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Abstract
This study examined the levels of self-determination skills of a select sample of African American students with learning disabilities who attend two selected Historically Black Colleges or Universities (HBCU), and who are enrolled in a learning disability (LD) program or disability services at their school. The study was an extension of the current literature base that has examined self-determination skills at the university level (L. Y. Peterson, 2004; Rasheed, 2005; Sarver, 2000). This study is the first study examining self-determination skills of students with learning disabilities in the Historically Black College or University setting. The investigator employed survey research methods to complete this study. The researcher administered a demographic survey to gain basic background information on the participants. Participants were also administered a revised copy of the Adolescent Version of The Arcs Self-Determination Scale originally created by Wehmeyer (1995) and revised by Rasheed (2005) for use in higher education settings. The Arcs Self-Determination Scale is a 72- item self-report instrument with total scores ranging from 0-148 and with higher scores representing higher levels of self determination skills. The Arcs Self-Determination Scale has four sub-domains: Autonomy, Self-Regulation, Psychological Empowerment, and Self-Realization. The researcher combined the two instruments and administered them during the end of the fall semester 2006 academic year to students enrolled in disabilities services or learning disability centers at two HBCUs. A total of 83 students participated in this study. Results from this study indicate the majority of the students in the study had at least a minimal level of overall total self-determination skills. The total self-determination scores and scores in the sub-domains do indicate that there is a need for academic interventions to improve the self-determination skills of this population. A one-way analysis of variance (ANOVA) was found to be statically significant for student classification and grade point average (GPA) as it related to Self-Regulation domain scores. A regression analysis revealed that both student classification and GPA were significant predictors for Self-Regulation sub-domain scores.