ICPSR: Resources for Use in Undergraduate Instruction
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This presentation was given at an ICPSR Lunch and Learn on 2-24-2010. Resources that can be used in undergraduate social science education were discussed and the slides/notes should contain enough information that they can be used by others to promote these resources.
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ICPSR: Resources for Use in Undergraduate Instruction
- 1. Promoting ICPSR: Resources for Use in Undergraduate Instruction Lunch & Learn February 24, 2010 Lynette Hoelter
- 9. Exploring Data Through Research Literature
- 10. Investigating Community and Social Capital
- 11. SETUPS 2008
- 17. Frequency Distribution Cells contain: -Column percent -Weighted N INCOME 1 LESS THAN $24,000 2 $24,000-$49,999 3 $50,000-$99,999 4 MORE THAN $100,000 ROW TOTAL YEARGAMB 0: Didn't gamble in past year 32.4 15,759,745 25.1 13,001,616 19.6 8,868,472 24.5 4,030,466 25.7 41,660,300 1: Gambled in past year 67.6 32,885,485 74.9 38,713,040 80.4 36,491,643 75.5 12,402,378 74.3 120,492,546 COL TOTAL 100.0 48,645,230 100.0 51,714,657 100.0 45,360,115 100.0 16,432,844 100.0 162,152,846
Notes de l'éditeur
- Developed by Rachael Barlow, Data Librarian at Trinity College. EDRL is a new approach to teaching students about research that was developed because of student questions relating to the typical “come up with a hypothesis and test it using this dataset” type of assignment often given in social science research methods or capstone courses. Shows that research is not done in a vacuum by demonstrating linkages based on dataset, author(s), or topic. Faculty give students a focal article and ask them to use ICPSR’s Bibliography of Data-Related Literature to find other articles based on a particular feature (author, dataset, etc.) of that focal article.
- Uses 3 data sets including the General Social Survey, DDB Needham Life Style Surveys, and State-level data to reproduce findings from Robert Putnam’s Bowling Alone A sequential set of exercises that introduces students to the research process by teaching them how to browse codebooks, devise and execute cross tabulations and summary statistics. Helps teach replication of scientific evidence http://www.icpsr.umich.edu/ICSC/index.html
- Uses the 2008 National Election Study to help students examine and understand voting behavior. Provides substantive background, terms and descriptions, and embedded exercises to allow users to get through simple exploratory analyses of political behavior. Builds cross tabular exercises based on various questions about the 2008 Presidential elections. SETUPS (Supplementary Empirical Teaching Units in Political Science) began in the 1970s as workbooks and has been solely online since 2004. www.icpsr.umich.edu/SETUPS
- Developed in direct response to interviews and focus groups with teaching faculty. Standardized series of exercises that are content-focused and model good scientific process. Really geared toward introductory-level and “substantive” courses rather than research methods and statistics. Launched in September 2009.
- Data-driven Learning Guides are the exercises. They are classified for browsing by discipline/topic (disciplines on site as of Feb. 2010 include political science, sociology, and social psychology – research methods and economics are also represented by guides in process), most sophisticated statistical analysis type used in the guide, and dataset on which they are based. They are also searchable by keywords.
- Exercises are set up as a blend of lesson plans and scientific reports in order to help both instructors and students. The goal and summary sections help faculty easily identify whether the guide is right for their courses. Concept section describes the focal concept and how it is used in social science literature and offers examples of possible angles for studying that topic. Dataset section describes the dataset (as well as links back to the original ICPSR metadata page) and why it is useful for examining the questions asked within the guide. It also lists all original variables that are used in the creation of the guide so that work can be replicated. Application documents any data manipulation and walks students through a series of questions and analyses. SDA is engaged behind the scenes as links are clicked – assures instructors that all students are seeing the same results. The interpretation section includes any general cautions that are relevant such as notes about missing data or generalizability, examples of how to interpret the statistical techniques used within the guide, and gives “answers” to the questions posed to give students an idea of the main points. Summary section is the “take home message” of the guide. Bibliography links to Bib. of Data-Related Literature and suggests articles based on topic. Can be used as the beginning of a larger research paper. The SDA results are the only things that can’t be seen by non-members. Again, content is the focus with students learning to interpret statistics as a “by product” of doing the activites.
- TeachingWithData.org is a part of the National Science Distributed Learning program – it is currently the only pathway focused on social sciences. Partnership with the Social Science Data Analysis Network Repository for materials found online that include (but not limited to): Teaching exercises involving data Datasets for educational use Sources of facts and figures Materials to help instructors learn about teaching with data Each object is tagged with metadata for easy searching and browsing