Graduate Course Catalog
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Note: For descriptions of classes each term, see the LSA Course Guide
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Courses in School of Education
Courses in the School of Education are listed in the Schedule of Classes under the School of Education. The following courses count as LSA courses for LSA degree credit.
Education C – Behavioral Sciences in Education (EDBEHAVR)
EDBEHAVR 800 / PSYCH 861. Proseminar in Education and Psychology
Graduate standing and permission of instructor. (3). May not be repeated for credit.

EDBEHAVR 801 / PSYCH 862. Proseminar in Education and Psychology
Graduate standing and permission of instructor. (3). May not be repeated for credit.

Education D – Curriculum and Instruction (EDCURINS)
EDCURINS 421 / LATIN 421. Teaching of Latin
Junior standing in Latin and permission of instructor. (3; 2 in the half-term). May not be repeated for credit. F, W, Sp.

EDCURINS 431 / GERMAN 531. Teaching Methods
Senior standing; and candidate for a teaching certificate. (2 - 3). May not be repeated for credit. F.

EDCURINS 455 / ROMLING 413 / SPANISH 413. Teaching Spanish/Applications of Linguistics
Nine credits chosen between SPANISH 279 and 399; or two RCLANG 324 and six credits chosen between SPANISH 279 and 399. (Prerequisites enforced at registration.) One of: SPANISH 298, ROMLING 298, LING 210. (3). May not be repeated for credit. F.

Principles of phonological, morphological, syntactic, and semantic analyses applied to the teaching of Spanish.

Education (EDUC)
EDUC 485 / MATH 485. Mathematics for Elementary School Teachers and Supervisors
One year of high school algebra or permission of the instructor. (3). May not be repeated for credit. No credit granted to those who have completed or are enrolled in MATH 385.

The history, development and logical foundations of the real number system and of numeration systems including scales of notation, cardinal numbers and the cardinal concept, the logical structure of arithmetic (field axioms) and their relations to the algorithms of elementary school instruction.

EDUC 580 / ARCH 609 / ENGLISH 528 / KINESLGY 505 / PMR 580 / RACKHAM 580 / SOC 580 / SW 572 / WOMENSTD 590. Topics in Disability Studies
Graduate standing. (1 - 3). May be repeated for a maximum of 9 credits.

An interdisciplinary approach to disability studies, including focus on the arts and humanities, natural and social sciences, and professional schools. Some topics include history and culture representation of disability, advocacy, health, rehabilitation, built environment, independent living, public policy. Team taught with visiting speakers. Accessible classroom with real-time captioning.

EDUC 593 / ELI 593. Educational Linguistics
Graduate standing and permission of instructor. (3). May not be repeated for credit.

This course deals with training and research in linguistics as it relates to education al theory and practice, specifically the teaching and learning of K-12 English as a Second Language (ESL) students. Topics include English structures and analysis, identification of ESL students' learning challenges, and pedagogical strategies to promote language acquisition.

EDUC 764 / POLSCI 734 / PUBPOL 732. Public Policy in Postsecondary Education
Graduate standing. (3). May not be repeated for credit.

EDUC 817 / PSYCH 817 / SOC 810 / STATS 817. Interdisciplinary Seminar in Quantitative Social Science Methodology
Graduate standing, and Graduate-level course in STATS at the level of STAT 500 and 501. (1). May be repeated for a maximum of 6 credits. This course has a grading basis of "S" or "U".

This seminar will meet to consider methodological issues that arise in research in the social sciences. Themes for each meeting will arise from ongoing research projects at the University of Michigan. Visiting researchers will provide a brief account of their aims and data before defining the methodological challenge for which they desire discussion.

EDUC 890 / SURVMETH 790. Multi-level Analysis of Survey Data
At least one graduate-level course in statistics or quantitative methods, and experience with multivariate regresion models, including both analysis of data and interpretation of results. (3). May not be repeated for credit.

In this course, students are introduced to an increasingly common statistical technique, hierarchical linear modeling (HLM). Multi-level methods and the HLM software can be used to analyze nested data and multi-level research questions. Although the course demonstrates multiple uses of the HLM software, including growth-curve modeling, the major focus is on the investigation of organizational effects on individual-level outcomes.

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