Graduate Module — Research Methods in Procurement & Capture (GC 530)
The session-by-session teaching plan for GC 530. Follows the module contract in modules/module-template.md, extended to the 14-week graduate arc. Statistics are taught from the ground up but at graduate pace; the course is a cumulative research journal that becomes the thesis/capstone proposal.
Audience: graduate students in the MS program. Prerequisites: program foundations (GB 510 for students who need a statistics refresher). Readings: the doctrine and literacy folders, plus the course reader. Data: the public record (award data, registries, forecasts).
Session 1 — The research–practice loop
Learning objectives. By the end of this session, students can: (1) explain why capture professionals need research; (2) distinguish folklore from testable claims; (3) turn a folklore claim into a researchable question.
Session plan (75 min).
- Open (5 min): "Name a claim the discipline makes that has never been tested."
- Teach (25 min): doctrine/03 + doctrine/07. The learning loop; folklore vs. evidence; the research-practice gap.
- Apply (25 min): write three folklore claims from the discipline and turn each into a researchable question.
- Discuss (15 min): "Why does the discipline run on so much folklore — and what would change if it did not?"
- Close (5 min): assignment.
Discussion prompts. 1. Which folklore claim would you most like to test, and why? 2. What would the discipline look like with a working research base?
Homework / reading. Read doctrine/03 and doctrine/07. Deliverable: three researchable questions from folklore claims.
Comprehension check. What is the research-practice loop? What makes a claim researchable?
Session 2 — Research design
Learning objectives. By the end of this session, students can: (1) distinguish descriptive, causal, and predictive designs; (2) state a hypothesis; (3) identify confounds.
Session plan (75 min).
- Open (5 min): "What is the difference between 'what happened' and 'what caused it'?"
- Teach (25 min): the course reader on research design + doctrine/05. Descriptive, causal, predictive; the counterfactual; confounds.
- Apply (25 min): for one folklore claim, state the design that would test it and what would count as evidence.
- Discuss (15 min): "Why is causal language so common in a discipline that so rarely runs experiments?"
- Close (5 min): assignment.
Discussion prompts. 1. When is a descriptive study the right design? 2. What would a causal study of pWin require?
Homework / reading. Read the course reader and doctrine/05. Deliverable: a design memo for one testable claim.
Comprehension check. What are the three research designs? What is a confound?
Session 3 — Measurement
Learning objectives. By the end of this session, students can: (1) move from concept to variable to measure; (2) state validity threats; (3) state reliability concerns.
Session plan (75 min).
- Open (5 min): "What is 'capture readiness,' exactly?"
- Teach (25 min): the course reader on measurement + doctrine/05. Concepts, variables, measures; validity and reliability.
- Apply (25 min): operationalize "capture readiness" and "price competitiveness" into measurable variables; state the validity threats.
- Discuss (15 min): "Which of the discipline's key concepts is hardest to measure — and what do we do about it?"
- Close (5 min): assignment.
Discussion prompts. 1. What does a measure gain and lose when it is operationalized? 2. How do you know you are measuring the thing, not a proxy?
Homework / reading. Read the course reader. Deliverable: an operationalization exercise with validity threats.
Comprehension check. What is operationalization? What is the difference between validity and reliability?
Session 4 — The public data substrate
Learning objectives. By the end of this session, students can: (1) enumerate the public data sources; (2) state their strengths and gaps; (3) match data to a research question.
Session plan (75 min).
- Open (5 min): "What can the public record actually tell us?"
- Teach (25 min): literacy/where-the-money-flows + the course reader on procurement data. Award data, forecasts, registries, debriefs, bid protests.
- Apply (25 min): for a research question, identify the public data that would answer it and what it cannot tell you.
- Discuss (15 min): "What is the biggest gap in the public record — and how do researchers work around it?"
- Close (5 min): assignment.
Discussion prompts. 1. What biases lurk in award data? 2. When is the public record enough, and when is it not?
Homework / reading. Read literacy/where-the-money-flows. Deliverable: a data memo mapping a research question to public sources and their limits.
