Niall Seery; Jeffrey Buckley – European Journal of Engineering Education, 2024
An association between spatial ability, particularly visualisation, and science, technology, engineering, and mathematics (STEM) education has been repeatedly demonstrated over the past four decades. Understanding this relationship is of critical importance as substantial evidence illustrates the malleability of spatial ability and that the…
Descriptors: Spatial Ability, Predictor Variables, Retention (Psychology), Visualization
Alshehri, Mohammad; Alamri, Ahmed; Cristea, Alexandra I.; Stewart, Craig D. – International Journal of Artificial Intelligence in Education, 2021
Since their 'official' emergence in 2012 (Gardner and Brooks 2018), massive open online courses (MOOCs) have been growing rapidly. They offer low-cost education for both students and content providers; however, currently there is a very low level of course purchasing (less than 1% of the total number of enrolled students on a given online course…
Descriptors: Instructional Design, Online Courses, Consumer Economics, Student Behavior
Goegan, Lauren D.; Dueck, Bryce S.; Daniels, Lia M. – Social Psychology of Education: An International Journal, 2021
Expectancy Value Theory (EVT) is a prominent theory on student motivation. To add to the growing research in this area, we investigated students within a large, mandatory course outside of the STEM areas, to examine perceptions of success utilizing an EVT lens. The aim of our study was twofold. First, to examine students' open-ended responses…
Descriptors: Undergraduate Students, Student Attitudes, Postsecondary Education, Student Satisfaction
Liao, Hongjian; Zhang, Qianwei; Yang, Lin; Fei, Yuenong – Education and Information Technologies, 2023
This study explored the relationships among regulated learning, teaching presence and student engagement in blended learning. A two-level model was designed based on contextual factors (teaching presence) and individual factors (regulated learning), and experience sampling method was employed to collect intensive longitudinal data on 139…
Descriptors: Metacognition, Teaching Methods, Learner Engagement, Blended Learning
Siu-Cheung Kong; Wei Shen – Interactive Learning Environments, 2024
Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…
Descriptors: Student Characteristics, Predictor Variables, Comprehension, Computation
Jordan Elaine Fink – ProQuest LLC, 2024
Professional advocacy is central to the counselor's professional identity and is essential for counselors to maintain the privilege of serving clients. Despite CACREP requirements for programs to provide training in professional advocacy, counseling students may need more training in this area. This quantitative study examined professional…
Descriptors: Advocacy, Competence, Masters Programs, Graduate Students
Jirasatjanukul, Kanokrat; Jeerungsuwan, Namon – International Education Studies, 2018
The objectives of the research were to (1) design an instructional model based on Connectivism and Constructivism to create innovation in real world experience, (2) assess the model designed--the designed instructional model. The research involved 2 stages: (1) the instructional model design and (2) the instructional model rating. The sample…
Descriptors: Instructional Innovation, Curriculum Design, Constructivism (Learning), Models