Online higher education is a field that can benefit significantly from further research on innovative pedagogical methods designed to support students and decrease attrition rates. One method shown to improve engagement and retention of students in online environments is to include interactive engagement. This case study explored the patterns of students' interactions and assessment performance in an introductory teacher education one-course cohort. The study used a conceptual framework incorporating Bandura's social learning theory and Siemens' theory of connectivism. The study assessed archival data, from Adobe Connect recordings and records of competency pass rates, on the interactions and patterns of behavior between instructors and participants, and their association with the final assessment results. Data were analyzed by type and frequency of interaction, organized with NVivo software. The findings were that the pattern of understanding and applying level questions, as classified by Bloom's Revised Taxonomy, provoked the most responses, comments, and questions from the participants. Applying had the highest direct response and suggested an interpretation about online students wanting to respond to questions from instructors that prompt higher-level thinking skills and stimulate interactions. No patterns of behavior were evident between the student interactions and final assessment performance. The results indicate positive implications for social change in the role of the instructor to facilitate understanding and among participants who engage in positive learning interactions. The education profession could benefit from further research with a focus on content questioning best practices, retention methods, and the nature of social and learning interactions in online education.
Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-2968 |
Date | 01 January 2016 |
Creators | Smith, Janeal Crane |
Publisher | ScholarWorks |
Source Sets | Walden University |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Walden Dissertations and Doctoral Studies |
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