Education Commons^™

Effective Teaching Practices In Online Higher Education, Kim Mcmurtry

CCE Theses and Dissertations

In the context of continuing growth in online higher education in the United States, students are struggling to succeed, as evidenced by lower course outcomes and lower retention rates in online courses in comparison with face-to-face courses. The problem identified for investigation is how university instructors can ensure that effective teaching and learning is happening in their online courses. The research questions were:

1. What are the best practices of effective online teaching in higher education according to current research?
2. How do exemplary online instructors enact teaching presence in higher education?
3. What are the best practices of effective online teaching in …

Motivations Of Students In The Open-Ended Use Of Mobile Computing In Lecture-Based Classrooms, Jeffrey Kimball

CCE Theses and Dissertations

While research supports the integration of mobile computing into instruction, there is disagreement concerning the unstructured use of mobile devices in lecture-based college classrooms. Research supports the argument that unstructured use creates distraction and decreased academic performance. Research also suggests that unstructured use actually supports lecture instruction through personalized learning situations. In either case, the motivations of students to use mobile device is often unclear. This study sought to investigate the motivations for students’ acceptance of mobile devices. The Unified Theory of Acceptance and Use of Technology (UTAUT) was utilized to identify the factors leading to college students’ adoption of …

A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti

CCE Theses and Dissertations

Predictive statistical modeling shows promise in accurately predicting academic performance for students enrolled in online programs. This approach has proven effective in accurately identifying students who are at-risk enabling instructors to provide instructional intervention. While the potential benefits of statistical modeling is significant, implementations have proven to be complex, costly, and difficult to maintain. To address these issues, the purpose of this study is to develop a fully integrated, automated predictive modeling system (PMS) that is flexible, easy to use, and portable to identify students who are potentially at-risk for not succeeding in a course they are currently enrolled in. …