Knowledge
- Have a good conceptual grasp of key statistical principles (e.g., uncertainty & variation) for making solid inferences and conclusions.
- Demonstrate an understanding of classical test theory & measurement approaches as well as more modern test design techniques based on item response theory.
- Have insight into different ways to quantitatively analyze and use data to address measurement problems & research questions in the social sciences.
- Demonstrate an understanding of current paradigms and related societal debates in the field of assessment, measurement, and evaluation.
Skills
- Quantitative: Apply state-of-the-art statistical techniques (e.g., Structural Equation Models) to analyze and learn from data.
- Software: Proficiency in using the free software environment R for statistical computing and graphics
- Design: Apply best practices, including useability studies & cognitive labs, to design high quality measurement instruments.
- Communication: Write scientific papers & research reports, present posters, and give talks in academic and professional settings.
Competence
Initiate and contribute in a constructive but critical way to
- the discussion of existing assessment and evaluation systems, particularly as they relate to issues around validity and reliability.
- the construction of new assessment and measurement instruments, with a strong focus on validity and reliability for the intended use of the instrument.