Contact Us
For more information about the Advance Research Methods—Causal Inference in Education certificate program, contact us at ProfessionalLearning@gse.upenn.edu
Estimating the effects of educational interventions and policies requires special analytic techniques. Advance your research skills by exploring approaches to causal inference related to improving educational outcomes.
Penn GSE has a rich history of preparing individuals in quantitative methods, intervention implementation, program evaluation, and policy analysis. Undergirding these areas is the notion of causal inference—that is, can we determine if a program, policy, or intervention is affecting student outcomes?
What Sets Us Apart
Engage in live virtual sessions with thought leaders from the Penn community
Cohort-based model focused on global networks and opportunities for connection
An accelerated course of study
About the Program
The Penn GSE Causal Inference in Education Certificate Program offers a sustained, deep, and rigorous learning opportunity for those engaged in intervention or data analysis work. Participants dive deep into learning about causal inference in the context of experiments and interventions, causal inference in education, and the complexities of the practice of causal inference.
Application deadline
- Priority Application Deadline: December 1, 2023
- Application Deadline: January 15, 2024
Program length
February 2024 – July 2024
Certificate Offered
Penn GSE Certificate in Causal Inference in Education
Cost
- Priority deadline rate: $4,500
- Standard rate: $6,500
Ideal Candidate
- Education Analysts/Researchers
- Policymakers
- Consultants
- Pre-doctoral studies applicants
Prerequisites
Introductory statistics/quant research courses
Modality
- Online
Overview
The program is an intensive, accelerated, 6-month certificate program that explores causal inference as it relates to improving educational outcomes.
This program is designed for policymakers, practitioners, government employees, those from private firms, workers from NGOs, and those interested in preparing for doctoral study in policy, quantitative methods, and evaluation from across the globe.
This program consists of 10 live virtual sessions that are organized in three main modules. Led by experts from the Penn GSE, this cohort-based program considers what causal inference is, causal inference in the context of experiments and interventions, causal inference in the context of education without researcher or natural experiments, and the key complexities of the practice of causal inference.
Program Schedule
Session Topic | Faculty Lead |
Session 1: What is Causal Inference | Dr. Michael Gotfried |
Session 2: Investigator-Initiated Experiments | Dr. Sharon Wolf |
Session 3: Causal Inference in Natural Experiments: Difference-in-Difference Designs | Dr. Rachel Baker |
Session 4: Causal Inference Addressing Self Selection | Dr. Wendy Chan |
Session 5: Causal Inference in Cutoff Experiments: Regression Discontinuity | Dr. Rachel Baker |
Session 6: Causal Inference in the Absence of Research or Natural Experiments, Part 1 | Dr. Michael Gottfried |
Session 7: Causal Inference in the Absence of Research or Natural Experiments, Part 2 | Dr. Michael Gottfried |
Session 8: Visualization | Dr. Sade Bonilla |
Session 9: Examining Cost-Effectiveness | Dr. Brooks Bowden |
Session 10: The Role of Politics and Policymaking in Implementation | Dr. Ericka Weathers |
Our Faculty
Program Leadership
Dr. Michael Gottfried
Academic Director, Professor, Penn Graduate School of Education