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Anna Moni – Online Learning, 2024
Despite extensive research on feedback models, there is still sparse empirical evidence of their validity and application in higher education learning settings, whether online, hybrid, or face-to-face. Understanding how a feedback framework--integrated in the instructional cycle--is perceived by the learners can provide empirical support about its…
Descriptors: Student Attitudes, Feedback (Response), Electronic Learning, Blended Learning
Lee, Jeonghyun; Soleimani, Farahnaz; Irish, India; Hosmer, John, IV; Soylu, Meryem Yilmaz; Finkelberg, Roy; Chatterjee, Saurabh – Online Learning, 2022
In this study, we work towards a strategy to measure and enhance the quality of interactions in discussion forums at scale. We present a machine learning (ML) model which identifies the phase of cognitive presence exhibited by a student's post and suggest future applications of such a model to help online students develop higher-order thinking. We…
Descriptors: Online Courses, Models, Thinking Skills, Computer Mediated Communication
Olesova, Larisa; Campbell, Susan – Online Learning, 2019
The "2017 Survey of Faculty Attitudes on Technology" conducted by Insider Higher Ed reported on the low percentage of partnerships between university faculty and instructional designers in online course development. Experts were unsurprised because instructional designers (IDs) are underutilized, and their role in higher education is…
Descriptors: Mentors, Models, College Faculty, Instructional Design
Borup, Jered; Evmenova, Anna S. – Online Learning, 2019
Growth of online learning has placed increased pressure on K-12 schools and universities to provide students at all levels with qualified instructors. It is especially important that colleges of education provide pre- and in-service teachers with skilled online instructors so that they can experience the benefit of quality online instruction…
Descriptors: Schools of Education, Electronic Learning, Faculty Development, College Faculty