• Socioeconomic factors that lead to Latino male students leaving school before graduating

      D'Agostino, Joseph C.; Wong, Nga-Wing Anjela; Barnhardt, Raymond; Armstrong, Anne Brenner (2012-05)
      Students of color make up a predominant number of learners that leave high school before graduating (National Center for Education Research, 2009). I selected to study Latino males to narrow the scope of my research. The literature I reviewed pointed directly at socioeconomics as one of the primary factors. I feel there are more specific factors involved for many of the individuals impacted. I used a qualitative approach and utilized an anonymous survey and individual interviews to pinpoint some of these factors. The findings from my research further supported that socioeconomics were a leading factor. My data and literature review showed that school environment and stereotyping/discrimination also played a role. I intend to conduct further research to identify the additional sub-factors that are most prevalent to Latino males. My long-term goal is to provide information to my peers that can assist in the construction or reconstruction of programs that can offer the best support for these students.
    • Strengths-based analysis of student success in online courses

      Gering, Carol; Sheppard, Dani'; Morotti, Allan; Adams, Barbara; Renes, Susan (2017-08)
      The purpose of this research was to increase understanding of post-secondary student success in online courses by evaluating a contextually rich combination of personal, circumstantial, and course variables. A strengths-based perspective framed the investigation. Mixed-method data were collected and analyzed sequentially in three phases: two phases of quantitative collection and analysis were followed by qualitative interviews and comprehensive analysis. The study first used logistic regression to analyze existing data on more than 27,000 student enrollments, spanning a time period of four academic years. The second phase of research enhanced the modeling focused on a subset of the total population; students from a single semester were invited to complete an assessment of non-cognitive attributes and personal perceptions. Between the two phases, 28 discreet variables were analyzed. Results suggest that different combinations of variables may be effective in predicting success among students with varying levels of educational experience. This research produced preliminary predictive models for student success at each level of class standing. The study concluded with qualitative interviews designed to explain quantitative results more fully. Aligned with a strengths-based perspective, 12 successful students were asked to elaborate on factors impacting their success. Themes that emerged from the interviews were congruent with quantitative findings, providing practical examples of student and instructor actions that contribute to online student success.