T 14

Conducting Research in Advising:

A Primer

Rich Robbins

Abstract

NACADA views research as scholarly inquiry into all aspects of the advising interaction, the role of advising in higher education, and the effects that advising can have on students (NACADA View on Research, 2008). This topical session will serve as a primer for conducting research in the field of academic advising with an emphasis on research as scholarly inquiry. Topics include reasons to conduct research in advising, identifying research questions, conducting a literature review, types of research methods, core skills in conducting advising research, gathering data, anddeveloping a research project.

Outline

  1. NACADA’s View of Research
  1. Reasons to Conduct Research in Advising
  1. Research as a Scholarly Inquiry
  1. Research Methodology
  1. Core Skills
  1. Data Collection
  1. Developing a Research Project

Bibliography of Research References

Research Design: Overall

Denzin, N. K. (1978). The Research Act: A Theoretical Introduction to Sociological Methods. New York: McGraw-Hill.

(A very significant introduction to research methods from a sociological perspective)

Firestone, W. A. (1987). Meaning in method: The rhetoric of quantitative and qualitative research. Educational Researcher, 16, 16-21.

(From an educational perspective, a good comparison of qualitative versus quantitative methods)

Sommer, R., & Sommer, B. B. (1986). A Practical Guide to Behavioral Research: Tools and Techniques. New York: OxfordUniversity Press.

(Recommended as the single best book to start research from scratch)

Research Design: Qualitative Methods

Altheide, D. L. (1987). Ethnographic content analysis. Qualitative Sociology, 10, 65-77.

Atkinson, P., & Hammersley, M. (1989). Ethnography Principles in Practice. New York: CambridgeUniversity Press.

Spradley, J. P. (1980). Participant Observation. New York: Holt, Rinehart, & Winston.

Strauss, A. L., & Corbin, J. (1990). Basics of Qualitative Research. Newbury Park, CA: Sage Publications.

Weber, R. P. (1990). Basic Content Analysis (2nd edition). Newbury Park, CA: Sage Publications.

Yin, R. K. (1989). Case Study Research: Design and Methods (2nd edition). Beverly Hills, CA: Sage Publications.

Research Design: Quantitative Methods

Babbie, E. (1973). Survey Research Methods. Belmont, CA: Wadsworth.

Kerlinger, F. N. (1973). Foundations of Behavioral Research. New York: Holt, Rinehart, & Winston.

Mahoney, M. (1978). Experimental methods and outcome evaluation. Journal of Consulting and Clinical Psychology, 46, 660-672.

Instruments/Questionnaires

Bonjean, C. M., Hill, R. J., & McLemore, S. D. (1967). Sociological Measurement: An Inventory of Scales and Indices. San Francisco, CA: Chandler.

(A solid source of sociological measures)

Buro’s Mental Measurement Yearbook

(The classic guide which lays out all published measures of psychological concern, their validation, reliability, and critical studies)

Chun, K., Cobb, S., & French, J. R. P., Jr. (1975). Measures for Psychological Assessment: A Guide to 3000 Original Sources and Their Applications. Ann Arbor, MI: University of Michigan, SurveyResearchCenter of the Institute for Social Research.

(A good source of less frequently used measures, as well as the well-established measures for a variety of psychological issues)

Statistics

Huberman, M., & Miles, M. (1994). Data management and analysis methods. In N. K. Denzin & Y. S. Lincoln (eds.) Handbook of Qualitative Research (pp. 428-444). Newbury Park, CA: Sage Publications.

(Good start on data management)

Huff, D. (1954). How to Lie With Statistics. New York: W. W. Norton.

(A classic which is still important; short and easy; how data can be manipulated and how to stay clean)

Rowntree, D. (1981). Statistics Without Tears: A Primer for Non-Mathematicians. New York: Charles Scribner’s Sons.

(A good overview of statistics, quick and easy)

Siegel, S., & Castellan, N. J. (1988). Non-Parametric Statistics for the Behavioral Sciences (2nd edition). New York: McGraw Hill.

(Most research in higher education does not lend itself to parametric design (which assumes conditions such as all sub-groups being independent of one another); however, most social scientists use them anyway…for those who wish to “do the right thing” (understanding percentages, etc.), non-parametric statistics is the best path to success)

NACADA Academic Advising Summer Institute 2011

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