Enrollment in online courses is increasing at a much higher rate than enrollment in on campus courses. Initially, online systems were developed by moving course content from in-class courses as is to an online platform. Later, Web 2.0 technology was implemented in order to improve students’ online engagement. These systems considered all students as one homogeneous group and ignored the fact that different students learn in different ways and at different speeds. Later, adaptive online learning systems were developed based on the assumption that if the instructional approach matches the student learning style, student performance and experience will improve. The use of these systems yielded mixed results because there is no agreement on what, how, and when to adapt instructions. The problem is that there is still a lack of empirical evidence about which online learning system’ design is the most effective, efficient, and engaging.
There were two goals for this study. The first was to develop a new instructional theory and design model suitable for personalizing and adapting online learning. The first goal was achieved by developing student personalized, adaptive, and comprehensive e-learning spaces instructional theory and design model. This theory is based on finding the best fit among student characteristics, knowledge domain objectives, and technology used in delivering the online course. The second goal was to implement the newly developed theory and design model in an e-learning system prototype. This goal was achieved by developing and internally validating the e-learning system prototype by utilizing a panel of five instructional design experts. The Delphi method was used to solicit input from the expert panel in three rounds of validation. The validation process resulted in the experts’ consensus that the prototype incorporated the instructional theory and design model well and that this instructional theory holds the promise of increasing online learning courses’ effectiveness, efficiency, and student engagement.
| Identifer | oai:union.ndltd.org:nova.edu/oai:nsuworks.nova.edu:gscis_etd-1373 |
| Date | 01 January 2016 |
| Creators | Samwel, Emad |
| Publisher | NSUWorks |
| Source Sets | Nova Southeastern University |
| Detected Language | English |
| Type | dissertation |
| Format | application/pdf |
| Source | CCE Theses and Dissertations |
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