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Creators/Authors contains: "Yang, T."

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  1. ; ; ; ; ; ; ; ; ; ; et al ( , Acta Materialia)
    Free, publicly-accessible full text available September 1, 2025
  2. ; ; ; ; ; ; ; ; ; ; et al ( , Journal of Materials Science & Technology)
    Full Text Available 
  3. ; ; ( , International Conference on Artificial Intelligence and Statistics (AISTATS))
    Accepted Manuscript Full Text Available
  4. ; ; ( , The 26th International Conference on Artificial Intelligence and Statistics (AISTATS))
    Accepted Manuscript Full Text Available
  5. ; ; ; ; ; ; ; ; ( , Scripta Materialia)
    Full Text Available 
  6. ; ; ; ( , Journal of machine learning research)
    Accepted Manuscript Full Text Available
  7. ; ; ; ( , Journal of machine learning research)
    Accepted Manuscript Full Text Available
  8. ; ; ; ; ( , Proceedings of the Twenty-third International Conference of the Learning Sciences—ICLS 2023)
    Bilkstein, P. ; Van Aaist, J. ; Kizito, R. ; Brennan, K. (Ed.)
    MedDbriefer allows paramedic students to engage in simulated prehospital emergency care scenarios and receive an automated debriefing on their performance. It is a web-based tool that runs on a tablet. Although debriefing is purported to be one of simulation-based training’s most critical components, there is little empirical research to guide human and automated debriefing. We implemented two approaches to debriefing in MedDbriefer and are conducting a randomized controlled trial to compare their effectiveness. 
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    Accepted Manuscript Full Text Available
  9. ; ; ; ; ( , Neural Processing Information Systems)
    Accepted Manuscript Full Text Available
  10. ; ; ; ( , Journal of laboratory chemical education)
    Accepted Manuscript Full Text Available