Critical Analysis of Quantitative Data Institute 2010July 13-15, 2010 |
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Email: rnjohnson@ucla.edu for more information
DateJuly 13-15, 2010
Location
Los Angeles, CA
Institute Director
Sylvia Hurtado
Higher Education Research Institute
University of California, Los Angeles
About the Institute
More than ever before, scholars are using statistical analyses to reveal educational inequalities and highlight the experiences of diverse student populations. The ASHE Institute on Research Methods for the Critical Analysis of Quantitative 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 1) Identify social and institutional inequities; 2) Understand educational processes and outcomes on a large scale and 3) Improve the utility of national data bases. Participants will also learn how to frame and design studies that are critical in nature, and support social justice and positive change.
In order to fully benefit from the Institute, participants should have a basic knowledge of correlation, regression, and factor analysis, and proficiency in SPSS or Stata. Those who attend the Institute are encouraged to bring their own data sets and a laptop, as part of the time will be spent applying the methods.
Panel Discussion:
Engaging in Critical Quantitative Research
The 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.
Seminars (Participants select one of the following to attend):
Social Network Analysis & Higher Education Research
This is an introductory seminar to Social Network Analysis 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 Analysis offers an alternate perspective, where the attributes of individual actors are less important than their relationships and ties with other actors within the network.
The seminar will demonstrate the conceptual and methodological value of Social Network Analysis in the study of higher education. There are both conceptual and methodological benefits to utilizing Social Network Analysis in areas of research relevant to institutions of higher education. Conceptually, Social Network Analysis allows researchers to understand the formation of ties and the characteristics of the ties that may be most relevant to the attainment of specific goals. Methodologically, the use of sociograms allows researchers to explore the dynamism embedded in the formation of social networks. More specifically, those attending the seminar will:
- Become familiar with the concepts and terminology used in social network theory
- Be able to re-conceptualize network structures into variables for subsequent quantitative data analyses
- Learn how to ask survey questions to generate data that can be analyzed using Social Network Analysis and methods
- Be able to discuss strengths and limitations of the existing literature on social network analysis
- Learn how to use software (UCINET) to analyze data and to produce sociograms
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
Schedule
| Tuesday, July 13 | |
| 7:00am-8:30 | Continental Breakfast at Hotel Palomar |
| 9:00am-10:30am | Becoming an Equity-Minded Researcher (Panel), GSEIS 111 -Dr. Sylvia Hurtado, UCLA -Dr. Marvin Titus, University of Maryland -Dr. Cecilia Rios-Aguilar, University of Arizona -Dr. Scott Thomas, Claremont Graduate University |
| 10:45am-12:00pm | Session 1: Multilevel Modeling, GSEIS 121 Session 2: Social Network Analysis, GSEIS 245 |
| 12:00pm-1:00pm | Lunch: 306 Royce Hall |
| 1:00pm-2:30pm | Session 1: Multilevel Modeling Session 2: Social Network Analysis |
| 2:30pm-3:00pm | Break, GSEIS Salon |
| 3:00-5:00pm | Session 1: Multilevel Modeling Session 2: Social Network Analysis |
| 6:00pm-8:00pm | Dinner at Hotel Palomar |
| Wednesday, July 14 | |
| 7:00am-8:30am | Continental Breakfast at Hotel Palomar |
| 8:30am | Shuttle to GSEIS Building |
| 9:00am-12:00pm | Session 1: Multilevel Modeling, GSEIS 121 Session 2: Social Network Analysis, GSEIS 245 |
| 12:00pm-1:00pm | Lunch: 306 Royce Hall |
| 1:00pm-3:00pm | Session 1: Multilevel Modeling, GSEIS 121 Session 2: Social Network Analysis, GSEIS 245 |
| 3:00pm-3:30pm | Break, GSEIS Salon |
| 3:30-5:00pm | Session 1: Multilevel Modeling, GSEIS 121 Session 2: Social Network Analysis, GSEIS 245 |
| 5:15pm | Shuttle to Hotel Palomar |
| Dinner on your own tonight | |
| Thursday, July 15 | |
| 7:00am-8:30am | Continental Breakfast at Hotel Palomar |
| 8:30am | Shuttle to GSEIS Building |
| 9:00am-12:00pm | Session 1: Multilevel Modeling, GSEIS 121 Session 2: Social Network Analysis, GSEIS 245 |
| 12:00pm-1:00pm | Lunch: 306 Royce Hall |
| 1:00pm-2:00pm | Session wrap-up |
| 2:30pm | Shuttle to Hotel Palomar |