• Postdoc 2012 – University of Amsterdam, Psychological Methods
  • Ph.D. 2010 – Simon Fraser University, Psychology (Theory and Methods)
  • M.Sc. 2005 – University of Calgary, Psychology
  • B.A. 2002 – University of Calgary, Psychology (Hons)

Area of Expertise

  • Psychometrics
  • Educational measurement
  • Educational technology
  • Small group collaborations
  • Educational Psychology


Peter Halpin specializes in psychometrics and educational measurement. He earned his Ph.D. from Simon Fraser University in Vancouver, Canada. Prior to joining UNC, he was a postdoctoral researcher at the University of Amsterdam, and an assistant/associate professor at New York University.


The overall goal of Halpin’s research is to develop innovative and rigorous statistical methodology to address pressing issues that arise in educational research, practice, and policy. Examples of some research questions his work has addressed are listed below.

  • How can online learning environments be designed to support small group interactions among students, and what do students learn as a result of such interactions?
  • How can we use intensive time-series data obtained from students’ use of educational technology to make reliable, valid, and fair inferences about student learning?
  • What makes teaching practices “effective” and how can we best provide educators with meaningful feedback about their practices?
  • How do the psychometric properties of outcome measures affect the conclusions that can be made from cluster-randomized control trials?
  • Current policy initiatives such as the United Nation’s Sustainable Development Goals emphasize the importance of universal access to quality early childhood education. How can we measure the effects of such initiatives on children’s early development in a way that is both psychometrically rigorous and feasible to implement on a global scale?

In addition to these topics, he has general interests in psychometric methodology (e.g., item response theory, factor analysis, latent class analysis), statistical programming (mainly in R with occasional forays into Python and C), quantitative research on individual differences, and philosophical aspects of quantification and measurement in the social sciences.

Prospective students who are interested in these topics or similar areas of research are invited to contact Halpin.