<p> Accelerated courses and programs are becoming more common in higher education institutions. The rapid rate of change in the 21st century requires people to react quickly and adapt to consistent shifts in their environments. This shift toward an accelerated pace of life has caused a growing demand for accelerated and intensive classes in which students still need to achieve deep levels of learning. A gap seems to exist in the literature regarding how to design accelerated learning environments to support deep learning. The published research on accelerated learning contains a variety of studies across a variety of institutions and disciplines using a broad array of methodological approaches that produce variable results as to how accelerated courses impact student learning compared to the impact traditional courses have on learning. The fundamental research questions that guided this study asked, (a) Which instructional design strategies do expert instructional designers utilize to promote deep learning in online accelerated learning environments across various disciplines? and (b) How do expert instructional designers decide which instructional design strategies to utilize to promote deep learning in accelerated learning environments? This study utilized an online modified Delphi method to provide insight into the research questions. Fourteen members of a professional organization focused on educational technology participated in the study. Quantitative data provided descriptive statistics to determine the average consensus per statement per round. Qualitative data identified patterns and themes in written responses from the expert panel. The experts reached consensus on 59 statements (73%) in beliefs about effective instructional design strategies, 30 statements (59%) on deep learning strategies, and 21 statements (70%) on accelerated learning strategies. The study provided clear guidelines on effective strategies to promote deep, accelerated learning. </p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10285475 |
| Date | 01 July 2017 |
| Creators | Grincewicz, Amy M. |
| Publisher | Capella University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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