Courses

Jeremy Caplan's teaching for 2025/2026:


Winter, 2027, PSYCH 416 and 505-B07 : Replication Controversies

(open to people from all departments)

Description: The Replication Crisis is a hot-button term that has gotten some people riled up and other people defensive. It has been used to hold people to account and to dismiss swaths of research. The goal of this seminar is to have thoughtful, considered discussions based on readings from multiple perspectives to develop a balanced view of the various phenomena the term evokes. We will critically examine topics related to replication in research, including file-drawer problems, selective reporting, publication bias, replication attempts, pre-registration and data-sharing, and how these interact with the culture of researchers. Statistical and mathematical methods for identifying publication bias will be discussed, with an emphasis on understanding both real and exaggerated research problems. We will discuss the statistics and mathematical methods for identifying publication bias in a field. If all goes well, we will end up with a nuanced understanding of both real and exaggerated problems and a repertoire of practices we can draw upon and adapt to our own research values and style.

Format: We will read articles and discuss them, led by students. A term project includes oral presentations and a final short paper based on a related practical activity.

Pre-requisites: Because the course is about research, *** experience conducting research and collecting data is required *** (but any topic or field of research is fine). Otherwise the course will feel punishingly difficult; concepts are way too abstract and hard to relate to without your own on-the-ground experiences doing your own research. Graduate students, honours students and people doing research via independent studies in any department are enthusiastically welcomed. Try out this self-quiz to assess your preparedness for this course or identify areas to read up on:

  • Explain what a hypothesis is, and how it differs from a topic, a prediction, an expectation or a research question.
  • What does a t test actually test?
  • When do you need to use an ANOVA?
  • What is a Pearson correlation? What does it mean if a correlation is positive, zero or negative?
  • What is a p value and how does it relate to false positives and false negatives?
  • What is a Bayes Factor?
  • Sketch your favourite experimental result and explain what we learn from it



Winter, 2027, PSYCH 473 and PSYCH 576: Cognitive Neuroscience

(open to people from all departments/faculties/colleges)

Description: Brain basis of human cognition studied using a diverse range of techniques, with a focus on measures of brain activity such as functional neuroimaging and electrophysiology recorded during behavioural tasks. Designed for graduate and advanced undergraduate students who are conducting their own cognitive neuroscience research.

Format: We will read articles and discuss them, led by students. Students will write hypothetical editorial letters for the articles. Students will present their own research or proposals. We will do hands-on analyses of sample brain-activity data.

Pre-requisites: I am happy to waive formal pre-requisites if you have the pertinent pre-requisite knowledge:
Basic knowledge of cognitive psychology and basic neuroscience and comfort reading and critiquing original research articles. Although we will work through the methods together, basic knowledge of cognitive neuroscience (e.g., EEG, fMRI and related topics) is also important so that you don't feel extremely lost. Have a look at recent articles in the Journal of Cognitive Neuroscience and try out this self-quiz to assess your preparedness for this course or identify areas to read up on (if most of these are hard work, the course will be more challenging than necessary):

  • Sketch a graph (fully labelled) of your favourite experimental psychology result and explain how the plot supports the researchers' conclusions.
  • Explain what a hypothesis is, and how it differs from a topic, a prediction, an expectation or a research question.
  • What does a t test actually test?
  • When do you need to use an ANOVA?
  • What is a Pearson correlation? What does it mean if a correlation is positive, zero or negative?
  • What is a p value and how does it relate to false positives and false negatives?
  • What is the difference between these units: V, mV and uV?
  • What do EEG and fMRI measure? How do people think each relate to neuronal activity?
  • What is the difference between MRI and fMRI?
  • What is an ERP, and how does that relate to EEG?
  • Sketch your favourite EEG or fMRI result, and explain what we learn from it











Check out the Alberta Cognitive Neuroscience group