Sem02 (2024-2025) Fundamentals: Becoming better at explaining and understanding*

Course details

• Practical information

  Academic year
  2024-2025

  Semester
  2

  Period
  4

  Day(s)
  Tuesdays & 1 full Saturday (1 March)

  Time
  Tuesdays: 18:00 – 21:00
  Saturday: 10:00 – 17:00

  Number of meetings
  8

  Dates all meetings
  4, 11, 18, 25 February;
  1, 4, 11, 18 March; 

  Location
  Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam

  Room
  NU-3A47
  
  Credits
  6

  Lecturers

  • Dr. Noah van Dongen | Contact: n.djaye@gmail.com
  • Prof. dr. Denny Borsboom

• Learning objectives

  After the course, the students will have acquired knowledge and skills on:

  1. Critical thinking, formal reasoning, and logic
  2. Basics of causal modelling
  3. Basics of mathematical and computational modelling
  4. Deriving predictions/consequences of theories and formulating critical tests
  5. Critical assessment of theories and their amendment in light of new evidence
  6. General assessment of the quality of scientific theories

• Assessment methods

  • Group-based assignments (50%), individual research plan (25%), group-based presentation of the theory building process (25%)
  • Group-based assignments (2-4 persons) are evenly spread-out across the course. These assignments are designed to put the materials of the lectures directly into practice, taking the students step-by-step through the process of theory development, testing, and assessment. These are small assignments that are introduced and started before the end of each lecture.
  • Near the end of the course, individual students write a brief research proposal (max 1000 words) for a critical test of the theory their group has been developing during the previous lectures.
  • On the final day of the course, the groups will give a presentation on their theory development: the results of the steps they took in the development of their theory (group-based assignments), the proposed tests.

• Study materials

  Relevant tools, e.g.,

  • Insight Maker   –  GUI application for stock and flow models https://insightmaker.com/
  • NetLogo  –  a multi-agent programmable modeling environment https://ccl.northwestern.edu/netlogo/ 
  • DAGitty – draw and analyze causal diagrams: http://www.dagitty.net/
  • Loopy  – a tool for thinking in systems: https://ncase.me/loopy/

  Some of the scientific literature for the interested reader (not mandatory):

  • Borsboom, D., van der Maas, H. L. J., Dalege, J., Kievit, R. A., & Haig, B. D. (2020). Theory Construction Methodology: A practical framework for theory formation in psychology. https://doi.org/10.31234/osf.io/w5tp8
  • Fried, E. I. (2020). Lack of theory building and testing impedes progress in the factor and network literature. https://doi.org/10.31234/osf.io/zg84s
  • Guest, O., & Martin, A. E. (2020). How computational modeling can force theory building in psychological science.
  •  Robinaugh, D. J., Haslbeck, J. M. B., Ryan, O., Fried, E. I., & Waldorp, L. J. (2020). Invisible Hands and Fine Callipers: A Call to Use Formal Theory as a Toolkit for Theory Construction. PsyArXiv. https://psyarxiv.com/ugz7y
  • Van Rooij, I., & Baggio, G. (2020). Theory before the test: How to build high-verisimilitude explanatory theories in psychological science. Perspectives on Psychological Science, 1745691620970604.

  Other material, e.g.:
  
  •    https://neuroplausible.com/path
  •    http://backreaction.blogspot.com/2017/11/how-popper-killed-particle-physics.html
  •    https://www.youtube.com/watch?v=gp0tYLufcNo&feature=youtu.be