Comprehension check. What are the public data sources? What can they not tell you?
Session 5 — Descriptive statistics
Learning objectives. By the end of this session, students can: (1) describe a distribution; (2) compute central tendency and spread; (3) describe before explaining.
Session plan (75 min).
- Open (5 min): "What does the distribution of award values in a market look like?"
- Teach (25 min): the course reader on statistics. Distributions, mean, median, spread, shape.
- Apply (25 min): describe the distribution of award values in a real segment; state what is typical and what is exceptional.
- Discuss (15 min): "Why describe before explain? What does a distribution reveal that an average hides?"
- Close (5 min): assignment.
Discussion prompts. 1. When is the median a better summary than the mean? 2. What does a skewed award distribution tell a competitor?
Homework / reading. Read the course reader. Deliverable: a descriptive analysis of a real market segment.
Comprehension check. What is a distribution? Why describe before explain?
Session 6 — Sampling and inference
Learning objectives. By the end of this session, students can: (1) define a population and a sample; (2) identify sampling bias; (3) state what a sample can and cannot support.
Session plan (75 min).
- Open (5 min): "You have 200 of 2,000 awards. What can you conclude?"
- Teach (25 min): the course reader on inference. Samples, populations, bias, confidence.
- Apply (25 min): for a research question, define the population, a defensible sample, and the lurking biases.
- Discuss (15 min): "What is the most common sampling bias in procurement research?"
- Close (5 min): assignment.
Discussion prompts. 1. Why does a convenience sample of visible awards mislead? 2. What does "confidence" actually mean?
Homework / reading. Read the course reader. Deliverable: a sampling memo for a research question.
Comprehension check. What is sampling bias? What does a sample support?
Session 7 — Hypothesis testing
Learning objectives. By the end of this session, students can: (1) state a null and alternative; (2) run a simple test; (3) distinguish statistical from practical significance.
Session plan (75 min).
- Open (5 min): "Do HUBZone set-asides differ in average award size? How would you know?"
- Teach (25 min): the course reader on hypothesis testing. Null, alternative, significance, the logic of the test.
- Apply (25 min): test a simple hypothesis about a public award dataset.
- Discuss (15 min): "When is a statistically significant result practically meaningless?"
- Close (5 min): assignment.
Discussion prompts. 1. What does a p-value actually tell you? 2. How big a difference matters in capture, not just in statistics?
Homework / reading. Read the course reader. Deliverable: a hypothesis test on a public dataset.
Comprehension check. What is a null hypothesis? What is the difference between statistical and practical significance?
Session 8 — Correlation and regression
Learning objectives. By the end of this session, students can: (1) read a correlation honestly; (2) interpret a simple regression; (3) state three confounds an analysis cannot rule out.
Session plan (75 min).
- Open (5 min): "Awards correlate with past performance. So what?"
- Teach (25 min): the course reader on regression. Association vs. causation; the coefficient; the confounds.
- Apply (25 min): estimate a simple relationship in public data and name the confounds.
- Discuss (15 min): "Why is 'correlation is not causation' the most important sentence in this course?"
- Close (5 min): assignment.
Discussion prompts. 1. What confounds the past-performance → win relationship? 2. When can a regression support a causal claim?
Homework / reading. Read the course reader. Deliverable: a regression exercise with a confound list.
Comprehension check. What is the difference between association and causation? What is a confound?
Session 9 — Midterm
Learning objectives. By the end of this session, students demonstrate: (1) design critique; (2) measurement discipline; (3) inference honesty.
Session plan (75 min).
- Open (5 min): exam logistics.
- Exam (65 min): a published procurement study is distributed. Students critique its design, measurement, and inference, and redesign the weak link.
- Close (5 min): what to review for the second half.
Discussion prompts. n/a (examination).
Homework / reading. Review weeks 1–8. Deliverable: midterm submission.
Comprehension check. n/a.
Session 10 — Qualitative methods
Learning objectives. By the end of this session, students can: (1) design a small case study; (2) write a document-analysis protocol; (3) state when qualitative work is the right method.
