Dr. Caleb Vatral

Assistant Professor of Computer Science

student on campus

Department of Computer Science听
Tennessee 福利影院最新网址听
3500 John A Merritt Blvd
Nashville, TN 37209

Office听:听McCord Hall 005F (Main Campus)
Email听: cvatral[at]tnstate[dot]edu
Phone听: (615) 963-5852
Homepage听:

Areas of Interest听
Artificial Intelligence, Machine Learning, Data Science, Educational Technologies, Learning Analytics, Human-Computer Interactions.

Education听
Ph.D., Vanderbilt University, Nashville, TN, USA.
B.Sc., Eastern Nazarene College, Quincy, MA, USA.

Biographical Sketch听
Dr. Caleb Vatral is an Assistant Professor in the Department of Computer Science at Tennessee 福利影院最新网址. Drawing from theories of distributed cognition and experiential learning science and combining them with research methodologies from user-centered participatory design and computational techniques from multimodal learning analytics, Dr. Vatral鈥檚 research focuses on how to improve education and training through the integration of AI technologies. By focusing on the strengths of both humans and AI systems, how these strengths can complement one another to build new capabilities, and how these capabilities can be designed and integrated into teaching with a strong emphasis on stakeholder needs and desires, Dr. Vatral鈥檚 work aims to build sustainable human-AI teaming in educational contexts. Prior to joining TSU, Dr. Vatral received their Ph.D. from Vanderbilt University.

Teaching Interests听
Artificial Intelligence, Machine Learning, Data Science, Applied Mathematics, Game Development and Interactive Media.

Selected Publications

  • Vatral, C., Biswas, G., Cohn, C., Davalos, E., & Mohammed, N. (2022). Using the dicot framework for integrated multimodal analysis in mixed-reality training environments. Frontiers in Artificial Intelligence, 5
  • Vatral, C., Biswas, G., Mohammed, N., & Goldberg, B. S. (2022). Automated assessment of team performance using multimodal bayesian learning analytics. Proceedings of the 2022 Interservice/Industry Training, Simulation and Education Conference (I/ITSEC). National Training and Simulation Association (Won Best Paper in the Human Performance Analysis Subcommittee)
  • Vatral, C., Cohn, C., Davalos, E., Biswas, G., Lee, M., Levin, D., Hall, E., & Holt, J. E. (2023). A tale of two nurses: Studying groupwork in nurse training by analyzing taskwork roles, social interactions, and self-efficacy. Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning-CSCL 2023, pp. 217-220
  • Vatral, C., Lee, M., Cohn, C., Davalos, E., Levin, D., & Biswas, G. (2023). Prediction of students鈥� self-confidence using multimodal features in an experiential nurse training environment. International Conference on Artificial Intelligence in Education, 266鈥�271
  • Snyder, C., Wen, C.-T., Hutchins, N. M., Vatral, C., Liu, C.-C., & Biswas, G. (2024). Investigating collaborative problem solving behaviors during stem+ c learning in groups with different prior knowledge distributions. Proceedings of the 17th International Conference on Computer-Supported Collaborative Learning-CSCL 2024, pp. 107-114 (Won Best Long Paper)

See More Publications: https://scholar.google.com/citations?user=RPuuRXUAAAAJ&hl=en