Critical Analysis of Quantitative Data Institute 2010

July 13-15, 2010

 Critical Analysis of Quantitative Data Institute Registration.

Location: UCLA Campus

Email: rnjohnson@ucla.edu for more information

Institute Director
Sylvia Hurtado
Higher Education Research Institute
University of California, Los Angeles

The ASHE Institute, research methods for the critical analysis of Data is designed to support individuals engaged in such work, by introducing statistical methods that will enhance critical research. Participants will learn techniques that will help them: Participants will also learn how to frame and design studies that are critical in nature, and support social justice and policy change.

Seminars (Participants select one of the following to attend):

Engaging in Critical Quantitative Research:

This panel will focus on how to conduct quantitative research through a critical lens. Topics to be addressed are: Critical Theories to Support Quantitative Work; Engaging in Work that Confronts Myths and Stereotypes; Choosing Instruments to Support Critical Work; and Engaging in Research that Contributes to Change and Social Justice.

Social Network Theory & Higher Educaton Research:

This is an introductory seminar to social network theory and how it can be applied to study critical and pressing issues in higher education, including college access, persistence, and success; racial diversity; and organizational dynamics. The power of social network theory stems from its difference from traditional studies, which assume that it is the attributes of individual actors (i.e., students and organizations)—whether they are under-represented minorities or public institutions— that matter. Social network theory offers an alternate perspective, where the attributes of individual actors are less important than their relationships and ties with other actors within the network.

Instructors:
Cecilia Rios-Aguilar, University of Arizona
Scott Thomas, Claremont Graduate University

Using Multilevel Modeling to Study How to Narrow the Equity Gap:

This seminar will focus on the use and advantages of applying multilevel modeling techniques to study equity issues where data allow examination of effects within nested contexts (states, institutions, departments). Hierarchical Level Modeling (HLM) software will be used with examples, and in application, to problems participants bring to the course. Data examples will include how higher education policies and resources at the state, institution, or department level influence the “relationship” between college student outcomes and student characteristics such as SES, race/ethnicity, and gender. This approach also allows for the examination of issues related to student outcomes by class, race/ethnicity, and gender.

Instructor:
Marvin Titus, University of Maryland