Journal Articles
Korban, M., Youngs, P., & Acton, S. (in press). A semantic and motion-aware spatiotemporal transformer network for action detection. Transactions on Pattern Analysis and Machine Intelligence.
Foster, J. K., Korban, M., Youngs, P., Watson, G. S., & Acton, S. T. (2024). Automatic classification of activities in classroom videos. Computers and Education: Artificial Intelligence, 6, 100207
Korban, M., Youngs, P., & Acton, S. T. (2023a). TAA-GCN: A temporally aware adaptive graph convolutional network for age estimation. Pattern Recognition, 134, 109066.
|
Korban, M., Youngs, P., & Acton, S. (2023b). A multi-modal transformer network for action detection. Pattern Recognition, 142, 109713.
|
Book Chapters
Foster, J. K., Korban, M., Youngs, P., Watson. G. S., & Acton, S. (in press). Classification of instructional activities in classroom videos using neural networks. In X. Zhai & J. Krajcik (Eds.), The uses of AI in STEM education. Oxford University Press.
Conference Presentations
- Korban, M., Singh, S., Watson, G., Youngs, P., & Acton, S. T. (2021). AI-assisted pedagogical performance evaluation. Asilomar Conference on Signals, Systems and Computers. Pacific Grove, CA.
- Watson, G., Youngs, P., van Aswegen, R. Singh, S., & Acton, S. (2021). Automated classification of elementary instructional objects and activities: Analyzing consistency of manual annotations. Paper presented at the annual meeting of the American Educational Research Association.
- Youngs, P., Korban, M., Foster, J., Watson, G. S., & Acton, S. T. (2022). Using neural networks to identify instructional activities in elementary classrooms to support evaluation of instruction. American Educational Research Association. San Diego, CA.
- Crimmins, S., Foster, J. K., & Youngs, P. (2023). Supporting elementary teachers in noticing instructional activities: The Artificial Intelligence for Advancing Instruction (AIAI) dashboard. Paper presented at annual meeting of the American Educational Research Association, Chicago.
- Foster, J. K., Korban, M., Youngs, P. Watson, G. S., & Acton. S. (2023). Toward automated classroom observation: Classification of elementary instructional activities using neural networks. Paper presented at annual meeting of the American Educational Research Association, Chicago.
- Youngs, P., Crimmins, S. B., Foster, J., Korban, M., Watson, G. S., & Acton, S. T. (2023). Using neural networks to provide automated feedback on elementary mathematics instruction. Paper presented at the annual meeting of the American Society for Engineering Education. Baltimore, MD. Available Online