List of recommended readings - MSc Psychology

The master’s programme in Psychology is specially designed for students holding a bachelor’s degree in Psychology. We noticed that given your background you (may) have some deficiencies. We would like to suggest to take a look at this list of recommended readings, to prepare for the master’s in Psychology so you can assess to what extent and in which discipline you have deficiencies. We strongly advise you to work hard to eliminate possible deficiencies. On this list, the recommended readings for all specialisations of Psychology are given. The recommended readings on statistics are relevant for all students who will enter our master’s programme. For the recommended readings of Brain and Cognition, Psychology of Human Learning and Performance or Organisational Psychology, please check the list with readings of your specialisation. Some of them are books, others are articles from scientific journals. You will not be tested on this information, however, the Head of the Department expects all students to have this knowledge. Please select carefully which literature you need to study. Good luck with the preparation!

  • Eysenck, M. W., & Keane, M. T. (2005). Cognitive psychology: a student's handbook. Hove, UK: Erlbaum, 5th edition.

    Matlin, M. W. (2009). Cognition. Fort Worth, TX: Harcourt Brace, 7th edition.

    Stahl, S.M. (2008). Stahl’s Essential Psychopharmacology: neuroscientific basis and practical applications. Cambridge University Press.

    Stern, R.M., Ray, W.J. & Quigley, K.S. (2001). Psychophysiological recording. New York: Oxford University Press.

    Goldstein, E.B. (2010). Sensation and perception. New York, NY: Wadsworth, 8th edition.

    Neath, I., & Surprenant, A. M. (2003). Human memory. Belmont, CA: Wadsworth (a division of Thomson Learning, Inc.), 2nd edition. ISBN 0-534-59562-6

    Gazzaniga, M.S., & Ivry, R.B. Cognitive Neuroscience: The Biology of Mind. NY, Norto, 2nd edition.

  • Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4–58.

    Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review, 28, 717-741.

    Ormrod, J. E. (2016). Human learning. 7th edition. Harlow, England: Pearson Education Limited

    Panadero E (2017) A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8:422.

    Scheiter, K., Schüler, A., & Eitel, A. (2017). Learning from multimedia: Cognitive processes and instructional support. In S. Schwan., & U. Cress (Eds.), The psychology of digital learning (pp. 1–19). Cham, Switzerland: Springer. 

    Schneider, M., & Preckel, F. (2017). Variables associated with achievement in higher education: A systematic review of meta‐analyses. Psychological Bulletin, 143, 565– 600.

    Soderstrom, N. C., & Bjork, R. A. (2015). Learning versus performance: An integrative review. Perspectives on Psychological Science, 10, 176-199.

    Sweller, J., Van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31, 261-292.

  • Bell, S. T., Villado, A. J., Lukasik, M. A., Belau, L., & Briggs, A. L. (2011). Getting specific about demographic diversity variable and team performance relationships: A meta-analysis. Journal of Management, 37, 709-743.

    Bakker, A. B., & Demerouti, E. (2017). Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology22, 273.-285.

    Carpini, J. A., Parker, S. K., & Griffin, M. A. (2017). A look back and a leap forward: A review and synthesis of the individual work performance literature. Academy of Management Annals, 11, 825-885.

    Grandey, A. A., & Melloy, R. C. (2017). The state of the heart: Emotional labor as emotion regulation reviewed and revised. Journal of Occupational Health Psychology, 22, 407-422

    Mathieu, J., Maynard, M. T., Rapp, T., & Gilson, L. (2008). Team effectiveness 1997-2007: A review of recent advancements and a glimpse into the future. Journal of Management, 34, 410-476.

    Lievens, F. (2017). Assessing personality–situation interplay in personnel selection: Toward more integration into personality research. European Journal of Personality, 31, 424-440.

    Roulin, N., & Bangerter, A. (2013). Social networking websites in personnel selection. Journal of Personnel Psychology, 12, 143-151.

  • Brace, Nicola, Rosemary Snelgar and Richard Kemp (2012). SPSS for Psychologists. Fifth edition. Palgrave Macmillan.

    Field, Andy (2009). Discovering statistics using SPSS. Third Edition. Londen: Sage Publications Ltd. (ISBN: 978847879073).

    To be able to keep up with the pace and level of the course in statistics, it is essential that you master statistics for Psychology on the level of a bachelor’s degree. That is, you should have a sufficient level of active knowledge of the following topics:

    • designs and methods of psychological research;
    • sampling theory;
    • exploring the data: univariate and bivariate distributions;
    • comparing two means (t-tests);
    • comparing several means (ANOVA/factorial ANOVA, ANCOVA);
    • correlation and regression;
    • comparing dependent means/repeated measures; and, to a lesser extent, test theory & psychometrics.

    Field (2009) covers most of these topics; it is advised to study the corresponding chapters in Field in advance to refresh your knowledge:

    • Correlation & regression - Field, Ch. 1, 2, 6
    • Multiple regression analysis - Field, Ch. 5, 7 (up to 7.11) • Major types of multiple regression analysis - Field, section 6.6 + Ch. 7 (7.11) Comparing means (GLM-Univariate) - Field, Ch. 9, 10, 11
    • ANCOVA part II & Factorial ANOVA - Field, Ch. 11, 12
    • REPEATED MEASURES (M)ANOVA (GLM-WS) - Field, Ch. 13 + Ch. 10 (section 10.2.11.1: 
    • polynomial contrasts: trend analysis)

    These methods will be taught during the master’s programme:
    • MANOVA (GLM-Multivariate) - Field, Ch. 16
    • GLM-WS MIXED DESIGNS - Field, Ch. Field explains statistics and SPSS on his YouTube channel as well: www.youtube.com/user/ProfAndyField