As evidenced by leading educational research, today’s nontraditional student constitutes the majority of the college student population (Choy, 2002). Higher education institutions have an ethical, intellectual, and financial responsibility to consider and meet the unique needs of nontraditional students. Often such a mandate is met with words of agreement, but implementing institutional measures to assess and address these needs are a completely different challenge altogether (Watson, 2009; Brock, 2010). There are numerous demographic and socio-economic variables that may qualify a student as nontraditional (Giancola, Munz, & Trares, 2008). For the purposes of this analysis, “nontraditional” refers to individuals who are first-generation and lowincome students. Refining the analysis based on these two groups helps focus the educational model to more directly address the needs of this student population. Furthermore, it is important to highlight that nontraditional students often have needs as unique as the individuals themselves and therefore it is unfair to generalize about a “one-size-fits-all” model of assessing and tackling their educational obstacles (Kasworm, 2008). Patience, innovation, and creativity are needed institutionally to drive the model of educational success.
In the age of “big data” and predictive analytics, modeling is a powerful tool to identify and examine the early warning signs of educational obstacles in the nontraditional student population (Campbell, DeBlois, & Oblinger, 2007). There are four central themes that drive our proposed model: (1) the importance of formalized student advising, (2) early detection of obstacles along with subsequent interventions, (3) individualized attention to specific obstacles, and (4) identifying educational obstacles by which an institution may enact change as well as personal obstacles which an institution has very little – if any – control, save that of perhaps supportive counseling.
Date of this Version
Willis, James E. III, "An Adaptable Model for Improving Accessibility and Success Rates for First-Generation and Low-Income Students." (2012). Teaching and Learning Technologies Publications. Paper 3.