About the Program
The Graduate Group in Science and Mathematics Education (known informally as SESAME) offers an interdisciplinary graduate program leading to a doctoral degree in science, mathematics, technology, and engineering education. The program is designed to give graduates advanced expertise in a STEM discipline as well as in educational theory and research methodologies.
This Graduate Group was established so individuals with training or experience in a mathematical, scientific, or technical discipline can pursue advanced studies focused on educational issues in these disciplines. SESAME produces scholars who can communicate effectively with scientists, mathematicians, and engineers as well as with educational researchers and practitioners. SESAME students are expected to attain a level of expertise equivalent to that of a Master's student in their chosen discipline.
Thesis work typically consists of basic research on learning or cognition in a STEM field or the development of improved pedagogical approaches based on relevant models and research. Upon satisfactory completion of their studies and thesis work, students will obtain the degree of Ph.D. in Science and Mathematics Education.
Admission to the University
Minimum Requirements for Admission
The following minimum requirements apply to all graduate programs and will be verified by the Graduate Division:
- A bachelor’s degree or recognized equivalent from an accredited institution;
- A grade point average of B or better (3.0);
- If the applicant has completed a basic degree from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, or an IELTS Band score of at least 7 on a 9-point scale (note that individual programs may set higher levels for any of these); and
- Sufficient undergraduate training to do graduate work in the given field.
Applicants Who Already Hold a Graduate Degree
The Graduate Council views academic degrees not as vocational training certificates, but as evidence of broad training in research methods, independent study, and articulation of learning. Therefore, applicants who already have academic graduate degrees should be able to pursue new subject matter at an advanced level without the need to enroll in a related or similar graduate program.
Programs may consider students for an additional academic master’s or professional master’s degree only if the additional degree is in a distinctly different field.
Applicants admitted to a doctoral program that requires a master’s degree to be earned at Berkeley as a prerequisite (even though the applicant already has a master’s degree from another institution in the same or a closely allied field of study) will be permitted to undertake the second master’s degree, despite the overlap in field.
The Graduate Division will admit students for a second doctoral degree only if they meet the following guidelines:
- Applicants with doctoral degrees may be admitted for an additional doctoral degree only if that degree program is in a general area of knowledge distinctly different from the field in which they earned their original degree. For example, a physics PhD could be admitted to a doctoral degree program in music or history; however, a student with a doctoral degree in mathematics would not be permitted to add a PhD in statistics.
- Applicants who hold the PhD degree may be admitted to a professional doctorate or professional master’s degree program if there is no duplication of training involved.
Applicants may apply only to one single degree program or one concurrent degree program per admission cycle.
Required Documents for Applications
- Transcripts: Applicants may upload unofficial transcripts with your application for the departmental initial review. Unofficial transcripts must contain specific information including the name of the applicant, name of the school, all courses, grades, units, & degree conferral (if applicable).
- Letters of recommendation: Applicants may request online letters of recommendation through the online application system. Hard copies of recommendation letters must be sent directly to the program, by the recommender, not the Graduate Admissions.
Evidence of English language proficiency: All applicants who have completed a basic degree from a country or political entity in which the official language is not English are required to submit official evidence of English language proficiency. This applies to institutions from Bangladesh, Burma, Nepal, India, Pakistan, Latin America, the Middle East, the People’s Republic of China, Taiwan, Japan, Korea, Southeast Asia, most European countries, and Quebec (Canada). However, applicants who, at the time of application, have already completed at least one year of full-time academic course work with grades of B or better at a US university may submit an official transcript from the US university to fulfill this requirement. The following courses will not fulfill this requirement:
courses in English as a Second Language,
courses conducted in a language other than English,
courses that will be completed after the application is submitted, and
courses of a non-academic nature.
Applicants who have previously applied to Berkeley must also submit new test scores that meet the current minimum requirement from one of the standardized tests. Official TOEFL score reports must be sent directly from Educational Test Services (ETS). The institution code for Berkeley is 4833 for Graduate Organizations. Official IELTS score reports must be sent electronically from the testing center to University of California, Berkeley, Graduate Division, Sproul Hall, Rm 318 MC 5900, Berkeley, CA 94720. TOEFL and IELTS score reports are only valid for two years prior to beginning the graduate program at UC Berkeley. Note: score reports can not expire before the month of June.
Where to Apply
Visit the Berkeley Graduate Division application page.
Admission to the Program
- A bachelor’s degree or its recognized equivalent from an accredited institution;
- Superior scholastic record, normally well above a 3.0 GPA;
- Indication of appropriate research goals, described in the statement of purpose; and
- For international applicants whose academic work has been in a language other than English, the Test of English as a Foreign Language (TOEFL).
SESAME accepts three to six Ph.D. students each year from more than 50 applications. Applicants are judged on a number of factors; good scores and a high GPA are necessary but not sufficient. Particularly valued are potential as a researcher and educator, a strong background in a STEM discipline, and an agenda that fits well with the work of specific faculty in this small, interdisciplinary program. Applicants should clearly indicate in their statement of purpose which faculty member(s) they are interested in doing research with and why.
