Statistical Analysis Consultation
“By providing a means to show resulting outcomes based on a rigorous research methodology, administrators can make policy decisions with a higher level of confidence that these programs should be continued or possibly that these programs are not providing any additional benefits and therefore, should be discontinued” (Vaughan, Lalonde, & Jenkins-Guarnieri, 2014, p. 566).
Educational research and statistical analysis is challenging due to the nature of student enrollment and self-selection in higher education. However, as the quote above illustrates, ongoing analysis is critical to ensure that programs are meeting expectations and are a responsible use of limited resources.
Yet, not everyone is a statistician. The other important consideration is the ability to share the information in such a way that stakeholders (i.e., administrators, faculty, students, parents, etc.) understand the data and its implications.
At VALC, we have the necessary skills to provide comprehensive and rigorous analysis of program effectiveness over the short and long term. This includes sharing the results in a clear and useful way to inform decision making at all levels. Typical questions we have answered recently include:
Is participation in a research-based academic FYS related to higher first-year achievement (i.e., first-term GPA and one-year persistence) for first-time STEM students including those students who are at additional risk (i.e., first-generation and conditionally-admitted students)?
Are there differences in academic outcomes between undeclared FYS participants and non-participants who identify as either first-generation students or students of color?
Does self-selection into a FYS course increase student persistence after four years compared with students (with similar/matched demographics) who did not take the course?
Does student achievement (i.e., first-term GPA and one-year persistence) vary by the FYS credit level?