M.Ed. in Quantitative Methods
The master of education (M.Ed.) in Quantitative Methods (QM) is designed to provide students with strong quantitative methods training for applied research settings. Students for whom the new program would have interest and value are those who wish to work in school systems, government, industry, dedicated research institutes, academic settings, and medical school research settings.
Students in this 32-hour program take two required core courses in quantitative methods, two required hours of seminar activity, and eight additional courses, of which one may be a content course (i.e. outside the QM area) and one may be a QM course outside of Psychology and Human Development. The program culminates in a summer-long or semester-long internship in which students obtain real-world experience producing data analyses for a public or private organization in Nashville or the broader research community.
Students trained in this program will be placed in such internships based on their data analytic skills, training in research design, statistical software skills, excellent writing/report and general communication ability, and their ability to develop and critique research designs, measurement plans, and sampling schemes.
Potential employers for such students will partially overlap with the internship settings for the QM masters students. A particularly strong research setting in need of such employees is the medical school research setting, many of which have dedicated research teams that employee data analytic, measurement, and design experts full-time to work on funded biomedical research projects. Another such setting is the public school system, which has increased needs for data analysis, measurement, and reporting expertise that has multiplied dramatically since the implementation of No Child Left Behind and associated school accountability initiatives.
Two required QM courses:
- PSY-GS 310 & 311, the two-semester introductory statistics sequence
Required Seminar enrollments:
- Students must obtain at least two hours from the regular one-hour QM seminar series, PSY-GS 300
Eight three-hour elective courses:
Of these, one QM course can come from outside the QM program e.g., biostatistics, or other quantitative methods courses within Peabody. In addition, one course can be a content course from within the Psychology Department (Peabody or A&S). Thus, of the eight electives, six must come from within the Psychology and Human Development QM curriculum (and seven or eight can come from the QM curriculum), including:
- PSY-GS 312, Multivariate;
- PSY-GS 313, Regression and Correlation;
- PSY-GS 314 Structural Equation Modeling;
- PSY-GS 317 Psychometric Methods;
- PSY-GS 319, Advanced Topics in SEM;
- PSY-GS 319, Exploratory Data Analysis;
- PSY-GS 319, Non-parametric Statistics;
- PSY-GS 320, Factor Analysis;
- PSY-GS 321, Multi-level Modeling;
- PSY-GS 322, Growth Curve Modeling;
- PSY-GS 323, Mixture Modeling;
- PSY-GS 326, Introduction to IRT;
- PSY-GS 327, Advanced IRT;
Total hours = 32
Near the end of the two-year program, all M.Ed. students must complete an intensive internship (either a three- or four-month semester internship, or a two-month summer internship). The internship will occur in an actual applied research setting, such as a school system, a medical school research setting, a testing company, or a policy institute.
A Vanderbilt faculty member and a representative of the organization will collaborate to supervise the internship. Upon completion, the student will write a 2,000-2,500 word research summary (approximately eight to 10 double-spaced pages) summarizing research activity during the internship. The summary must indicate research activity on which the student worked, the student’s specific contribution, analtyic methods employed, software employed, and the products of the research activity. The conclusion to the research summary should critically evaluate the contribution of the internship experience to the student’s personal career goals. The summary is submitted to the Vanderbilt QM faculty member supervising the student’s internship.
For additional information about the QM program and its faculty, click here.