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Desitra: A Simulator for Teaching Situated Decision Making in Dental Surgery

Published:07 March 2016Publication History

ABSTRACT

Use of simulation to teach decision making in surgery is challenging partly due to the situated nature of the decisions, with situation awareness playing a critical role in making high quality decisions. Thus simulation systems need to be able to provide the key cues needed in making decisions with high fidelity. In this paper we present the first version of Desitra, a simulation environment for teaching decision making in dental surgery. System design was driven by an observational study of teaching sessions for endodontic surgery in the operating room which identified perceptual cues used in decision making as well as tutorial intervention strategies used by surgeons. Desitra provides an open environment for learning decision making -- students carry out dental procedures and are free to make mistakes. The pedagogical module monitors the student actions and intervenes when students make mistakes, providing as little guidance as necessary to keep students on a productive learning path. The system is implemented to run on Android tablets to be maximally accessible. Preliminary evaluation of the system shows that Desitra effectively captures key perceptual cues.

References

  1. Dana K Andersen. 2012. How can educators use simulation applications to teach and assess surgical judgment? Academic Medicine?: Journal of the Association of American Medical Colleges 87, 7: 934--41.Google ScholarGoogle ScholarCross RefCross Ref
  2. Joseph Beck, Mia Stern, and Erik Haugsjaa. 1996. Applications of AI in education. Crossroads 3, 1: 11--15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A W Evans. 2001. Assessing competence in surgical dentistry. British Dental Journal 190, 7: 343--346.Google ScholarGoogle ScholarCross RefCross Ref
  4. R. Flin, S. Yule, S. Paterson-Brown, N. Maran, D. Rowley, and G. Youngson. 2007. Teaching surgeons about non-technical skills. The Surgeon 5, 2: 86--89.Google ScholarGoogle ScholarCross RefCross Ref
  5. Michael G Flowers and Rajesh Aggarwal. 2014. Second LifeTM : a novel simulation platform for the training of surgical residents. Expert review of medical devices 11, 2: 101--103.Google ScholarGoogle Scholar
  6. Linnea S. Hauge, Jeanne A. Wanzek, and Constantine Godellas. 2001. The reliability of an instrument for identifying and quantifying surgeons' teaching in the operating room. The American Journal of Surgery 181: 333--337.Google ScholarGoogle ScholarCross RefCross Ref
  7. Dana T Lin, Julia Park, Cara a Liebert, and James N Lau. 2015. Validity evidence for Surgical Improvement of Clinical Knowledge Ops: a novel gaming platform to assess surgical decision making. The American Journal of Surgery 209, 1: 79--85.Google ScholarGoogle ScholarCross RefCross Ref
  8. Indira Padayachee. 2002. Intelligent tutoring systems: Architecture and characteristics. Proceedings of the 32nd Annual SACLA Conference.(Cité p. 2), August: 1--8.Google ScholarGoogle Scholar
  9. Vanessa N Palter and Teodor P Grantcharov. 2010. Simulation in surgical education. Canadian Medical Association Journal 182, 11: 1191--1196.Google ScholarGoogle ScholarCross RefCross Ref
  10. Vanash M. Patel, Oliver Warren, Kamran Ahmed, et al. 2011. How can we build mentorship in surgeons of the future? ANZ Journal of Surgery 81, 6: 418--424.Google ScholarGoogle ScholarCross RefCross Ref
  11. Sudip K. Sarker, Saif Rehman, Meera Ladwa, Avril Chang, and Charles Vincent. 2009. A decisionmaking learning and assessment tool in laparoscopic cholecystectomy. Surgical Endoscopy 23, 1: 197--203.Google ScholarGoogle ScholarCross RefCross Ref
  12. Elliot L Servais, Wayne W Lamorte, Suresh Agarwal, Wayne Moschetti, Sandeep K Mallipattu, and Steven L Moulton. 2006. Teaching surgical decision-making: an interactive, web-based approach. The Journal of Surgical Research 134, 1: 102--106.Google ScholarGoogle ScholarCross RefCross Ref
  13. Nick Sevdalis, Rosamond Jacklin, and Charles Vincent. 2012. Surgical Decision-Making: A Multimodal Approach. In Safer Surgery: Analysing Behaviour in the Operating Theatre, Rhona Flin and Lucy Mitchell (eds.). Ashgate, 353--340.Google ScholarGoogle Scholar
  14. Robert A. Sottilare and Stephen Gilbert. 2011. Considerations for adaptive tutoring within serious games: authoring cognitive models and game interfaces.Google ScholarGoogle Scholar
  15. Frederick Spencer. 1978. Teaching and measuring surgical techniques: the technical evaluation of competence. Bull Am Coll Surg 63, 3: 9--12.Google ScholarGoogle Scholar
  16. Linh N Tran, Priyanka Gupta, Lauren H Poniatowski, Shaheen Alanee, Marc a Dalléra, and Robert M Sweet. 2013. Validation study of a computer-based open surgical trainer: SimPraxis(®) simulation platform. Advances in medical education and practice 4: 23--30.Google ScholarGoogle Scholar
  17. Shawn Tsuda, Daniel Scott, Jennifer Doyle, and Daniel B Jones. 2009. Surgical skills training and simulation. Current problems in surgery 46, 4: 271--370.Google ScholarGoogle Scholar
  18. Jamie Tsui and Stanford Edtech. 2014. Septris and SICKO: Implementing and Using Learning Analytics and Gamification in Medical Education. Educause, March: 1--7.Google ScholarGoogle Scholar
  19. Narumol Vannaprathip, Peter Haddawy, and Siriwan Suebnukarn. 2015. A Preliminary Analysis of Tutorial Intervention Strategies for Teaching Decision Making in Dental Surgery. Proceedings of the 2nd International Conference on Innovation in Education., 382--390.Google ScholarGoogle Scholar
  20. Kyle R. Wanzel, Myléne Ward, and Richard K. Reznick. 2002. Teaching the surgical craft: From selection to certification. Current Problems in Surgery 39, 6: 583--659.Google ScholarGoogle ScholarCross RefCross Ref

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          cover image ACM Conferences
          IUI '16: Proceedings of the 21st International Conference on Intelligent User Interfaces
          March 2016
          446 pages
          ISBN:9781450341370
          DOI:10.1145/2856767

          Copyright © 2016 ACM

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          Publication History

          • Published: 7 March 2016

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          IUI '16 Paper Acceptance Rate49of194submissions,25%Overall Acceptance Rate746of2,811submissions,27%

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