Dr. Bryan Brown

Professor

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Biography

Bryan Brown is the Kamalachari Professor of Science Education at the Graduate School of Education at Stanford University. His research explores the relationship between student identity, discourse, classroom culture, and academic achievement in science education. He focuses on the social connotations and cultural politics of science discourse in both small-group and whole-group interactions. Additionally, his work examines how teacher-student discourse influences learning opportunities in science classrooms, particularly in urban communities. Brown’s research is dedicated to developing collaborative curricular cycles and pedagogical practices that enhance discourse-intensive instruction for urban learners. His recent studies investigate how classroom and school culture impacts access to higher education, conducting mixed-methodological research that explores the effects of race, language, and culture on students' learning experiences in urban science education settings.

Research Interests

Experience

Kamalachari Professor

— Present

Graduate School of Education, Stanford University • Stanford, CA

Professor in Science Education

Professor

— Present

Graduate School of Education, Stanford University • Stanford, CA

Professor in Science Education

Associate Professor

— Present

Graduate School of Education, Stanford University • Stanford, CA

Associate Professor in Science Education

Courses

EDUC 267B EDUC 359B EDUC 480 EDUC 180 EDUC 490 EDUC 190 EDUC 140 EDUC 185 EDUC 470 EDUC 380 EDUC 267A EDUC 359C

Requirements for Stanford University

Doctorate Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:26
Reading
Required:26
Writing
Required:26
Speaking
Required:26
Total
Required:100
GRE General
Verbal
Required:160
Quantitative
Required:165
Analytical Writing
Required:4.5
Overall
Required:4.5
Prerequisites
Bachelor degree from an accredited institution Strong background in mathematics and programming
Application Checklist
  • Statement of Purpose
  • Three letters of recommendation
  • Official transcripts
  • Resume/CV
Specialization Notes

The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.