Experience teaching, developing instructional materials, or doing educational or psychological research in these areas will also be favorably considered. Knowledge of psychology, cognitive science, education, or statistics is helpful but not required. See SESAME Admissions for more information. SESAME accepts applications for only the Fall semester.
Statement of Purpose and Personal History
The statement of purpose and personal history are two separate essays.
The statement of purpose should succinctly explain your reasons for applying to SESAME, briefly review our relevant academic preparation and work experience, and describe your future academic or professional goals once the degree is acquired. The focus should be on your preparation, experience, and aims rather than a discussion of the trends or importance of education in general. The most successful statements are one to two pages in length and focus on the strengths and experiences of the applicant, providing the reviewers with evidence and justification for admitting those applicants who are qualified and well-suited for SESAME.
The personal history should include any relevant information not already included in the statement of purpose. Additional suggestions may be found in the Graduate Division’s Personal Statement Guide. There is no minimum length for the personal history.
These two essays are used in part to evaluate the candidate’s writing skills. Pursuant to UC Berkeley Policy, the two statements must be written by the candidate.
Three Letters of Recommendation
Ph.D. applicants should provide at least three and no more than five letters that speak directly to their ability and potential to perform academic work at the doctoral level.
Doctoral Degree Requirements
SESAME is programmatically separate from the GSE so GSE-wide course requirements do not apply. Note, however, that the Graduate Division’s requirement of EDUC 375 still applies.
A. Two SESAME Core Courses Taken in Year 1
|SCMATHE 210||Practicum in Science and Math Education Research and Development||4 Units in Fall and 2 Units in Spring|
|SCMATHE 292||Research Seminar and Colloquium (Fall and Spring)||1|
B. Two Foundations Courses Beginning in Year 1
|EDUC 203||Cultivating Cognitive Development: From Sensorimotor Intelligence to Embodied STEM Concepts (Spring)||3|
|EDUC 254||Introduction to Cultural Historical Activity Theory (Spring)||3|
C. Three Methodology Courses (1 Quant, 1 Qual + 1 More) Taken at Any Time
|EDUC 222C||Design-Based Research Forum||3|
|EDUC 241C||Narrative across Learning Contexts||3|
|EDUC 241D||Perspectives on Classroom Discourse||3|
|EDUC 243||Advanced Qualitative Methods||3|
|EDUC 244||Data Mining and Analytics||3|
|EDUC 250A||Qualitative Research in Language/Literacy Education||3|
|EDUC 250C||Discourse Analysis||3|
|EDUC 252B||Ethnographic Methods in the Study of Language and Literacy in Traditional and Digital Environment||3|
|EDUC 259||(co)Participant Observation Research in the Field||4|
|EDUC C260F||Machine Learning in Education||3|
|EDUC 271B||Introduction to Qualitative Research Methods||3|
|EDUC 274A||Measurement in Education and the Social Sciences I||4|
|EDUC 274B||Measurement in Education and the Social Sciences II||4|
|EDUC 274D||Multidimensional Measurement||4|
& EDUC 275L
|Data Analysis in Educational Research II|
and Educational Data Analysis Laboratory II
|EDUC 275G||Hierarchical and Longitudinal Modeling||3|
|EDUC 276A||Introduction to Program Evaluation||3|
|EDUC 280C||Research Apprenticeship and Qualitative Methodology Seminar I||3|
& EDUC 293L
|Data Analysis in Education Research|
and Educational Data Analysis Laboratory
|SCMATHE 220C||Instructional Design in Science and Mathematics Education||3|
D. One Learning in the Discipline Course Taken at Any Time
Below are examples of courses that represent this area but this list is not exhaustive. Students are encouraged to look at courses offered each term, to consult with their advisor, and to explore graduate coursework on campus more broadly.
|EDUC 222C||Design-Based Research Forum (Fall)||3|
|EDUC 224A||Mathematical Thinking and Problem Solving (Fall)||3|
|EDUC 282||Introduction to Disciplined Inquiry (Fall)||3|
|SCMATHE 220C||Instructional Design in Science and Mathematics Education (Spring, odd years. May satisfy the E requirement below.)||3|
E. Required: One Curriculum and Technology Design Course Taken at Any Time
Below are examples of courses that represent this area but this list is not exhaustive. You are encouraged to look at courses offered each term, to consult with your advisor, and to explore graduate coursework on campus more broadly - e.g., the School of Information.
|EDUC 222||Politics and Pedagogies at the Intersections of Data, Technologies, and Inequalities||3|
|EDUC 224C||Gender, Mathematics and Science||3|
|EDUC 224A||Mathematical Thinking and Problem Solving||3|
|EDUC 170||K12 Computer and Data Science Education: Design, Research, and Evaluation||3|
|EDUC 244||Data Mining and Analytics||3|
|EDUC/INFO C260F||Machine Learning in Education||3|
F. Two STEM Disciplinary Courses in the Student’s Field of Emphasis
Reflecting the range of STEM disciplinary fields and your interests, these two courses should be selected in consultation with your faculty advisor and with an eye toward your professional development.