Session plan (75 min).
- Open (5 min): "When do the numbers not carry the question?"
- Teach (25 min): the course reader on qualitative methods. Case study, document analysis, interviews; the transparent protocol.
- Apply (25 min): design a small case study (e.g., of an incumbent displacement play) with a transparent evidence protocol.
- Discuss (15 min): "What does a qualitative study gain and lose compared to a quantitative one?"
- Close (5 min): assignment.
Discussion prompts. 1. When is a single case the right design? 2. How do you keep a qualitative study honest?
Homework / reading. Read the course reader. Deliverable: a qualitative study design with an evidence protocol.
Comprehension check. When is a case study the right method? What makes qualitative work disciplined?
Session 11 — Mixed methods
Learning objectives. By the end of this session, students can: (1) combine quantitative and qualitative evidence; (2) use triangulation; (3) design a mixed study.
Session plan (75 min).
- Open (5 min): "One study with numbers and two cases. What does the combination buy you?"
- Teach (25 min): the course reader on mixed methods. Triangulation; when the methods reinforce and when they conflict.
- Apply (25 min): sketch a mixed design that combines award data with two qualitative cases to answer a research question.
- Discuss (15 min): "What do you do when the numbers and the cases disagree?"
- Close (5 min): assignment.
Discussion prompts. 1. What does triangulation actually confirm? 2. When do conflicting methods teach you the most?
Homework / reading. Read the course reader. Deliverable: a mixed-design sketch.
Comprehension check. What is triangulation? What do mixed methods buy you?
Session 12 — Research ethics
Learning objectives. By the end of this session, students can: (1) state the ethics of procurement research; (2) draw the wall between research and espionage; (3) write the data boundaries of a study.
Session plan (75 min).
- Open (5 min): "Your employer has proprietary win data. Can you publish a study from it?"
- Teach (25 min): doctrine/04 + the course reader on research ethics. Public data, employer data, competitor data; the researcher's obligation to the truth.
- Apply (25 min): write the ethical boundaries of your proposed study — what data you will use, what you will not, and why.
- Discuss (15 min): "Where is the line between research and espionage in this discipline?"
- Close (5 min): assignment.
Discussion prompts. 1. What data should a procurement researcher never touch? 2. How does the public-record discipline make research cleaner?
Homework / reading. Read doctrine/04. Deliverable: an ethics memo for your proposed study.
Comprehension check. What are the ethics of procurement research? Where is the wall between research and espionage?
Session 13 — Writing the research proposal
Learning objectives. By the end of this session, students can: (1) write a research proposal; (2) argue for a design; (3) state limitations.
Session plan (75 min).
- Open (5 min): "Write the proposal a skeptical reviewer would fund."
- Teach (25 min): the course reader on proposal writing. Question, design, data, analysis, ethics, limitations.
- Apply (25 min): workshop drafts — the room attacks the design.
- Discuss (15 min): "What makes a research proposal fundable?"
- Close (5 min): assignment.
Discussion prompts. 1. What is the weakest part of most proposals — question, design, or data? 2. How do you write limitations without undermining your own study?
Homework / reading. Read the course reader. Deliverable: the full research proposal draft.
Comprehension check. What are the parts of a research proposal? Why must limitations be explicit?
Session 14 — The proposal defense
Learning objectives. By the end of this session, students can: (1) present a research proposal; (2) defend it before a panel; (3) revise from feedback.
Session plan (75 min).
- Open (5 min): defense logistics.
- Defenses (50 min): each student presents their proposal; the panel and peers probe.
- Discuss (15 min): "What did the strongest proposals share?"
- Close (5 min): bridge to GC 690/690T and the doctorate.
Discussion prompts. 1. What made a proposal survive the panel? 2. What would you change in your own design after hearing the others?
Homework / reading. Course synthesis. Deliverable: final research proposal, revised after defense.
Comprehension check. What does a defensible research proposal look like? What is the bridge to the capstone and thesis?