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Solid Science: Research Methods

University of Amsterdam via Coursera

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Overview

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Can we still put our trust in the social and behavioural sciences? Cases of social scientists exposed as frauds keep turning up and many disciplines are under fire for their failure to replicate key results. No wonder the integrity of our field is being questioned; sloppy science is starting to seem the norm rather than the exception!

As social scientist Daniel Kahneman suggests, it is time for the social sciences to clean house. We will try to answer his call with a series of courses that explain the scientific principles of research and how methodology and statistics can help to ensure that research is solid. We will explain the basics and put them into context by showing you how things can go horribly wrong when methods and statistics are abused. And we will teach you how to recognize these questionable research practices - after the fact - in published articles.

This first course, Solid Science: Research Methods (in the Social and Behavioral Sciences), will cover the fundamental principles of science, some history and philosophy of science, research designs, measurement, sampling and ethics. This basic material will lay the groundwork for the more technical stuff in subsequent courses. The course is comparable to a university level introductory course on quantitative research methods in the social sciences, but has a strong focus on research integrity. We will use examples from sociology, political sciences, educational sciences, communication sciences and psychology.

Please note that this course will focus on quantitative methods, qualitative methods will be treated in a separate course.

Syllabus

This first course will cover the fundamental principles of science, some history and philosophy of science, research designs, measurement, sampling and ethics. This basic material will lay the groundwork for the more technical stuff in subsequent courses. The course is comparable to a university level introductory course on quantitative research methods in the social sciences, but has a strong focus on research integrity. We will use examples from sociology, political sciences, educational sciences, communication sciences and psychology.

Week 1: Origins of the scientific method
  • non-scientific and scientific ways to gain knowledge, types of scientific claims 
  • history of the scientific method (classical period, enlightenment, modern science) 
  • philosophical considerations: ontology and epistemology 
  • approaches to science (qualitative versus quantitative) 
  • warm-up assignments (not graded)
Week 2: The scientific method
  • the empirical cycle and testing hypotheses 
  • scientific criteria and causality 
  • threats to internal validity 
  • variables of interest and disinterest 
  • small assignments (graded)
Week 3: Research designs
  • true experiments, manipulation and randomization 
  • experimental, quasi-experimental, correlational designs 
  • factorial and repeated measures designs 
  • matching and ecological validity 
  • small assignments & paper on week 1 & 2 due (graded)
Week 4: Measurement
  • variables and operationalizations 
  • measurement levels and types, validity and reliability 
  • surveys, questionnaires and tests, items and scales 
  • other forms of measurement 
  • small assignments (graded)
Week 5: Sampling
  • threats to external validity 
  • random and non-random sampling 
  • random sampling methods 
  • sampling bias and error, sample size 
  • assignments & paper on on week 3 & 4 due (graded)
Week 6: Practice, ethics & integrity
  • research protocols and data management 
  • ethics towards participants and research integrity 
  • review and publication process 
  • questionable research practices
  • small assignments (graded)
Week 7: Study week
  • time to catch up and study for the final exam
  • time to ask your final questions
  • time to work on last paper
Week 8: Exam week
  • paper on week 5 & 6 due (graded), final exam (graded) and course evaluation

Taught by

Annemarie Zand Scholten

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