Surgeons as Educators A Guide for Academic Development and Teaching Excellence

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  1. Stefanidis D, Korndorffer JJ, Heniford B, Scott D.  Limited feedback and video tutorials
    optimize learning and resource utilization during laparoscopic simulator training. Surgery.
    2007;142(2):202–6.

  2. Perone J, Fankhauser G, Adhikari D, Mehta H, Woods M, Strohmeyer J, et al. Who did the
    case? Perceptions on resident operative participation. Am J Surg. 2017;213(4):821–6.

  3. Morgan R, Kauffman DF, Doherty G, Sachs T. Resident and attending perceptions of resident
    involvement: an analysis of ACGME reporting guidelines. J Surg Educ. 2016;74(3):415–22.

  4. Reznick RK. Teaching and testing technical skills. Am J Surg. 1993;165(3):358–61.

  5. Williams RG, Klamen DA, McGaghie WC.  Cognitive, social and environmental sources of
    bias in clinical performance ratings. Teach Learn Med. 2003;15(4):270–92.

  6. Gundle K, Mickelson D, Hanel D. Reflections in a time of transition: orthopaedic faculty and
    resident understanding of accreditation schemes and opinions on surgical skills feedback. Med
    Educ Online. 2016;21(1):30584.

  7. Martin JA, Regehr G, Reznick R, Macrae H, Murnaghan J, Hutchison C, et al. Objective struc-
    tured assessment of technical skill (OSATS) for surgical residents. Br J Surg. 1997;84(2):273–8.

  8. Vassiliou MC, Feldman LS, Andrew CG, Bergman S, Leffondré K, Stanbridge D, et  al. A
    global assessment tool for evaluation of intraoperative laparoscopic skills. Am J Surg.
    2005;190(1):107–13.

  9. Goh AC, Goldfarb DW, Sander JC, Miles BJ, Dunkin BJ.  Global evaluative assessment of
    robotic skills: validation of a clinical assessment tool to measure robotic surgical skills. J Urol.
    2012;187(1):247–52.

  10. Hogg M, Zenati M, Novak S, Chen Y, Jun Y, Steve J, et al. Grading of surgeon technical per-
    formance predicts postoperative pancreatic fistula for Pancreaticoduodenectomy independent
    of patient-related variables. Ann Surg. 2016;264(3):482–91.

  11. Shah J, Darzi A. Surgical skills assessment: an ongoing debate. BJU Int. 2001;88(7):655–60.

  12. Holst D, Kowalewski TM, White LW, Brand TC, Harper JD, Sorensen MD, et  al. Crowd-
    sourced assessment of technical skills: differentiating animate surgical skill through the wis-
    dom of crowds. J Endourol. 2015;29(10):1183–8. 150413093359007

  13. Stefanidis D, Arora S, Parrack DM, Hamad GG, Capella J, Grantcharov T, et  al. Research
    priorities in surgical simulation for the 21st century. Am J Surg. 2012;203(1):49–53.

  14. Greenberg CC, Ghousseini HN, Pavuluri Quamme SR, Beasley HL, Wiegmann
    DA.  Surgical coaching for individual performance improvement. Ann Surg [Internet].
    2015;261(1). Available from: http://journals.lww.com/annalsofsurgery/Fulltext/2015/01000/
    Surgical_Coaching_for_Individual_Performance.8.aspx.

  15. Greenberg C, Dombrowski J, Dimick J. Video-based surgical coaching: an emerging approach
    to performance improvement. JAMA Surg [Internet]. 2016;151(3):282–3. Available from:
    https://doi.org/10.1001/jamasurg.2015.4442.

  16. Howe J.  The rise of crowdsourcing. Wired Mag [Internet]. 2006;14(6):1–5. Available from:
    http://www.clickadvisor.com/downloads/Howe_The_Rise_of_Crowdsourcing.pdf.

  17. Garrigos-Simon FJ, Gil-Pechuán I, Estelles-Miguel S.  Advances in crowdsourcing. Cham:
    Springer; 2015. p. 1–183.

  18. Brabham DC.  Crowdsourcing as a model for problem solving: an introduction and cases.
    Converg Int J Res into New Media Technol. 2008;14(1):75–90.

  19. Lévy P.  Collective intelligence: Mankind’s emerging world in cyberspace [internet].
    Challenges. 1997:277 p. Available from: http://portal.acm.org/citation.cfm?id=550283

  20. Ipeirotis P. Demographics of mechanical turk. Working Paper CeDER-10-01. 2010. http://hdl.
    handle.net/2451/29585

  21. Ranard BL, Ha YP, Meisel ZF, Asch DA, Hill SS, Becker LB, et  al. Crowdsourcing  – har-
    nessing the masses to advance health and medicine, a systematic review. J Gen Intern Med.
    2014;29:187–203.

  22. Cooper S, Khatib F, Treuille A, Barbero J, Lee J, Beenen M, et al. Predicting protein structures
    with a multiplayer online game. Nature. 2010;466:756–60.

  23. Kawrykow A, Roumanis G, Kam A, Kwak D, Leung C, Wu C, et al. Phylo: a citizen science
    approach for improving multiple sequence alignment. PLoS One. 2012;7(3):e31362.


6 Crowdsourcing and Large-Scale Evaluation

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