Course: APPL 655 Practical Applications in I/O Psychology

1
Course APPL 655 Practical Applications in I/O
Psychology

• Tom Mitchell, U. of Baltimore, (Instructor)
• Div of Applied Psychology Quant Methods
• Tmitchell_at_ubalt.edu
• http//home.ubalt.edu/tmitch
• Mike Sturman, Cornell U. (Data generator)
• Organizational Mgt, Communication, and Law
  
  
  
• mcs5_at_cornell.edu [phone]

2
Capstone Course in I/O ?U. of Baltimore M.S. in
Applied ?

• 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

3
Capstone Course Objectives

• Apply SKAs to real HR problems
• Integrate knowledge from I and O ?
• Bridge gap between theory and practice
• Gain experiential teamwork experience
• Demonstrate competencies

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

5
Course Characteristics

• Real problems
• Mundane realism
• Experimental realism
• Dynamic projects
• Change over time
• Progress over time
• Interactive Information exchange
• Client lt-gt Instructor lt-gt Team

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

7
Course Format (cont)

• Cases Real world organizations (disguised)
• From consulting work
• Projects tailored to fit problem
• Each Team
• Assess problem
• Generate solutions
• Implement solutions
• Write report / present to mgt

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

9
Course Materials

• Course description
• Client organizations
• Case assignments
• Assessment

10
Tech Tools

• MS Office Word/Excel/Ppoint
• SPSS
• Webboard / email
• Data generator (DataSim)

11
DataSim (Mike Sturman)

• Visual Basic program
• Creates data sets to user specifications
• Saves simulation / data in txt file
• For import into Excel/SPSS/SAS/ etc.
• Importing existing data
• Add additional vars later

12
DataSim (Sturman)

• Unlimited number of
• Cases
• Constructs / variables
• Correlation matrix (user specified)
• Variable characteristics (user specified)

13
DataSim (Sturman)

• Constructs
• Number of items (vars)
• Reliability (internal consistency)
• Construct characteristics can be
• Normal (continuous)
• Categorical (2 12)
• Custom continuous

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

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

16
Project Process Instructor

• Accepts or recommends changing structure
• Creates data set to meet Team specs
• To confirm/disconfirm hypotheses
• Returns completed data set to team for analysis

17
Project Process Team

• Analyses data using SPSS
• Incorporates results in report
• Forwards report to Instructor for critique

18
Example Sel3 Alum Alum Corp.

• Selection of mid-managers
• Concurrent Validation study
• Demos
• Race/gender/education
• Predictors
• WPT/WGCTA/CPI
• Criteria
• Supervisor ratings

19
Conclusion of Capstone Sim

• Assesses student competencies
• Requires integration of SKAs
• Experiential (mundane/exp realism)
• Provides student with portfolio item
• Provides instructor with feedback
  strengths/weaknesses of curriculum

20
Uses of DataSim

• Research methods
• Simulate data for proposals
• Test pilot data for studies
• Statistics courses
• Create data sets for examples
• Assessment
• Develop unique data set for each student

21
Suggestions?

• For Capstone course?
• For DataSim?
• Other uses?
• What you would like it to do?