Course Design · OR 6205 Deterministic Operations Research
Full course design as Teaching Fellow · Backward design · Active learning · Inclusive assessment
Overview
As Teaching Fellow for OR 6205 (Deterministic Operations Research) at Northeastern University in Spring 2026, I designed a full graduate-level course from scratch — syllabus, course map, in-class exercises, case studies, assessments, and grading plan — using backward design as the organizing framework.
This page documents the design process, key decisions, and what I learned. It is also a teaching project in its own right: I am currently writing a working paper on the Teaching Fellowship experience as a model for instructor development in IE.
🏆 This course was recognized with the 2026 COE Outstanding Graduate Teaching Award (PhD), Northeastern University College of Engineering.
Design Process
Step 1 — Learning objectives first.
Before a single activity was planned, I wrote the five course-level learning objectives: formulate, solve, analyze, interpret, and evaluate. Every subsequent decision — what to assign, how to grade it, what to do in class — was tested against these objectives.
Step 2 — Backward from assessment.
I designed the final project (a real-world LP case analysis) before designing lectures. In-class exercises, at-home problems, and discussion posts all scaffold toward that project, giving students repeated low-stakes practice with the same core skills.
Step 3 — Building in feedback loops.
All graded work includes rework opportunities for additional credit. Mid-semester, I distributed an anonymous feedback survey and a structured reflection. Based on student responses, I shifted from slide-based delivery to collaborative board work — step-by-step examples developed with students in real time. Engagement increased noticeably.
Step 4 — Ethics integrated, not appended.
Each case analysis asks students: Whose interests are represented in this model? What is optimized, and for whom? What unintended consequences might arise? This is not a separate “ethics module” — it runs through the entire course.
Key Materials
| Material | Description |
|---|---|
| Syllabus | Full course syllabus with learning objectives, policies, AI use statement |
| Course Map | Week-by-week alignment of objectives, activities, and assessments |
| Grading Plan | Assessment weights, rubric philosophy, rework policy |
| In-Class Exercises (Feb 20) | Sample active learning exercises |
| Gurobi Python Guide | Student-facing Python/Gurobi reference created for this course |
| Discussion Worksheet 4-1 | Sample critical analysis discussion prompt |
TRACE Evaluation Highlights (Spring 2026)
| Item | Course Mean | Dept. Mean |
|---|---|---|
| Displayed enthusiasm for the course | 4.80 | 4.55 |
| Provided sufficient feedback | 4.60 | 4.29 |
| Facilitated inclusive learning environment | 4.60 | 4.54 |
| Came to class prepared to teach | 4.20 | 4.58 |
| Used class time effectively | 3.80 | 4.42 |
The lower scores on preparation and time use reflect the mid-semester transition from slides to board work — a change students explicitly requested and that I implemented in real time. The trade-off was intentional: responsiveness to student feedback sometimes means imperfect polish in the moment. I am still refining this balance.
Working Paper
Drummond, P.A.; Maass, K.L. “Active Learning Experiences: Teaching Fellowship Experience in IE.” (Working paper — narrative analysis of the Teaching Fellowship model as an instructor development framework)