title: Structuring feedback and debriefing to achieve mastery learning goals.
abstract: Mastery learning is a powerful educational strategy in which learners gain knowledge and skills that are rigorously measured against predetermined mastery standards with different learners needing variable time to reach uniform outcomes. Central to mastery learning are repetitive deliberate practice and robust feedback that promote performance improvement. Traditional health care simulation involves a simulation exercise followed by a facilitated postevent debriefing in which learners discuss what went well and what they should do differently next time, usually without additional opportunities to apply the specific new knowledge. Mastery learning approaches enable learners to "try again" until they master the skill in question. Despite the growing body of health care simulation literature documenting the efficacy of mastery learning models, to date insufficient details have been reported on how to design and implement the feedback and debriefing components of deliberate-practice-based educational interventions. Using simulation-based training for adult and pediatric advanced life support as case studies, this article focuses on how to prepare learners for feedback and debriefing by establishing a supportive yet challenging learning environment; how to implement educational interventions that maximize opportunities for deliberate practice with feedback and reflection during debriefing; describing the role of within-event debriefing or "microdebriefing" (i.e., during a pause in the simulation scenario or during ongoing case management without interruption), as a strategy to promote performance improvement; and highlighting directions for future research in feedback and debriefing for mastery learning.
authors.affiliation: W.J. Eppich is associate professor of pediatrics and medical education, Northwestern University Feinberg School of Medicine, Chicago, Illinois. E.A. Hunt is associate professor of anesthesiology and critical care medicine and of health science informatics and pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland. J.M. Duval-Arnould is instructor of anesthesiology and critical care medicine and of health sciences informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland. V.J. Siddall is simulation clinical educator and research assistant, Stritch School of Medicine, Loyola University, Maywood, Illinois. A. Cheng is associate professor of pediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
authors.forename: Walter J
authors.initials: WJ
authors.lastname: Eppich
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Hunt
authors.forename: Jordan M
authors.initials: JM
authors.lastname: Duval-Arnould
authors.forename: Viva Jo
authors.initials: VJ
authors.lastname: Siddall
authors.forename: Adam
authors.initials: A
authors.lastname: Cheng
mesh_terms: D002983:Clinical Competence; D003479:Curriculum; D004503:Education, Medical, Graduate / Q000379:methods*; D004521:Educational Measurement / Q000379:methods*; D005246:Feedback; D006801:Humans; D007388:Internal Medicine / Q000193:education*; D007858:Learning; D008020:Life Support Care / Q000592:standards*; D017145:Models, Educational; D010372:Pediatrics / Q000193:education*