G. Participation in a Research Group (At Least Four Semesters)
Many faculty in the GSE have one or multiple research groups that run yearlong. SESAME students typically enroll in a research group led by their advisor. However, you are encouraged to participate in multiple research groups if it will further enhance your growth. Below is a list of Learning Sciences and Human Development research groups to consider.
|EDUC 209||Academic Writing Support Group||2|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Embodied Design Research Lab)||2-6|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Embodied Underground)||2-6|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Technology Enhanced Learning in Science)||2-6|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Leveraging Learning Technologies)||2-6|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Functions in Research)||2-6|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Teaching for Robust Understanding)||2-6|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Designing for Joy and Justice in Education)||2-6|
|EDUC 223B||Special Problems in Mathematics, Science and Technology Education (Computational Representations in Education (CoRE))||2-6|
|EDUC 298C||Group Studies, Seminars, or Group Research--DCEMST||1-4|
|EDUC 290A||Special Topics Seminars: Policy, Organization, Measurement, and Evaluation||1-4|
Learning Sciences Certificate
- Design courses for undergraduates and graduate students
- Use learning sciences research in design, implementation, and assessment of educational programs
- Use and refine learning technologies, including online courses, learning management systems, interactive models and simulations, and educational games
- Succeed in K-12 settings; undergraduate, graduate, and research institutions; out-of-school settings; non-profits, education startups, and industries that develop technical training and novel approaches to learning
- Meet the needs of students with varied cultural, educational, and personal experiences, including emergent bilinguals, underrepresented minorities, and students new to technology.
Faculty and Instructors
* Indicates this faculty member is the recipient of the Distinguished Teaching Award.
Dor Abrahamson, Professor, Graduate School of Education. Mathematics cognition through the lenses of design-based frameworks.
Alice M. Agogino, Professor, Mechanical Engineering. Intelligent learning systems, information retrieval and data mining, multiobjective and strategic product design, nonlinear optimization, probabilistic modeling, intelligent control and manufacturing, sensor validation, fusion and diagnostics, wireless sensor networks, multimedia and computer-aided design, design databases, design theory and methods, MEMS Synthesis and CAD, artificial intelligence and decision and expert systems, gender equity .
Anne M. Baranger, Associate Teaching Professor, Adjunct Professor, College of Chemistry. The overall goal of our research is to develop evidence-based educational practices that teach rigorous chemical content and authentic scientific practices and make undergraduates education more accessible, more enjoyable, and more relatable .
Kris Gutierrez, Professor, Graduate School of Education. Designed learning environments, Cultural dimensions of learning, language and literacy learning for dual language learners, biliteracy, and new media literacies, the social organization of learning, ethnographic methodology and qualitative approaches to inquiry, design experiment/social design experiments, education of Latino, immigrant, and migrant youth, urban education, teacher learning, educational and language policy.
Marcia C. Linn, Professor, Graduate School of Education (SESAME Chair). Cognitive processes, science, computer instruction.
Zachary A. Pardos, Associate Professor, Graduate School of Education. Formative assessment in virtual learning environments, educational data mining.
Thomas M. Philip, Professor, Graduate School of Education. Teacher Education , Learning as Political & Ethical .
Michael Andrew Ranney, Professor, Graduate School of Education. Reasoning, learning, cognitive science and society.
Alan H. Schoenfeld, Professor, Graduate School of Education and Department of Mathematics. Problem solving, metacognition, mathematical cognition.
Tesha Sengupta-Irving, Assistant Professor, Graduate School of Education. STEM Teaching and Learning, Inequality and Resistance, Politics, Ethics, and Emotions, Agency and Identity, Ethnographic Case Study & Design-Based Research.
* Angelica M. Stacy, Professor, College of Chemistry. Chemistry education.
Michelle H. Wilkerson, Assistant Professor, Graduate School of Education. After-school Programs, Computer-Mediated Learning, Mathematics Education, Science Education, Simulation Learning Environments, Teacher Education, Technology and Schools, Classroom Learning Environments.
Armando Fox, Professor, Electrical Engineering and Computer Sciences. Programming systems (PS), Education (EDUC), Operating Systems and Networking (OSNT).
Robert J. Full, Professor, Integrative Biology.
Dan Garcia, Teaching Professor, Electrical Engineering and Computer Sciences.
David Romps, Professor Earth and Planetary Sciences. Atmospheric dynamics, moist convection and turbulence, and the interaction of clouds with Earth's climate.
Lloyd Goldwasser, Lecturer, Graduate School of Education.
Andrea A. diSessa, Professor, Graduate School of Education. Computer-Mediated Learning, Curriculum Development, Educational Media, Information Technology, Learning, Science Education, Simulation Learning Environments.
Bernard R. Gifford, Professor, Graduate School of Education. Assessment and Educational Measurement, Computer-Mediated Learning, Curriculum Development, Development of Professional Learning Communities, Educational Equity, Experimental Design In Education, High School Reform, Information Technology, Leadership, Mathematics Education, Minorities, Policy Analysis and Evaluation, Politics of School Structure and Governance, Professional Development for Educators, Reform Issues, School Data Analysis, School-University Collaboration, Science Education, Superintendency, Technology and Schools, Testing, Urban Leadership.