Welcome! Research in the Markant Lab examines interactions between learning, memory, and decision making. How do people take action to navigate uncertain or changing environments? How do learners monitor and control their own learning experience? How do learning and memory influence the tendency to take risks or explore new behaviors?

We use behavioral experiments and computational modeling to investigate cognitive mechanisms involved in effective learning and decision making. In addition to basic research in cognitive science, the lab explores implications of these processes for learning and decision making in other contexts, including real-world instructional environments and among populations of learners with diverse cognitive abilities. Learn more about our research by reading the posts below or by browsing our list of publications.

The Markant Lab is part of the Department of Psychological Science at UNC Charlotte. We operate a shared space and engage in collaborative research and mentorship with the lab of Dr. Alexia Galati. We actively contribute to academic programs in health psychology, cognitive science, and computer science. If you are a student who is interested in the lab's research, see how you can get involved.

News & Updates

CogSci 2016 - Hypothesis generation and self-directed learning

At CogSci this year I presented some new work on hypothesis generation and its role in self-directed learning (specifically, the learning of categorical rules). This project explores the idea that hypothesis generation is a bottleneck in active learning, as is suggested by a lot of work in classic cognitive tasks as well as studies from educational psychology. The results give an example of how biases in the hypothesis generation process can have a big impact on whether people can efficiently learn different kinds of rules.

For more on this project, see the paper in the proceedings and the poster below (PDF).


Enhanced memory as a common effect of active learning (new paper)

I have a new paper out in Mind, Brain, and Education, coauthored with Azzu Ruggeri, Todd Gureckis, and Fei Xu. In the paper we argue that one reason active learning improves outcomes relative to passive conditions (like lectures) is that exercising control leads to enhanced memory (in particular, episodic memory for the events experienced during learning).

In many lab-based tasks, having control over learning (e.g., controlling the selection or pacing of new information) often leads to better memory compared to yoked conditions in which such control is absent but the same information is experienced. By surveying a range of research that has employed this kind of active/yoked design in different domains, we outline how improved memory can arise from a number of different mechanisms depending on the kind of control afforded to the active learner. Thinking about real-world learning activities in terms of this basic dimension of control (which is just one part of what people typically think of as “active learning”) may help us understand when and why active learning tends to produce better outcomes than traditional instruction.

A couple of things struck me while researching the paper:

  • Some form of episodic memory is important to many theories of conceptual learning or semantic memory – but episodic memory is not really a focus in educational research. Perhaps unsurprisingly, educational psychologists seem to be primarily interested in measures of conceptual learning: does the student remember the definition of a term, or how to solve a certain kind of physics problem? As far as I can tell there isn’t much work examining memory for the details of the learning experience (e.g., the activities completed, example problems that were encountered, conversations during class, etc.) and how it relates to other performance measures.

  • There’s a similar gap in lab-based research related to inquiry-based learning (including work on category and causal learning which usually shows an advantage for active control over yoked observation). This work has largely focused on the value of the information that active learners select (e.g., do they ask questions that are useful? Can they come up with experiments that lead to unconfounded evidence?). But it seems likely that the same set of memory-based mechanisms could play a role, particularly in real-world inquiry learning settings that involve richer materials and forms of interaction than the typical lab-based experiment.

Writing the paper helped me pinpoint some of these big open questions about how memory and control interact during learning. Of course, despite our best efforts it’s inevitable that we missed some existing work that would be useful. If you know of something relevant or have any other comments about the paper, let me know!

Active learning workshop at CogSci

Next month I’ll be participating in a full-day workshop at CogSci, entitled “Active learning: Cognitive development, education, and computational models.” The workshop will feature lots of terrific researchers from the CogSci community who have been thinking about active learning from many angles. Come by if you are in Philly on Wednesday!