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Course: APPL 650 Practical Applications in I/O Psychology

Course: APPL 650 Practical Applications in I/O Psychology. Tom Mitchell, U. of Baltimore, (Instructor) Div of Applied Psychology & Quant Methods Tmitchell@ubalt.edu http://home.ubalt.edu/tmitch Mike Sturman, Cornell U. (Data generator)

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Course: APPL 650 Practical Applications in I/O Psychology

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  1. Course: APPL 650 Practical Applications in I/O Psychology • Tom Mitchell, U. of Baltimore, (Instructor) • Div of Applied Psychology & Quant Methods • Tmitchell@ubalt.edu • http://home.ubalt.edu/tmitch • Mike Sturman, Cornell U. (Data generator) • Organizational Mgt, Communication, and Law • mcs5@cornell.edu U. Baltimore / 3rd Annual Teaching

  2. Capstone Course in I/O ΨU. of Baltimore M.S. in Applied Ψ • M.S. Curriculum in I/O (42 hours) • Personnel (I): • Job analysis / personnel / assessment • Organizational (O): • Org psych / mot-sat-leadership • Core: • Research methods / stats U. Baltimore / 3rd Annual Teaching

  3. Capstone Course objectives • Apply SKAs to real HR problems • Integrate knowledge from I and O Ψ • Bridge gap between theory and practice • Gain experiential teamwork experience • Demonstrate competencies U. Baltimore / 3rd Annual Teaching

  4. Competencies Demonstrated • Core SKAs: • Conduct job analysis • Develop performance appraisal • Develop employee selection program • Assess employee morale • Analyze data • Software utilization • Communication / Interpersonal skills: • Report writing • Oral presentation of findings • Teamwork skills U. Baltimore / 3rd Annual Teaching

  5. Course Characteristics • Real problems • Mundane realism • Experimental realism • Dynamic: projects • Change over time • Progress over time • Interactive: Information exchange • Client <-> Instructor <-> Team U. Baltimore / 3rd Annual Teaching

  6. Course format • Applied Psychology Consultants Inc.APC, Inc. (virtual consulting firm) • Instructor(s) = Senior consultant • Students = Junior consultant • Three projects each (sel/pa/sat) • Team Leader on one of projects U. Baltimore / 3rd Annual Teaching

  7. Course format (con’t) • Cases: Real world orgs (disguised) • From consulting work • Projects tailored to fit problem • Each Team: • Assess problem • Generate solutions • Implement solutions • Write report / present to mgt U. Baltimore / 3rd Annual Teaching

  8. Course Format (dynamic/interactive) • Instructor responds / reacts • to identified problems • changes/redirects (via memos) • to proposed solutions • to interventions • Provides • simulated feedback (data) • To confirm/disconfirm hypotheses • critique / recommendations U. Baltimore / 3rd Annual Teaching

  9. Course Materials • Course des • Client Organizations • Case Assignments • Assessment U. Baltimore / 3rd Annual Teaching

  10. Tech Tools • MS Office: Word/Excel/Ppoint • SPSS • Webboard / email • Data generator U. Baltimore / 3rd Annual Teaching

  11. DataSim (Mike Sturman) • Visual Basic program • Creates data sets to user specifications • Saves simulation / data U. Baltimore / 3rd Annual Teaching

  12. DataSim (Sturman) • N up to 10,000 cases • Eleven constructs • Correlation matrix (user specified) • Variable characteristics (user specified) U. Baltimore / 3rd Annual Teaching

  13. DataSim (Sturman) • Constructs • Number of items (vars) • Reliability (internal consistency) • Construct characteristics can be: • Normal (continuous) • Categorical (2 – 12) • Custom continuous U. Baltimore / 3rd Annual Teaching

  14. Item types & char • Normal continuous • Min/max/ mean/ sd • Truncate / winsorize • Categorical • 2 to 12 • Proportion of each category • Custom - continuous • Median / sd • Skew level (+ to -) • Tail elongation U. Baltimore / 3rd Annual Teaching

  15. Project Process: Team • Identifies problem • Formulates hypotheses • Develops assessment plan • Requests data from org • Develops or finds existing measures (tests/inventory/survey) • Creates SPSS data structure / parameters U. Baltimore / 3rd Annual Teaching

  16. Project Process: Instructor • Accepts or recommends changing structure • Creates data set to Team specs • To confrim/disconfirm hypotheses • Returns completed data set to team for analysis U. Baltimore / 3rd Annual Teaching

  17. Project Process: Team • Analyses data using SPSS • Incorporates results in report • Forwards report to Instructor for critique U. Baltimore / 3rd Annual Teaching

  18. Example: Sel3: Alum Alum Corp. • Selection of mid-managers • Concurrent Validation study • Demos: • Race/gender/education • Predictors: • WPT/WGCTA/CPI • Criteria: • Supervisor ratings U. Baltimore / 3rd Annual Teaching

  19. Conclusion of Capstone Sim • Assesses student competencies • Requires integration of SKA • Experiential (mundane/exp realism • Provides student with portfolio item • Provides instructor with feedback strengths/weaknesses of curriculum U. Baltimore / 3rd Annual Teaching

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