Intentional Curriculum Design: A Data-Centric Approach for STEM Curricula

From 2015-2025, I have had the distinct honor and privilege of serving as Director of the Center for Environmental Studies at Virginia Commonwealth University. During this time, the faculty and I conducted a complete revision of the undergraduate and graduate curricula. These changes resulted in:

• A marked increasing the quality, competitiveness, and preparation of the students.  The mean interval between graduation and the start of the first full-time position is 1.2 months (1.9 months standard deviation).
• The development of mechanisms that increased student-reported senses of belonging and identity in the unit and discipline.
• Increased enrollment in courses—and a concomitant increase of tuition generation—by 150%.

Developing a Pedagogy

During this process, we have learned several important lessons about curriculum design, development, assessment, and management. As a data nerd, I have been not only documenting all the steps we've taken (for reproducible research purposes) but also developing protocols and software for quantitative and qualitative analysis of our progress.

A large-scale reorganization in 2025 will result in the dissolution of the Center for Environmental Studies. The programs we have developed will be merged into a general biology department serving ~2000 pre-health/professional majors—which will undoubtedly impact the future trajectory of the existing academic programs.

I hope this book project can effectively document lessons learned and guide other units interested in implementing data-centric approaches to academic curriculum development.

The general outline of the Book builds on the following components:

ICD Foundations - General Philosophy and Frameworks in ICD.

The Curricular Landscape - How can we use quantitative decision analytics to optimize the efficacy of our programs?

Linguistic Taxonomies of STEM Programs: Parsing Course Descriptions

This post is a data component of the work going into the Intentional Curriculum Design: A Data-Centric Approach for STEM Curricula. This contributes to the section defining The Curricular Landscape, where I define undergraduate STEM programs at VCU and from across the Commonwealth of Virginia, using a quantitative linguistic approach

rodneydyerRodney Dyer

Frequency-Dependent Linguistic Embedding of Course Descriptions

Mapping textual input into quantitative spaces facilitates statistical analyses supporting decision analytics. Here, university course descriptions are mapped onto numerical spaces and used to define the landscape of academic offerings.

rodneydyerRodney Dyer

Bottom-Up Development - Strategies for faculty-motivated curriculum change.

Data Acquisition & Microassessments - Embed processes that produce curriculum-relevant data.

Curricular Structure & The Flow of Learning - A curriculum is more than just a collection of courses. How do we optimize emergent benefits based on the composition and configuration of an academic program?

Cohort-Based Implementations - Curriculum change is in progress, and methods should be adopted to minimize disruption to students and faculty while implementing new initiatives.

Faculty & Curriculum Assessment - Data-driven changes must be based on quantitative analytics.

Continual Curricular Ordination - The importance of continual evaluation and revisions based on temporal trends.