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Investigating Shared Leadership in Undergraduate Capstone Design Teams: A Pilot Study

Investigating Shared Leadership in Undergraduate Capstone Design Teams: A Pilot Study. LTC Brian J. Novoselich, West Point, Virginia Tech Dr. David B. Knight, Department of Engineering Education, Virginia Tech. Research Team. Dr. David Knight. LTC Brian Novoselich. EDUCATION

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Investigating Shared Leadership in Undergraduate Capstone Design Teams: A Pilot Study

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  1. Investigating Shared Leadership in Undergraduate Capstone Design Teams: A Pilot Study LTC Brian J. Novoselich, West Point, Virginia Tech Dr. David B. Knight, Department of Engineering Education, Virginia Tech

  2. Research Team Dr. David Knight LTC Brian Novoselich • EDUCATION • Ph.D. Higher Education, Pennsylvania State University, 2012 • M.S. Environmental Sciences, University of Virginia, 2009 • M.U.E.P Urban and Environmental Planning, University of Virginia, 2009 • B.S. Environmental Sciences, University of Virginia, 2006 • EDUCATION • M.S. Mechanical Engineering, The University of Texas at Austin, 2006 • B.S. Mechanical Engineering, United States Military Academy, 1996

  3. Call for Leaders • Leadership is essential to long term tech success: • Growing interdependence of technological/ economic/ social functions “demands” technologically adept leaders to make sound policy decisions for a sustainable future. NAE (2004) • ABET Leadership requirements for Civil Engineering/ Construction Engineering/ Engineering Management & Overall Teaming Requirements. • “an engineer is hired for her or his technical skills, fired for poor people skills, and promoted for leadership and management skills” Russel and Yao (1996).

  4. Team Leadership • Leadership is an important component of team success: • “most would agree that team leaders and the leadership processes that they enact are essential to promoting team performance, adaptation, and effectiveness” Salas et. al. (2007). • Lack of Eng. Ed. Focus on leadership for effective teams. • Borrego et al. (2014) literature review:

  5. Faculty Perceptions • Non-purposeful treatment of leadership within the curriculum. • Knight & Novoselich (2014): Analysis of nationally representative undergrad engineering data set (P2P, 2008) • Is our conceptualization of design team leadership accurate?

  6. Shared Leadership • The shared paradigm is changing perceptions of leadership • Historical leadership perceptions are individual and hierarchical. • Shared leadership can be more effective in knowledge work that is: Creative, Complex, Interdependent. i.e. Pearce (2004). • Shared Leadership: “a simultaneous, ongoing, mutual influence process within a team that is characterized by ‘serial emergence’ of official as well as unofficial leaders” Pearce (2004).

  7. Theoretical framework (Northouse, 2013, p. 194)

  8. To what degree are transactional and transformational leadership shared within undergraduate engineering student design teams? • How is the degree of shared leadership related to undergraduate engineering student design team effectiveness? • What role does faculty involvement play in undergraduate engineering student design team leadership and outcomes? • Initial focus on Senior, ME Capstone design teams: • Design Pervasiveness in ME • Seniors at height of “expertise” Research Questions

  9. Research Design Sequential Explanatory Research Design (Creswell, 2009) Degree of Shared Leadership Correlation of sharedness to outcomes/effectiveness Advisor Role Leadership Scales Interviews • Survey • MLQ • Control Var. • Dep. Variables Sociograms Course Documents • How/Why Leadership Developed • Team performance/outcomes Network Centralization Pilot Study Scope

  10. Current Status • Pilot data collection on-going: • ME specific capstones. • Virginia Tech (population=350, responses =221, teams=61) • Fall: complete. • Spring: to initiate. • West Point (population=108, teams=18) • Spring: on-going. • Preliminary factor analysis completed. • Three teams from VT fall data analyzed.

  11. Factor Analysis • 221 students. • Peer ratings treated as individual cases. • Resulted in 1460 total cases. • EFA conducted in SPSS. Anticipated Scales Intellectual Stimulation Individualized Concern Transformational Leadership Idealized Influence (B/A) Inspirational Motivation Contingent Reward Transactional Leadership Management by Exception (A) Management by Exception (P) Laissez Faire Laissez Faire

  12. Factor Analysis • Eigen Values supported 5 Scales. • 3, 5, and 9 Scales Explored • Principal Axis and Maximum Likelihood. • Oblimin Rotation. • Construct generally held across 3 and 5. Discovered Scales Intellectual Stimulation Individualized Concern Non-Corrective Leadership Transformational Leadership (Re-named from Transformational Leadership) Idealized Influence (B/A) (-) Inspirational Motivation Contingent Reward (Re-named from Transactional Leadership) Corrective Leadership Transactional Leadership Management by Exception (A) (+) Management by Exception (P) (Re-named from Laissez Faire) Delayed Leadership Laissez Faire Laissez Faire

  13. Out Degree Centralization “Star Network” “Linear Network” 0 0 0 0 4 2 0 0 1 1 High Centrality Variation: 1@4, 4@0 Out Degree Centralization= Sc2= 1 Low Centrality Variation: 1@2, 2@1, 2@0 Out Degree Centralization = Sc2 = 0.375 (i.e. shared leadership) (i.e. individual leadership) (Mayo et al. 2003)

  14. Delayed Corrective Non-Corrective Member 3 (0.00) Advisor (0.00) Member 2 (0.00) Member 1 (0.00) Team Summary Centralization: 0.333 Centralization: 0.444 Centralization: 0.375 Centralization: 0.3125 Centralization: 0.167 Centralization: 0.250 Note: Link cutoff set to 3.00

  15. Team 156 Summary Non-Corrective Corrective Centralization: 0.167 Centralization: 0.250 Delayed Note: Link cutoff set to 3.00

  16. Take Aways • Teams are showing varying degrees of centralization. • Leadership may be unique for design teams. • Full team participation is challenging. • Survey fatigue may be an issue. • Skewed centrality for Advisor.

  17. Next steps • Incorporate spring survey data. • Initial correlation of network centralization to team outcomes. • Assess likelihood of adequate participation. • Increase research sites.

  18. Questions?

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