THE GRADUATE SCHOOL
The Joint PhD Program in Computer Science and Learning Sciences builds on enduring and growing connections between research on learning and computation. Rapid technological advances continue to create new and exciting ways to both understand and support learning in all settings and in all stages of life. This program is intended for students with an interest in both fields who would otherwise be forced to choose one area or the other.
Areas of Interest
The possible areas of study are broad and draw from the diverse expertise of affiliated faculty. However, all research must have clear relevance to both Computer Science and Learning Sciences. Example areas of interest include educational data mining; computational modeling as a means to understand complex scientific phenomena; adaptive technology for learning; equity issues in computing; intelligent tutoring systems; and interaction design to support learning.
Additional resources:
- Department website
- Program handbook(s)
Program Statistics
Visit PhD Program Statistics for statistics such as program admissions, enrollment, student demographics and more.
Program Contact
Contact Megan Redfearn
Director, Faculty Support and Doctoral Student Affairs
847-467-6519
Degree Requirements
The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.
Course Requirements
Students are expected to take courses during the first two years of their graduate career. Every student is required to take courses that fulfill specific requirements for breadth and depth in computer science and learning sciences. Students are also expected to take coursework and continue reading beyond these specific requirements. In particular, students should take coursework that is relevant to their research.
Learning Sciences Foundational Courses (4 courses)
Course List | Course | Title |
|---|
| LRN_SCI 401-0 | Knowledge Representation for the Learning Sciences |
| LRN_SCI 402-0 | Social Dimensions of Teaching & Learning |
| LRN_SCI 403-0 | Foundations of the Learning Science |
| LRN_SCI 426-0 | Design of Technological Tools for Thinking and Learning |
Learning Sciences Approved Methods Courses (choose 3 courses)
Course List | Course | Title |
|---|
| LRN_SCI 404-0 | Methods and Epistemologies for the Study of Learning 1 |
| LRN_SCI 405-1 | Methods and Epistemologies for the Study of Learning II |
| LRN_SCI 410-0 | Quantitative Methods I: Probability and Statistics |
| LRN_SCI 411-0 | Quantitative Methods II: Regression Analysis |
| LRN_SCI 415-0 | Field Methods |
| LRN_SCI 416-0 | Advanced Qualitative Methods |
| LRN_SCI 451-0 | Topics in Learning Sciences (Discourse Analysis) |
| LRN_SCI 451-0 | Topics in Learning Sciences (Interaction Analysis) |
| COMP_SCI 472-0/LRN_SCI 451-0 | Designing and Constructing Models with Multi-Agent Languages |
Computer Science Foundational Courses (at least 5 courses)
Students will declare a Computer Science doctoral degree track (e.g., Graphics and Interactive Media or AI/ML) as outlined in the Computer Science graduate study manual (section 4). Students should take at least 5 courses in CS that are approved for graduate credit (all 300 and 400-level courses). Students should consult the qualifying procedures for their track to ensure they have the necessary background. In general, we require a breadth of experience in all of the following areas:
- Programming (comparable to CS 111+211+214)
- Human Computer Interaction
- AI, Machine Learning, or Cognitive Systems
- Systems (1 of the following)
- Operating systems
- Databases
- Computer architecture
- Networking
- Programming languages
- Computer Graphics
- Fundamental algorithms
- Computing and complexity theory
We accept both Northwestern courses and prior coursework at other institutions to satisfy these requirements.
Breadth Courses (3 courses)
Three additional courses are required within years 2 and 3. Any non-required, graduate-level course in any school or department can be used to fulfill the breadth requirement.
Responsible Conduct of Research Training
Students should complete the McCormick Responsible Conduct of Research training course: GEN_ENG 519.
Other Degree Requirements
- Second-year qualifying exams
- Second-year independent research project
- PhD Prospectus
- PhD Dissertation
Last Updated: September 12, 2023
