Open2012 measuring-what-matters-unger


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Open2012 measuring-what-matters-unger

  1. 1. Measuring what matters in teaching innovation March 2012 Darian Unger, Ph.D. Associate Professor Howard University School of Business 202-806-1656
  2. 2. Research Topic• Purpose – To better assess whether students understand and can apply key innovation concepts and skills• Methodology – Comparison of course objectives to performance on actual innovation and commercialization projects – Feedback from inventors, professors, and innovation-oriented MBA students
  3. 3. Research Topic• Literature review – Technological innovation as “introducing a new device, method, or material for application to commercial or practical objectives (Schilling, 2010) – Assessment as the “new reality” at colleges and universities (Pelimeni and Iorgulescu, 2009) • Assessments are helpful in facilitating replicable models, but should not be an exclusive focus because of several difficulties (Klein, 2005; Schmoker, 2002)
  4. 4. Research Topic• Findings – Assessing innovation education is harder than it looks (and it never looked easy) – Traditional assessments are insufficient – Most promising assessments include • evaluations of project based innovation and commercialization plans • innovator-based evaluations of utility
  5. 5. Drivers for this work• Necessity may be the mother of invention, but in this case…• Inventions themselves drove the need for an innovation & tech. mgmt. course
  6. 6. Drivers for this work• Development of new courses on innovation management, technology strategy, and sustainable business at Howard University
  7. 7. Key course skills and lessons: commercializing innovation• Creating value through innovation• Technology & market adoption S-curves• Categories and patterns of innovation• (Sources of) creativity• New product design and development• Tech strategies to protect & exploit innovation – Dominant designs, patents, and licensing – 1st and 2nd mover advantages
  8. 8. …along with other skills (and traits)• Ability to communicate Evaluated, – Writing (business plans) but also – Group dynamics common to other – Listening (customer needs) subjects – Speaking (persuasion)• Tenacity – Edison’s “stick-to-it-iveness” Not evaluated• Propensity for risk
  9. 9. Assessable methods or demonstrations1) Concept identification2) Recognition of a historical parallel or previous application3) Evaluation of performance on specific exercises or problems4) Actual project synthesis – case
  10. 10. Ability to assess Value Type S- (Sources New Prod. of of Curves of) Creativity Design/Dev. innov innovConcept ID      Historic orprior apps.      Exercise/Problem      Projectsynthesis      
  11. 11. Example• Technology and adoption S-curves – Objective assessment of how they can be identified and distinguished (Exams) – Many prior examples in different industries available (Discussions) – Gradable time-series problems and numerical exercises – But since S-curves are often descriptive rather than prescriptive, S-curve skills or knowledge are more difficult to assess on actual, ongoing projects
  12. 12. Adoption in practice% adoption of key technologies in U.S.
  13. 13. How to assess these individually?• Hard quantities – #’s of patents and licenses – % scores on exams• Softer quantitative measures – Innovator assessments of student assistance and insight• Quantified subjective measures – Student evaluations• Creativity and tenacity are subjective, unquantified, and unassessed
  14. 14. Findings and Implications• Findings – Assessing innovation education is difficult, because traditional assessments are insufficient – Categorization helps (i.e. between skills and traits) – Multiple forms of assessment necessary, including • evaluations of project based innovation and commercialization plans • innovator-based evaluations of utility
  15. 15. Questions and Suggestions?
  16. 16. Innovation models Sales Time Adoption TimeS-curve and adoption models (1965 and 1986)
  17. 17. Innovation models Creates new markets and/or breaks down existing market linkages Niche Architectural creation innovationReinforces existing Makes existingcompetence within competence withintechnology technology obsolete Regular Revolutionary innovation Innovation Reinforces existing market linkages Abernathy and Clark model (1985)
  18. 18. Innovation models Great impacts on links between components Architectural Radical innovation innovationLittle impact on Great impact on components components Incremental Modular innovation Innovation Little impact on links between components Henderson model (1990)
  19. 19. Innovation modelsAfuah and Bahram model (1995)
  20. 20. Innovation modelsChristensen models (1997 and 2003)
  21. 21. Assessment modes Exam Discussion ProjectConcept ID   Synth or HistoricApplication   Exercise/Problem   Repetition   Projectsynthesis   
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