Distance Learning Courses
The University of Florida offers a series of online courses on research methods in cultural anthropology. The courses carry graduate credit and are open to upper division undergraduates, graduate students, and professionals. The emphasis in each course is on skills for collecting and analyzing the many kinds of data that anthropologists work with.
Four digital learning courses are offered in 2013. Each course has 12 hours of lecture and 33 hours of online, interactive instruction. Courses are limited to 18 participants.
Text Analysis in Cultural Anthropology
May 13 – June 21, 2013
This graduate seminar surveys methods of network analysis. The focus of the course is on developing skills that students can use to do systematic analysis of textual data, including written texts, photos, and audio or video data. The course will explore a range of inductive and deductive approaches and will cover analytic skills that cut across traditions, including theme identification, code definition, and construction of codebooks, and teamwork in text analysis. Advanced topics covered will include schema analysis, grounded theory, classical content analysis, content dictionaries, word-based analysis, and semantic network analysis.
Students taking this course will:
- develop a working familiarity with a wide range of methods used to analyze text data
- be able to select appropriate methods for a variety of research questions
- acquire hands-on experience using analytic techniques
- apply these skills to their own independent projects.
For further details about cost, registration, and the scope of the courses, please visit the UF Distance Learning program.
Network Analysis in Cultural Anthropology
May 13 – June 14, 2013
Social network analysis (SNA) is the study of the patterns of relations between actors. In this intensive, hands-on course, participants will learn about whole network analysis (relations within groups) and personal network analysis (relations surrounding individuals). The focus is on the collection and analysis of social network data, with many examples germane to field research. By the end of the course, participants should understand how to:
- Collect whole and personal network data and input it into social network analysis packages
- Transform data for analysis using graph-based and statistics-based social network measures
- Visualize network data with different algorithms
- Apply node and group level social network measures
- Build network models
- Choose among social network designs based on research goals
- Apply social network theory to example data sets
Geospatial Analysis in Cultural Anthropology
July 1– August 2, 2013
This intensive course introduces different components of geospatial analysis and their applications in Anthropology: Remote Sensing (RS), Geographic Information Systems (GIS), Global Positioning System (GPS), and their integration. The course covers basic concepts necessary to work with geospatial data. We pay particular attention to research set-up and design, and the use of specialized software, such as ArcGIS, Erdas Imagine, and Multispec via hands-on activities.
By the end of the course, participants should understand how to:
- add a geospatial component to traditional anthropological questions (ex. resource use, disparities, adaptation)
- understand how anthropologists can improve geospatial analysis research
- generate data (for example, change detection) using remotely sensed images
- integrate data sources from paper and electronic maps and tables
- analyze geospatial data
- create maps for presentation or field work
Video Analysis in Cultural Anthropology
July 1– August 2, 2013
This online course presents basic techniques for systematically gathering and analyzing video data for use in anthropological enquiry. This is an interactive, practice-based class that covers the basics of gathering and analyzing video data. By the end of the couerse, participants should understand where visual data fit into the anthropological research process, including issues surrounding the ethics of collecting visual data. Participants should also understand how to:
- use photos in eliciting data
- capture behavior streams with video
- use video in conducting interview
- archive digital recordings
- transcribe the textual data that results from an interview
- code and analyze the non-verbal interactions that occur within an interview
- test hypotheses using visual data