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Citation:
Using the National Datasets for Faculty Studies (J. Milam; 20 pp; No. 70). Winter, 1999. |
Abstract:
Numerous policy issues arise at the institutional, state, and national level which may be addressed with data about faculty. While in the past, it has been difficult if not impossible to gather data to support this research, the advent of the World Wide Web has transformed the dissemination and diffusion of the national datasets. In particular, the National Center for Education Statistics (NCES) and the National Science Foundation (NSF) have taken significant steps to make the data they collect available on the Web in a readily-accessible format for analysis.
The purpose of this AIR Professional File article is to document the national datasets which may be used for policy studies and research about faculty. These include 11 datasets which include faculty information (the IPEDS S, IPEDS SA, CUPA, Oklahoma State, AAUP, NSOPF, HERI, SDR, NRC, NSCG, and the NSRCG); two datasets about student enrollment (the IPEDS EF and the GSS); two datasets about degrees awarded (the IPEDS C and the SED); and two datasets about institutional activity (the IPEDS F and IPEDS IC).
An extensive review of each dataset is provided. This includes a discussion of the nature of each survey and examples of how the data may be used for faculty studies. The review also describes whether each dataset is based on a population or sample survey, key variables, the administering agency, response rates, where the data may be obtained, what historical data are available, and the most current data available. Most of the discussion focuses on the datasets with information about faculty or potential faculty. The six non-faculty datasets are analyzed in terms of how they may be used in conjunction with the other 11 for purposes such as calculating performance measures.
When examining the data, it is helpful to think of using different lenses for different kinds of analysis. Most of the datasets may be used for peer comparison of specific institutions and these serve as important resources for institutional research. It is also important to think about ways to aggregate the data by Carnegie classification and/or control. Regional issues such as the impact of cost of living on faculty salaries may be addressed with location, state, and zip code fields. At the national level, patterns of faculty workload, salary compression, and access may be discerned. |
Full Text: 70.pdf (3,207,482 bytes)
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