<p> Accountability measures, by way of standardized curriculum and assessments, have played a large part in the attempt to ensure that students from all backgrounds receive equal access to quality education. However, the inherent disadvantage of a standardized system is the implied assumption that all students come in with the same knowledge, learn at the same pace, and learn the same way. In the wake of an increasingly diverse K-12 population, educational researchers, learning theorists, and practitioners agree that the concept of the average student is, in fact, a myth. Students come to school with different needs, norms, interests, cultural behavior, knowledge, motivations, and skill sets. In order for education to properly address the issue of equity, the issue of learner variance must first be attended to. </p><p> In 2010, the U.S. Department of Education released its educational plan encouraging teachers to address student variance through more inclusive learning environments. The report highlighted Blended Learning (BL) and Universal Design for Learning (UDL) as promising practices in enabling, motivating, and inspiring all students to achieve regardless of background, language, or disability. Research suggests that the combination of these two approaches could lead to transformative teaching practices that dramatically impact student learning. However, the efficacy of such a model has yet to be tested. </p><p> This study tested the efficacy of a Blended Universal Design for Learning (BUDL) model in improving student outcomes. An experimental design was used to explore the impact of a two-week BUDL intervention in an accelerated 7<sup> th</sup> grade math class. The effect on student achievement, engagement, and perception was measured. Both quantitative and qualitative data were collected. Though results from the study were statistically insignificant, possible positive associations between a BUDL intervention and student achievement, engagement, and perception emerged. Considerations for clinical significance, suggestions for improvement on the BUDL model, and implications for future research are discussed.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10128128 |
| Date | 24 June 2016 |
| Creators | Mathews, Kai Monet |
| Publisher | University of San Diego |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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