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Applied Experimental Research

Course Dates and Times

Monday 6 August - Friday 10 August

14:00-15:30 / 16:00-17:30

John Jost

john.jost@nyu.edu

New York University

This course will involve little lecturing and will focus instead on students’ development of their own theories, hypotheses, and research programs. By leveraging William J. McGuire’s philosophy of science and the perspectivist method of planning research in behavioral science, we will emphasize creative hypothesis generation and theory building.

Students will complete exercises designed to clarify the conceptual foundations of their own work and to help them develop multiple hypotheses concerning empirical relationships among independent, dependent, mediating, and moderating variables. We will develop useful manipulations and measurement strategies that overcome common methodological problems.

On several occasions, students will present their hypotheses, research designs, and experimental procedures to the rest of the class, and we will engage in group discussion and constructive evaluation. Students will incorporate this feedback to refine their plans, with the long-term goal of conducting sophisticated programs of research on interesting ideas of their own choosing.

Tasks for ECTS Credits

  • Participants attending the course: 2 credits (pass/fail grade) The workload for the calculation of ECTS credits is based on the assumption that students attend classes and carry out the necessary reading and/or other work prior to, and after, classes.
  • Participants attending the course and completing one task (see below): 3 credits (to be graded)
  • Participants attending the course, and completing two tasks (see below): 4 credits (to be graded)

For 3 credits, participants will be evaluated on the in-class presentation, based on their research, all participants are required to make.

For 4 credits, participants will also be required to complete a take-home paper.  The deadline will be set during the course.


Instructor Bio

John T. Jost is Professor of Psychology and Politics and Co-Director of the Center for Social and Political Behaviour at New York University.

His research, which addresses stereotyping, prejudice, political ideology, and system justification theory, has been funded by the National Science Foundation, has appeared in top scientific journals and received national and international media attention.

He has published more than 200 journal articles and book chapters and four co-edited book volumes, including Social and Psychological Bases of Ideology and System Justification (Oxford, 2009).

John has received numerous honours and awards, including the Gordon Allport Intergroup Relations Prize, the Erik Erikson Award for Early Career Research Achievement in Political Psychology, the International Society for Self and Identity Early Career Award, the Society for Personality and Social Psychology Theoretical Innovation Prize, the Society of Experimental Social Psychology Career Trajectory Award, and the Morton Deutsch Award for Distinguished Scholarly and Practical Contributions to Social Justice.

He has served on several editorial boards and executive committees of professional societies and is currently editor of the Oxford University Press book series on Political Psychology.

John Jost is a Fellow of the Society of Experimental Social Psychology and the Association of Psychological Science, and is Past President of the International Society of Political Psychology.

  @JohnJost1

This course will be unusual in the sense that it will involve very little lecturing. Instead, we will focus squarely on students’ development of their own research ideas, interests, questions, theories, and hypotheses. We will begin by considering William J. McGuire’s post-Popperian philosophy of science and his perspectivist method of planning and implementing programmatic research in the social and behavioral sciences. The focus of this method is on creative hypothesis generation and theory building rather than on hypothesis testing and theory disconfirmation per se.

Specifically, students will complete a series of written exercises designed to clarify the conceptual foundations of their own research programs and, in the process, develop multiple hypotheses concerning nonobvious empirical relationships among independent, dependent, mediating, and moderating variables that are of genuine theoretical interest. Students will be asked to present their hypotheses to the rest of the class, and we will engage in group discussion and constructive evaluation.

We will discuss the major advantages of developing experimental programs of research in the social and behavioral sciences, such as leveraging the method of strong inference, and the four stages of experimentation, namely: (l) setting the stage for the experiment, (2) constructing the independent variable, (3) measuring the dependent variable, and (4) planning the post-experimental follow-up. We will work on developing meaningful operationalizations of variables, including manipulations as well as measurement strategies, and we will seek to avoid and overcome common methodological problems or “impurities,” which can introduce interpretational (and rhetorical) threats and ambiguities. Students will be asked to present their experimental designs to the rest of the class, and we will engage in group discussion and constructive evaluation.

Based on feedback at several stages, students will work to refine their hypotheses, research designs, and experimental procedures, with the eventual long-term goal of independently conducting sophisticated, theory-driven programs of research on interesting ideas of their own choosing.

Note from the Academic Convenors to prospective participants: by registering to this course, you certify that you possess the prerequisite knowledge that is requested to be able to follow this course. The instructor will not teach again these prerequisite items. If you doubt whether you possess that knowledge to a sufficient extent, we suggest you contact the instructor before you proceed to your registration.

All students are expected to have completed ECPR’s “Introduction to Experimental Research in the Social Sciences” which is offered during the first week of the 2018 “ECPR Summer School in Methods and Techniques” or to have obtained equivalent knowledge elsewhere. In addition, it is assumed that students will have already conducted their own empirical research programs (typically in the context of a Ph.D. program in the social sciences) and have ongoing plans to conduct research that lends itself to experimental methods. Students will be asked to present their own ideas for research and to engage in theory building, hypothesis generation, and the design of careful, sophisticated experiments for investigating those hypotheses. This is only possible if workshop participants are actively pursuing empirical research programs in the social and behavioral sciences.

