Nigel Bosch

Assistant Professor

PhD, University of Notre Dame

Other professional appointments

Assistant Professor, Department of Educational Psychology
Faculty Affiliate, National Center for Supercomputing Applications (NCSA)
Faculty Affiliate, Illinois Informatics

Research focus

Learning analytics, user modeling, fairness and transparency in machine learning.

Honors and Awards

National Study of Learning Mindsets Early Career Fellowship

Biography

Nigel Bosch is an assistant professor in the School of Information Sciences and the Department of Educational Psychology at the University of Urbana-Champaign and a faculty affiliate at the National Center for Supercomputing Applications (NCSA) and Illinois Informatics. His research includes machine learning/data mining methods to study human behaviors, especially in learning contexts (learning analytics), with an emphasis on model generalization and fair treatment of users.

His research examines data such as facial expressions, audio recordings, log file records of user actions, and other sources that provide insight into learners' behaviors. Neural networks and other machine learning methods provide powerful ways to mine these data for knowledge, but can proliferate biases that are commonly found in datasets. Bosch's research also focuses on analyzing the biases in these methods, with the goal of ultimately developing fairer learning software and research methods.

He obtained his PhD in computer science at the University of Notre Dame in 2017. For two years prior to joining the iSchool, he was a postdoctoral researcher at the NCSA.
 

Office hours

Fridays 10:30 a.m.-12:00 p.m. or by appointment

Publications & Papers

Bosch, N., Mills, C., Wammes, J. D., & Smilek, D. (2018). Quantifying classroom instructor dynamics with computer vision. In C. Rosé, R. Martínez-Maldonado, H. U. Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, ... B. du Boulay (Eds.), Proceedings of the 19th International Conference on Artificial Intelligence in Education (AIED 2018) (pp. 30–42). Cham, CH: Springer. 

Bosch, N., & Paquette, L. (2018). Metrics for discrete student models: Chance levels, comparisons, and use cases. Journal of Learning Analytics, 5(2), 86–104.

Jiang, Y., Bosch, N., Baker, R. S., Paquette, L., Ocumpaugh, J., Andres, J. M. A. L., ... Biswas, G. (2018). Expert feature-engineering vs. deep neural networks: Which is better for sensor-free affect detection?. In C. Rosé, R. Martínez-Maldonado, H. U. Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, ... B. du Boulay (Eds.), Proceedings of the 19th International Conference on Artificial Intelligence in Education (AIED 2018) (pp. 198–211). Cham, CH: Springer.

Crues, R. W., Bosch, N., Perry, M., Angrave, L., Shaik, N., & Bhat, S. (2018). Refocusing the lens on engagement in MOOCs. In R. Luckin, S. Klemmer, & K. R. Koedinger (Eds.), Proceedings of the 5th ACM Conference on Learning@Scale (L@S 2018) (pp. 1–10). New York, NY: ACM.

Bosch, N., & Paquette, L. (2017). Unsupervised deep autoencoders for feature extraction with educational data. Deep Learning with Educational Data Workshop at the 10th International Conference on Educational Data Mining.

Monkaresi, H., Bosch, N., Calvo, R. A., & D'Mello, S. K. (2017). Automated detection of engagement using video-based estimation of facial expressions and heart rate. IEEE Transactions on Affective Computing, 8(1), 15–28.

Bosch, N., D'Mello, S. K., Ocumpaugh, J., Baker, R. S., & Shute, V. (2016). Using video to automatically detect learner affect in computer-enabled classrooms. ACM Transactions on Interactive Intelligent Systems (TiiS), 6(2), 17:1–17:26.

Kai, S., Paquette, L., Baker, R., Bosch, N., D'Mello, S. K., Ocumpaugh, J., ... Ventura, M. (2015). Comparison of face-based and interaction-based affect detectors in physics playground. In C. Romero, M. Pechenizkiy, J. Boticario, & O. Santos (Eds.), Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015) (pp. 77–84). International Educational Data Mining Society.

Rodeghero, P., McMillan, C., McBurney, P. W., Bosch, N., & D'Mello, S. K. (2014). Improving automated source code summarization via an eye-tracking study of programmers. Proceedings of the 36th International Conference on Software Engineering (ICSE 2014) (pp. 390–401). New York, NY: ACM.

Bosch, N., D'Mello, S. K., & Mills, C. (2013). What emotions do novices experience during their first computer programming learning session?. In H. C. Lane, K. Yacef, J. Mostow, & P. Pavlik (Eds.), Proceedings of the 16th International Conference on Artificial Intelligence in Education (AIED 2013) (pp. 11–20). Berlin, Heidelberg: Springer.