The Education domain emphasis introduces students to foundational paradigms of research in the educational sciences. The role of theory, AI, and other technologies in the growing landscape of digital pedagogy, measurement, and curricular development will be explored. The DE provides an opportunity for students to augment their skillset with analysis methodologies adapted to the precepts and values of the field of education.

From the lists shown below, students will select one course from the lower-division, and two courses from the upper-division. The lower division course is a required element of the Domain Emphasis.

Prerequisites are shown within square brackets.

Lower Division (select one)

  • EDUC 40AC. From Macro to Micro: Experiencing Education (In)equality in and beyond Schools (4 units)
  • **EDUC W161. Digital Learning Environments (3 units)

Upper Division (select two)

  • COMPSCI 194. STAR Assessments for Proficiency-Based Learning - approved only when offered with this topic
  • DATA 144. Data Mining and Analytics (3 units) [Corequisite: Data C100]
  • EDUC/EDSTEM C122. Research Methods for Science and Mathematics K-12 Teachers (3 units) [Prerequisite: UGIS 82]
  • EDUC 130. Knowing and Learning in Mathematics and Science (3 units) [Prerequisite: UGIS 81A or 81B or 82]
  • EDUC C142/GLOBAL C129. Education in a Global World (4 units)
  • EDUC W153. Research in Education: Studying Educational Inequality and Possibility (4 units)
  • **EDUC W161. Digital Learning Environments (3 units)
  • EDUC 168. Educational Testing in the USA: Issues and Practical Experiences (3 units)
  • EDUC 170. K12 Computer and Data Science Education: Design, Research, and Evaluation (3 units)
  • SOCIOL 113 or 113AC. Sociology of Education (4 units) [Prerequisite: Sociol 1 or 3 or 3AC]
  • SOCIOL 180E. Comparative Perspectives on U.S. and European Societies: Education (4 units) [Prerequisite: Sociol 1 or 3 or 3AC]

The following graduate classes can also count toward the Education domain emphasis. Interested students should email the course instructor directly to request permission to enroll:

  • EDUC 260. Machine Learning in Education (3 units)
  • EDUC 261C. Causal Inference in Policy and Education Research (3 units)
  • EDUC 274A. Measurement in Education and the Social Sciences I (4 units)
  • EDUC 274B. Measurement in Education and the Social Sciences II (4 units) [Prerequisite: Educ 274A]
  • EDUC 275B. Data Analysis in Education Research II (4 units) [Prerequisite: Educ 293A and 293L or equivalent]
  • EDUC 275G. Hierarchical and Longitudinal Modeling (5 units) [Prerequisite: linear and logistic regression, Educ 275B or equivalent]
  • EDUC 276A. Introduction to Program Evaluation (3 units)
  • EDUC 293A. Data Analysis in Education Research (4 units)

**Education W161 may count toward the lower-division or upper-division requirement, but not both. Students may fulfill this domain emphasis by completing Education W161 plus two additional upper-division courses from the list, without taking a lower-division course.

Unit values and prerequisites are subject to change. Please refer to guide.berkeley.edu for the most up-to-date course information.