Machine Learning
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Developer Behaviors in Validating and Repairing LLM-Generated Code Using IDE and Eye Tracking
Tang, N., Chen, M., Ning, Z., Bansal, A., Huang, Y., McMillan, C., Li, T.J.-J., “Developer Behaviors in Validating and Repairing LLM-Generated Code Using IDE and Eye Tracking,” Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC, 2024, pp. 40-46, DOI: 10.1109/VL/HCC60511.2024.00015. Read MoreNov. 21, 2024
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Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions
Zhang, Y.; Huang, Y.; Rosen, A.; Jiang, L.G.; McCarty, M.; RoyChoudhury, A.; Han, J.H.; Wright, A.; Ancker, J.S.; Steel, P.A.D. “Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions.” PLOS Digital Health, Volume 3, Issue… Read MoreNov. 21, 2024
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A multimodal approach to support teacher, researcher and AI collaboration in STEM+C learning environments
Cohn, C.; Snyder, C.; Fonteles, J.H.; Ashwin, T.S.; Montenegro, J.; Biswas, G. “A multimodal approach to support teacher, researcher and AI collaboration in STEM+C learning environments.” British Journal of Educational Technology, 2024, DOI: 10.1111/bjet.13518. Advances in generative AI and multimodal learning analytics… Read MoreNov. 21, 2024