Isdt 2012 presentation

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Dr. Stefan Mol's presentation about the exploitation directions of the OntoHR project

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Isdt 2012 presentation

  1. 1. Integrating Knowledge Management in the Context of Evidence Based Learning:Two concept models for facilitating the assessment and acquisition of job knowledge Stefan T. Mol Gabor Kismihok Fazel Ansari Mareike Dornhöfer May 13th 2012 ISDT 2012, Mallorca, Spain
  2. 2. Contents• Context• The Med-Assess Concept• The Meta Practitioner Concept• Challenges• Synthesis• Questions / comments
  3. 3. Point of departure“…people who are more intelligent learnmore job knowledge and learn it faster, themajor determinant of job performance isnot GMA but job knowledge” (Schmidt andHunter, 2001). Job GMA Job knowledge Performance
  4. 4. Job Knowledge: A tentative definitionThe oftentimes job idiosyncratic and specificallydefined know-how or evidence that is requiredof and by the job-holder to make sounddecisions and thereby demonstrate successfuljob performance.
  5. 5. Job Knowledge Substantiation1 2 3 4 5 6 7 8 9 9 8 7 6 5 4 3 2 1 Job Knowledge Specificity Job Performance Specificity
  6. 6. Introducing Med-Assess• MED-ASSESS is a personnel selection and training platform that takes an individualized approach to the assessment and development of job specific knowledge.• Based on cutting edge semantic technology, MED-ASESS provides detailed personalized assessment and training of essential technical competencies and related job knowledge elements that are required for a particular job.
  7. 7. What will MED-ASSESS offer?• General Mental Ability test• Customizable, adaptive job knowledge test for medical employees (e.g., ward nurses, medical imaging nurses)• Applicant ranking based on integrated Job Knowledge and GMA test performance• Automatic and tailored e-Learning content delivery on the basis of test results• Cutting-edge semantic technology for job knowledge structuring, testing, and evaluation
  8. 8. Benefits of MED-ASSESS to Organizations• Efficient applicant screening• Greater person – job fit.• Cuts in selection and initial training costs• Fully customizable tests and training modules• Based on ONTO-HR (see www.ontohr.eu)
  9. 9. Benefits of MED-ASSESS to individuals• Easy to access, online interface• Easy to use and straightforward test environment• Comprehensive presentation of results• Personalized learning plan for knowledge deficiencies• Fair and ethical testing
  10. 10. The MED-ASSESS ConceptUndeniably Job General Unequivocally Job Specific (albeit more portable for more related occupations) Job Job GMA Knowledge Performance Education Job Specific – Job General
  11. 11. The META-PRACTITIONER Concept Unequivocally Job Specific (albeit more portable for more related occupations) Job Job Knowledge Performance Education Job Specific – Job General
  12. 12. Evidence based management…is based on the belief that facing the hardfacts about what works and what doesn’t,understanding the dangerous half-truths thatconstitute so much conventional wisdom aboutmanagement, and rejecting the total nonsensethat too often passes for sound advice will helporganizations perform better. Pfeffer & Sutton (2006)
  13. 13. Meta-Practitioner• Aimed at facilitating practitioner access to academically accrued evidence through the automated conduct of meta-analysis
  14. 14. Systematic Reviews: Meta-analysisMeta-analysis is a statistical technique ofsummarizing and aggregating the findings oflarge numbers of previous investigations intothe strength of the relationship between two ormore variables (for instance the correlationbetween general mental ability and jobperformance).
  15. 15. Systematic Reviews: Meta-analysis Shaffer et al. 2006
  16. 16. Conclusions• The importance and centrality of job knowledge in today’s knowledge based economy is undeniable• Multidisciplinary approaches are needed to tackle the challenges inherent to modeling job knowledge
  17. 17. Research challenges– both systems are currently mainly concerned with explicit knowledge that has in some way shape or form been documented. One challenge that awaits here is facilitating the automated processing and mapping into the ontologies of such knowledge.– It should be recognized that job incumbents are likely to have significant know-how, and incorporating this latent knowledge into either system will be another significant challenge.
  18. 18. Research challengesTechnological challenges:– (semi) automated ontology development– Content development– Validation– Integration • Into existing learning environments • With educational programs– Engaging stakeholders
  19. 19. Job Knowledge as Matchmaker• Connecting: – HRM, eLearning & Knowledge Management (foster collaboration) – Academia and industry (Science and practice) – Employees and workplaces (Enhanced Matching) – Policy and Education (Training) – Government and Labor Market (Needs analysis) http://www.ontohr.eu
  20. 20. Dr. Stefan T. MolAssistant Professor in Organizational BehaviorRm. M-2.36 | Plantage Muidergracht 121018 TV Amsterdam | The NetherlandsT +31 20 525 5490 | F +31 20 525 4182E s.t.mol@uva.nl | I www.abs.uva.nl/pp/stmol

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