Cognition and Active Learning Lab

Welcome to the Cognition and Active Learning (CAL) Lab! The CAL Lab involves the application of cognitive psychology principles to the study of effective teaching and learning strategies. We aim to bridge cognitive psychology and education and contribute to the science of learning. More specifically, the purpose of our lab is to determine how to design instruction to encourage effective cognitive processing in students with a particular focus on STEM content.

We consider instructional design in a multitude of contexts (e.g., in small and large courses, for introductory and advanced content) and using different media (e.g., real-world instruction, immersive virtual reality, artificial intelligence) to advance our understanding of how to support active learning in STEM courses. Our work involves quasi- and true-experimental designs that take place in lab and class settings and systematic reviews to evaluate research literature related to psychology, educational psychology, and education.

Meet our Team

Amédee Marchand Martella

Assistant professor and lab director

Logan Fiorella

Associate professor and lab collaborator

Ryan Patrick, postdoc

Co-advised by Logan Fiorella, Ryan completed his Ph.D. in psychological science at the University of Louisville in May 2025. Broadly, his research focuses on applying cognitive principles to enhance learning and memory. His past work has examined instructional sequencing—particularly productive failure—and spaced retrieval practice. Ryan’s current research explores the effectiveness of instructional sequences and the ways in which instructional design shapes metacognition and self-regulated learning.

Yun Zhang, doctoral student

Yun earned her B.S. in psychological and brain sciences, B.A. in cultural anthropology, and a minor in applied psychology from the University of California, Santa Barbara. Her research investigates how emerging technologies can enhance learning and motivation. She is particularly interested in multimedia learning, virtual reality learning, and generative AI applications in instructional design. Yun’s prior work explored how emotional cues, instructor characteristics, and feedback design influence learners’ cognitive and affective experiences in digital environments. Her current research focuses on VR-supported collaborative learning and scaffolding, particularly through the integration of conceptual and procedural lessons.

Beatrix Kim, doctoral student

Bea earned her B.S. in psychological and brain sciences from the University of California, Santa Barbara. Her research interests center on improving scientific literacy, examining the construct of active learning, and strengthening the connection between research and classroom practice. She is particularly interested in how different instructional design strategies impact learning outcomes in introductory STEM lessons, both in traditional and online classroom environments. Currently, she is working on a study that explores how peer teaching influences learning outcomes in introductory biology.

Research Themes

Use of lecture and/or activities to teach STEM content

Under this project theme, our studies investigate research questions such as:

Should lecture and activities be used in isolation or in combination to promote student learning?
Should lecture or activities be presented first or second in an instructional sequence?
How much time should be dedicated to lecture versus learning activities during a lesson?
How can learning activities be designed to assist students in encoding new content?

Use of educational technologies to teach STEM content

Under this project theme, our studies investigate research questions such as:

Should immersive virtual reality be used to present new content (e.g., as a form of lecture), to practice new content, or for both instructional phases?
How should instruction be sequenced (e.g., modeling, guided practice, independent practice versus modeling, modeling, independent practice versus guided practice, guided practice, independent practice) within virtual reality to maximize student learning?
How can we encourage effective collaboration within virtual environments?
How can we use artificial intelligence during a lesson to support student learning?

Use of systematic reviews to evaluate the research literature

Under this project theme, our systematic reviews investigate questions that span different research literatures such as active learning, learning and motivation, immersive virtual reality, ChatGPT, and productive failure. Example research questions include:

How methodologically rigorous is the [insert name] literature?
What are the strengths of the [insert name] literature base, are there any areas in need of improvement, and do any research gaps exist?
Within the [insert name] literature base, do interventions vary in their design and implementation and, if so, how?
How well designed and controlled are the experimental and control conditions within the [insert name] literature?

Research Opportunities

We are always looking for collaborators on new projects, as well as for undergraduate/graduate students and visiting fellows.

Collaborators

Please email Amédee Marchand Martella , CAL Lab director, expressing your interest in collaborating on future projects.

Undergraduate Students

Please email Amédee Marchand Martella and Ryan Patrick to express your interest in serving as a research assistant in our lab. In your email, please list your major and research interests. Members of our lab also have the opportunity to conduct CURO research.

Graduate Students

If you are interested in joining the CAL Lab as a Ph.D. student, please email Amédee Marchand Martella to ensure students are currently being accepted before applying to the Ph.D. program in applied cognition and development in the Department of Educational Psychology.

Visiting Fellows

If you are interested in being a visiting fellow, please email Amédee Marchand Martella .