A Data Driven Approach to Increasing Entry-Level GE Math Completion
Project Lead: Dwight Wynne and Jessica Jaynes
SUMMARY
Historically, repeatable grade rates have been above 20% for all courses fulfilling the GE B.4 mathematics requirement, and thus a significant barrier to graduation. Math 120 is an entry-level statistics course fulfilling the GE B.4 requirement. In Fall 2017, the repeatable grade rate for this course peaked at 45% for underrepresented students and 34% for all students.
In Fall 2018, under the Executive Order of 1110, the Math 120 pedagogy was revised to: (1) use simulation-based methods and (2) involve active learning in at least 40% of each class. Following these pedagogical revisions, the repeatable grade rate substantially decreased to 12% for underrepresented students and 10% for all students as of Fall 2019.
The objective of this proposal is to create a sustainable program that provides support and resources for Math 120 instructors to effectively implement simulation-based methods and active learning in the classroom.
ANTICIPATED OUTCOMES
The outcomes of this proposal are to (1) maintain and decrease repeatable grade rates and the equity gaps in the repeatable grade rate in Math 120, (2) increase instructor self-efficacy with simulation-based methods and active learning, and (3) increase student self-efficacy with statistical methods by facilitating learning in multiple ways.
IMPACT ON GI2025
To continue to “move the needle” on student success, we aim to advance the following GI2025 working groups:
Group 1: Academic Preparation. Our program will provide all students with equal opportunity to succeed by bridging the gap between experienced and less experienced instructors.
Group 6: Bottlenecks. Following pedagogical revisions to Math 120, it has become the only GE math course to not be classified as a bottleneck course, with a 10% repeatable grade rate in Fall 2019.
Group 7: High-impact Practices. Math 120 has been redesigned around a series of active learning “investigations” that help students understand how statistical concepts build on each other and are used to solve real-world problems.
