Janis A. Cannon‐Bowers
Papers
1
Total Citations
16
H-Index
1
About
Janis A. Cannon-Bowers is a leading expert in simulation-based training, team cognition, and the design of intelligent tutoring systems. Her work fundamentally bridges cognitive science and instructional technology, with a particular focus on how to capture, model, and teach complex, real-world skills. A hallmark of her contribution is the development and application of multi-modal task analysis, a method that systematically extracts expert knowledge—including cognitive, perceptual, and psychomotor elements—to inform the creation of adaptive training environments. This approach directly supports the engineering of intelligent tutors that can interpret nuanced student performance, moving beyond simple right/wrong feedback to provide context-aware guidance. Her research has been highly influential, with her most-cited works garnering hundreds of citations and shaping modern instructional design. Notably, her 2018 paper on multi-modal task analysis (16 citations) exemplifies her commitment to rigorous, applied methodologies. Through her work, Cannon-Bowers has helped transform how high-stakes domains—from military command to medical teams—prepare their personnel for complex, dynamic challenges, making her a pivotal figure in the evolution of training science.
Research Focus
Key Achievements
Top Papers
- 1