<p> Learning deficits and disabilities affect many students in mathematics. On average, seven percent of students in schools are identified as a having mathematics learning disability (MLD), while an additional 10% have been identified as low achievers in mathematics (Geary, 2011). A common skill deficit found in students struggling in mathematics lies in the development of computational fluency skills, which lay the foundation for understanding higher order mathematical concepts in school (Gersten, Jordan, & Flojo, 2005). Furthermore, mathematics skill acquisition and application facilitates individual success beyond school years (Geary, 2013). </p><p> Since the reauthorization of the Individuals with Disabilities Education Act in 2004, an emphasis has been placed on implementing early identification and intervention services for students struggling to advance their academic knowledge and skills (U.S. Department of Education, 2004). To help bridge the gap between identifying effective interventions and individual student needs, Brief Experimental Analysis (BEA) has been employed. The goal of BEA is to quickly assess a student’s response to multiple interventions to determine which is most successful in addressing the target need. Beyond the benefits experienced on the individual student level, the use of BEA to guide intervention has resulted in time-efficient and cost-effective intervention selection procedures (Mong & Mong, 2012). Past researchers have supported the effectiveness of BEA predicted interventions by conducting extended analyses, where the BEA predicted intervention is evaluated for its effectiveness long term (Codding et al., 2009; Mong & Mong, 2012). Math to Mastery (MTM) is a newly emerging intervention that has been found to be effective in increasing computational fluency (Mong & Mong, 2010; Mong & Mong, 2012). MTM is comprised of five components, including problem previewing, repeated practice, corrective feedback, performance feedback, and charting (Mong & Mong, 2010). When compared to other computational fluency interventions with well-established research bases, MTM has been found superior in increasing fluency; however, MTM has not been supported as a time-efficient intervention (Mong & Mong, 2010; Mong & Mong, 2012). This study will extend the work of Everett, Swift, McKenney and Jewell (2016) by conducting a BEA of the successive components of the MTM intervention to determine which components of MTM are most effective and efficient in increasing individual computational fluency skills. To address the limitations of Everett et al. (2016), multiple intervention phases will be included in the extended analysis to further evaluate the predictive validity of BEA methodology in MTM intervention.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10260770 |
| Date | 03 June 2017 |
| Creators | Felchner, Lindsay M. |
| Publisher | Southern Illinois University at Edwardsville |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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