Day Topic Details
1 Scientific theories and criteria for their evaluation; post-Popperian philosophy of science; creative hypothesis generation; the perspectivist method

Both sessions will involve a mix of background lectures and discussion, as well as individual and group activities focused on students’ own theoretical development

2 Presentation and discussion of hypothesis generation exercise (perspectivist worksheets)

These sessions will involve student presentations of initial and contrary hypotheses (according to the perspectivist method) followed by group discussion/constructive evaluation

3 Presentation and discussion of (rough) experimental designs; operations and other logistical issues

These sessions will involve student presentations of initial experimental designs (and procedures) followed by group discussion

4 Strong inference; overcoming experimental “impurities”; improving your manipulations and measures

In addition to methods of strong inference, we will discuss common problems with the conceptualization and operationalization of independent and dependent variables and other interpretational threats

5 Presentation and discussion of theoretical ambitions and (more polished) experimental procedures

Students will describe (and receive feedback on) their plans for conducting theory-driven experimental research programs on interesting ideas of their own choosing

Day Readings
1
2
  • William J. McGuire (1989). Strategic planning of programs of research. Selection from: The Psychology of Science: Contributions to Metascience (pp. 224-245).
  • Prior to Day 2, participants will complete worksheets made available electronically and adapted from William J. McGuire (2004). Perspectivist worksheets for generating a program of research. In J.T. Jost et al. (Eds.) Perspectivism in Social Psychology (pp. 319-324). http://www.psychwiki.com/dms/wiki/uploadedfiles/researchdesign/Perspectivist_Worksheets_Original.pdf
3
4
5

Software Requirements

None.

Hardware Requirements

Participants are required to bring their own laptop.

Literature

Background (Foundational):

Druckman, J. N., Green, D. P., Kuklinski, J. H., & Lupia, A. (Eds.). (2011). Cambridge Handbook of Experimental Political Science. Cambridge University Press. (http://groups.polisci.northwestern.edu/researchpool/Handbook.pdf)

Kittel, B., Luhan, W. J., & Morton, R.B. (Eds.). (2012). Experimental Political Science: Principles and Practices. Palgrave-Macmillan.

Morton, R.B. & Williams, K. (2010). Experimental Political Science and the Study of Causality. From Nature to the Lab. Cambridge University Press. (http://faculty.som.yale.edu/shyamsunder/ExperimentalEconomics/Nature_to_Lab_manuscript.pdf)

Foreground (Required):

Abelson, R.P. (1995). Impurities in experiments. Selection from: Statistics as Principled Argument (pp. 189-198). Hillsdale, NJ: Erlbaum.

Druckman, J.N., & Lupia, A. (2012, March 9). Experimenting with politics. Science, 335, 1177-1179.

Hendrick, C., & Jones, R.A. (1972). Postscript (on the method of strong inference).  Selection from: The Nature of Theory and Research in Social Psychology (pp. 355-360). New York: Academic.

McGuire, W.J. (1989). Strategic planning of programs of research. Selection from: B. Gholson, W.R. Shadish, Jr., R.A. Neimeyer, & A.C. Houts (Eds.), The Psychology of Science: Contributions to Metascience (pp. 224-245). New York: Cambridge University Press.

McGuire, W.J. (1997). Creative hypothesis generating in psychology: Some useful heuristics. Annual Review of Psychology, 48, 1–30. http://annualreviews.org/doi/full/10.1146/annurev.psych.48.1.1

McGuire, W.J. (2004). Appendix: Perspectivist worksheets for generating a program of research. In J.T. Jost, M.R. Banaji, & D. A Prentice (Eds.) Perspectivism in Social Psychology (pp. 319-324). Washington, DC: APA. http://www.psychwiki.com/dms/wiki/uploadedfiles/researchdesign/Perspectivist_Worksheets_Original.pdf

McGuire, W.J. (2013). An additional future for psychological science. (Edited with an introduction by J.T. Jost). Perspectives on Psychological Science, 8, 414-423. https://pdfs.semanticscholar.org/18f6/2a894a69eb68b217fa18cc7b2fcf8052d1ba.pdf

Wilson, T.D., Aronson, E., & Carlsmith, K. (2010). The four stages of laboratory experimentation. Selection from: Handbook of Social Psychology (Fifth Ed., Vol. 1, pp. 63-78). http://www.colgate.edu/portaldata/imagegallerywww/184416d4-5863-4a3e-a73b-b2b6b86e7b60/ImageGallery/Wilson_Aronson_Carlsmith_2010.pdf

Supplemental (Optional):

Festinger, L., & Carlsmith, M. (1959). Cognitive consequences of forced compliance. Journal of Abnormal and Social Psychology, 58, 203-210. https://faculty.washington.edu/jdb/345/345%20Articles/Festinger%20&%20Carlsmith.pdf

Lord, C.G., Lepper, M., & Preston, E. (1984). Considering the opposite: A corrective strategy for social judgment. Journal of Personality and Social Psychology, 47, 1231-1243. http://synapse.princeton.edu/~sam/lord_lepper_preston84_JPSP_considering-the-opposite.pdf

Recommended Courses to Cover Before this One

Summer School

Introduction to Experimental Research in the Social Sciences

Recommended Courses to Cover After this One

Summer School

Structural Equation Modeling
Multilevel Modeling

Winter School

Structural Equation Modeling
Multilevel Modeling