TPC Journal-Vol 9- Issue 4-FULL ISSUE

350 The Professional Counselor | Volume 9, Issue 4 Because of the small number ( n = 19) of Native American, Hawaiian/Pacific Islander, and “two or more race” students, we did not use these ethnicities in our regression model. Representing all students is crucial in school counseling; however, with such small sample sizes, it might make the students personally identifiable (NCES, 2017). The Every Student Succeeds Act (ESSA) also has guidelines regarding minimum numbers of n -size requirements to make statistical inferences in state accountability systems, and 19 did not make the minimum (Alliance for Excellent Education, 2018). Measures Senior Exit Survey. This school district administers its Senior Exit Survey to each senior every school year between May 15 and June 15. The purpose of the survey is to assess the types of support services students accessed during their high school careers. The survey includes questions that directly answered the research questions posed for this study: whether students had met with their school counselor about (a) attendance; (b) college planning, applications, essays, and scholarships; (c) concerns about grades; and (d) goal setting (all responses coded as 0 for not met, and 1 for met). The survey also included a question that asked students, “Were there parts of the college search and/or application process you felt you needed more assistance or information?” We incorporated responses to this survey question into the current study as an additional predictor variable because we wanted to examine if the perception of needing more assistance resulted in students not enrolling in either a 2- or 4-year college (all responses coded as 0 for not attended, and 1 for attended). National Student Clearinghouse data. NSCH data is collected from over 3,600 colleges and universities, both private and public. Membership in the Clearinghouse is open to any postsecondary institution that participates in the Federal Title IV program. The data includes degrees obtained and enrollment in postsecondary institutions (NSCH, n.d.). The specific information used as the outcome variable in our study was if students enrolled in a 2- or 4-year postsecondary institution at least once in the 5 years after graduating from high school (coded as 1 for yes, or 0 for no). We used the 5-year time frame because not all students enroll immediately in college upon graduation, and we wished to capture students who enrolled later (NCES, 2005; Rowan-Kenyon, 2007). District data. Student data that has been known to reflect achievement and postsecondary enrollment were provided by the district as well. District data included in the data analysis was: (a) ethnicity, (b) GPA, and (c) FRL status. Data Construction and Analysis A de-identified dataset was obtained from the school district’s research department after receiving a research proposal. As the dataset was de-identified and had already been collected, the university IRB committee determined that an IRB application for human subjects was not required. A multiple logistic regression was performed, with binary and scale variables, using SPSS Statistics 22.0 to examine whether the set of school counseling duties (dependent variables) are statistically significant in predicting 2- or 4-year institution enrollment (independent variable). In addition to these, background supplemental independent predictor variables were included to assess their relative contribution to the outcome response. School counseling duties, FRL status, and ethnicity were coded as binary variables, and GPA was coded as a scale (A = 4, B = 3, C = 2, D = 1, F = 0). Some data was recoded in order to condense some of the information. One piece of the dataset that was recoded was the NSCH data. As there were 5 years of postsecondary enrollment data, it was condensed and recoded to create one variable that indicated if the individual had been enrolled (yes or no) in a postsecondary institution, either 2- or 4-year, during those 5 years.