(209) Leadership Case Consultations as an Experiential Learning Tool for Leadership Development in the Classroom

Objective : This retrospective cohort study included students’ quantitative and qualitative assessments of a Leadership Case Consultation (LCC) activity involving application of leadership frameworks to solve real-world problems.

Methods: Based on a model used by the Harvard John F. Kennedy School of Government, LCCs were implemented at two colleges of pharmacy. Students applied their knowledge to address a real-world leadership problem as consultants from the perspectives of three or four frameworks including, Clifton Strengths®, Kotter’s 8 Steps, Heifetz’ Adaptive Leadership, and Kouzes and Posner’s Five Practices of Exemplary Leadership®. Descriptive statistics were used to analyze quantitative student assessment data and qualitative data were independently, blindly coded by 2 individuals, with adjudication and finalization of themes by a third reviewer.

Results: Mean student agreement that the LCC learning objectives were achieved ranged from 3.04-3.32 on a 4-point Likert scale, ranging from 1=Strongly Disagree to 4=Strongly Agree. “Expand your leadership development network” was the learning objective with the lowest level of agreement (88% Agreed or Strongly Agreed) and “Develop skills related to provision of quality feedback to resolve a challenge”with the highest level of agreement (96%). The most prevalently recurring themes from the qualitative analysis included “Increased perception of value of others’ perspectives,” “Value of supportiveness through shared experiences,” and “Increased appreciation of the complexity of solving leadership problems.” Student feedback also provided specific insights that can be used to optimize future iterations of LCCs.

Conclusions: LCCs represent an opportunity for teaching leadership development through experiential learning in the classroom. Findings from our student assessment data suggest it is a reasonable learning strategy, with some specific suggestions for optimizing future iterations.