Syllabus/achievement requirements
Focus is on scientific literacy to prepare you for selecting and defining a suitable master thesis topic and writing a proper thesis proposal. Specifics readings pre and post lecture will be assigned through the UiO - CANVAS learning platform to facilitate class discussion. The course will also partially be supported by the university library team to guide you through the library collections, databases, and bibliometric tools, search systems, and ethical use of sources.
Most of the texts on the reading list are available electronically through the University of Oslo Library. You have to be logged on to the UiO network in order to access them. Information about how to gain access from home can be found on this webpage.
The books that are listed are available at the Akademika bookstore on Blindern campus and in the library.
Selected readings
Philosophy of Science
(Book) Dienes, Z. (2008). Understanding Psychology as a Science: An Introduction to Scientific and Statistical Inference. Macmillan International Higher Education. [Chapter1+2]
Meehl, P. E. (1967). Theory-Testing in Psychology and Physics: A Methodological Paradox. Philosophy of Science, 34(2), 103–115.
Meehl, P. E. (1990a). Appraising and Amending Theories: The Strategy of Lakatosian Defense and Two Principles that Warrant It. Psychological Inquiry, 1(2), 108–141.
Meehl, P. E. (1990b). Why Summaries of Research on Psychological Theories are Often Uninterpretable. Psychological Reports, 66(1), 195–244.
Meehl, P. E. (1993). Philosophy of Science: Help or Hindrance? Psychological Reports, 72(3), 707–733.
Platt, J. R. (1964). Strong Inference: Certain systematic methods of scientific thinking may produce much more rapid progress than others. Science, 146(3642), 347–353.
O’Donohue, W., & Buchanan, J. A. (2001). The Weaknesses of Strong Inference. Behavior and Philosophy, 29, 1–20.
Makel, M. C., & Plucker, J. A. (2014). Facts Are More Important Than Novelty: Replication in the Education Sciences. Educational Researcher, 43(6), 304–316.
Critical reading of Meta-analysis
Bakker, M., van Dijk, A., & Wicherts, J. M. (2012). The Rules of the Game Called Psychological Science. Perspectives on Psychological Science, 7(6), 543–554.
Glass, G. V. (1977). 9: Integrating Findings: The Meta-Analysis of Research. Review of Research in Education, 5(1), 351–379.
Lewis, S., & Clarke, M. (2001). Forest plots: trying to see the wood and the trees. BMJ, 322(7300), 1479–1480.
Sterne, J. A. C., Sutton, A. J., Ioannidis, J. P. A., Terrin, N., Jones, D. R., Lau, J., … Higgins, J. P. T. (2011). Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ, 343, d4002.
Thompson, S. G., & Pocock, S. J. (1991). Can meta-analyses be trusted? Lancet, 338(8775), 1127–1130.
Use of computer-assisted Text analysis
Blei, D. M. (2012). Probabilistic Topic Models. Commun. ACM, 55(4), 77–84.
Grimmer, J., & Stewart, B. M. (2013). Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts. Political Analysis, 21(03), 267–297.