By Lisa Dierker, Ph.D., Wesleyan University
I teach introductory statistics. Yes, I know what many are thinking. I know because when I attend parties and mention this in the course of conversation, people tend to force a smile and move away from me as quickly as possible. The rare party guest who doesn’t walk away regales me with the harrowing, dispiriting and/or mind-numbingly boring experience they had in their first (and usually last) statistics course. Those who actively avoided taking statistics tend to make self-disparaging comments about their math ability and suggest that I am doing something out of their reach. I say things like “no, it’s not like that” and “you would love this course”, but it’s a hard sell.
Except that, the course is not like that and you would definitely love it. Passion-Driven Statistics is a project-based introductory curriculum that has been implemented as a statistics course, a research methods course, a data science course, a capstone experience, and a summer research boot camp with students from a wide variety of academic settings. Liberal arts colleges, large state universities, regional colleges/universities, medical schools, community colleges, and high schools have all successfully implemented the model. Funded by the National Science Foundation, the curriculum engages students in authentic projects with large, real-world data sets (e.g. National Household Survey on Drug use and Health, The Behavioral Risk Factor Surveillance System, and National Longitudinal Study of Adolescent to Adult Health) from the very first day! (Dierker et al, 2012). There are no canned exercises, and at the same time, no M&M’s or other entertaining maneuvers. Instead, the focus is on welcoming and empowering students to ask and answer questions they care about. Is exposure to a drug use prevention curriculum associated with lower rates of experimentation with diverse substances? Are religious adolescents less likely to be depressed? What factors predict ‘safe sex’ practices? As students engage in productive struggle in the context of their own original research, the instructor and peer mentors support each student individually through ample one-on-one mentoring. Together, we take students completely out of their comfort zone, and at the same time “love them through it” by creating an inviting classroom culture and an experience that gives them a safe and supportive space to “get it wrong before they get it right”, no matter their educational background or experience.
Research evaluating the model has been exciting to see unfold. The curriculum attracts higher rates of under-represented minority (URM) students compared to a traditional statistics course and students enrolled in Passion-Driven Statistics are more likely to report increased confidence in working with data and increased interest in pursuing advanced statistics coursework (Dierker et al., 2018). In new research currently under review, the project-based curriculum promoted further training in statistics. Using causal inference techniques to achieve matched comparisons across three different statistics courses, students originally enrolled in Passion-Driven Statistics were significantly more likely to take at least one additional undergraduate course focused on statistical concepts, applied data analysis, and/or use of statistical software compared to students taking either a psychology statistics course or math statistics course. Further, Passion-Driven Statistics students took a larger number of one of these additional courses compared to students originally enrolled in either of the comparison courses.
Many student reactions have supported the positive impact of the course. In anonymous post-course evaluations, one student wrote, “I have never felt so excited and motivated to be part of an academic environment as I have in this class. I am so proud of my work.” Another wrote, “Allowing students to pick from a study and data set to answer their own research question was effective because we became attached to our own projects, understood exactly why we were learning what we were learning, and wanted to know more.” Finally, “Though the structure of the class is unorthodox, the resulting education is priceless. Aside from teaching me the valuable process and application of statistical inquiry, this course taught me how to take initiative and start a scientific project that I can call my own.”
Resources are available at https://passiondrivenstatistics.com/. Some that you might find most helpful include 1) a free e-book, with links to videos that allow you to “flip” the classroom and 2) translation code aimed at supporting the use of statistical software across all of the major platforms (i.e. SAS, R, python, Stata and SPSS).
We are currently in the second year of a 5-year NSF grant aimed at nationwide dissemination of the model. If you are interested in learning more or attending one of several faculty workshops, I would encourage you to get in touch; email me at firstname.lastname@example.org. Because of the diversity of psychology majors nationwide, statistics instructors have great potential to break down long-standing disparities and contribute to opening the analytics economy to everyone. Along the way, we might even end up being less lonely at parties. J
Dr. Lisa Dierker is the Walter Crowell University Professor of Social Sciences and Professor of Psychology at Wesleyan University. She received her Ph.D. in Developmental Psychology from the University of Connecticut and completed postdoctoral training in Epidemiology at the Yale School of Medicine. A researcher in addictive behaviors, her more recent work based on the NSF funded Passion-Driven Statistics Project centers on the dissemination of innovative pedagogical practices.
Dierker, L., Kaparakis, E., Rose, J. & Selya, A. (2012). Strength in numbers: A multidisciplinary, project-based course in introductory statistics. Journal of Effective Teaching, 12(2): 4-14.
Dierker, L., Woods, K., Singer-Freeman, K., Germano, K.,Cooper, J.L. & Rose, J. (2018). Evaluating Impact: A comparison of learning experiences and outcomes of students completing a traditional versus multidisciplinary, project-based introductory statistics course, International Journal of Education, Training and Learning, 2(1), 16-28.