Registration is now open for the 2014 summer workshops offered by the Institute for Social Science Research. All workshops are open to faculty and students at UMass Amherst, the Five College system, and other institutions.
Below are details about each workshop and links for additional information.
Qualitative Research Design: Considerations and Tensions
May 12, 9 a.m.-3 p.m., and May 13, 9 a.m.-2 p.m.
Instructors: Gretchen Rossman and Zeke Kimball
Veteran qualitative researchers discuss challenges and opportunities as they arise in designing thoughtful and responsive research; considering purpose, context, potential participants and ethics; modifying the initial design based on emerging understandings of the context; and the conceptual and epistemological assumptions and their implications.
Organizing and Analyzing Qualitative Data with NVivo 10
May 14-16, 9 a.m.-noon
Instructor: Jackie Stein
This workshop will teach you the basics of using NVivo to code and analyze qualitative data. We will cover importing, organizing and beginning to code your data, then add other data types such as demographic information, and begin to explore your data with basic queries. Finally, we’ll cover more advanced ways of exploring coded data.
Applied Regression with R for Social Science Researchers
May 19-20, 9 a.m.-3 p.m.
Instructor: Christopher Burns
R is a free, open source programming language that gives empirical researchers a powerful set of tools for regression analysis. Workshop participants will learn how to import and export data, perform exploratory data analysis, run multiple regressions, conduct hypothesis testing, and estimate fixed and random effects models in the R environment.
Modeling Emergence: Computer Simulation of Social Dynamics
May 21-23, 9 a.m.-3 p.m. on Wednesday and Thursday, 9 a.m.-noon on Friday
720 Du Bois Library
Instructor: James A. Kitts
This workshop will allow attendees to understand some of the goals and methods of social simulation, give them hands-on experience in experimenting on theoretical models, and point them to resources to begin using these tools in their own work. Applications will include social networks, organizations, and population health models.
Web Scraping for Text Analysis in R
May 27-28, 10 a.m.-5 p.m.
Instructor: Greg Matthews
Social science researchers are often interested in retrieving data from the internet. Often, this can be accomplished using so-called web-scraping techniques. This course introduces the statistical programming language R, then demonstrates techniques for web scraping using R. Finally, tools for analyzing text data in R will be presented.
Making Your Research Matter Outside of Academia
May 29-30, 9:30 a.m.-4:30 p.m.
Instructors: Amy T. Schalet and Linda R. Tropp
This workshop, presented by the Public Engagement Project, offers an understanding of how to work in diverse public settings, as well as communication and networking skills to strategically and effectively engage in those settings while thriving in academia. Workshop activities include guided discussions, mapping professional networks and more.
Using MTurk and Qualtrics for Social Science Research
June 5-6, 10 a.m.-5 p.m.
Instructor: Bernhard Leidner
This workshop introduces you to MTurk and its utility in facilitating social science research. You will learn how to screen data collected from MTurk samples and learn the basics of how to create online surveys and experiments in Qualtrics, an online survey tool that can be used in conjunction with MTurk.
Ethnographic Research in Meeting-Intensive Settings
June 9-10, 10 a.m.-4 p.m.
Instructors: Jen Sandler and Renita Thedvall
Participants will examine some challenges of data collection in meeting-intensive settings and issues that arise when analyzing meeting-based fieldnotes, transcripts and artifacts. Participants are encouraged to bring their own meeting ethnography challenges to the session, as there will be time to discuss research design, data collection and more.
Introduction to Network Analysis using R
June 16-17, 9 a.m.-4 p.m.
Instructor: Bruce Desmarais
This course will introduce you to a network analysis in R, provide an as-necessary introduction to R programming and cover the basics of network analysis, including terminology; data collection/storage; and basic description. We will consider advanced topics in description and exploration, such as graphical representation and community detection.