An Internet-based Tool for Collaboration Exercises and Research

1. An Internet-based Tool for Collaboration Exercises and Research Bill Klinger – Computer Science Dept.

2. Project Objectives Create web-based exercises to: • Facilitate team building • Teach team dynamics • Evaluate leadership styles • Have fun

3. Project Summary • Developed four collaboration exercises • over 25,000 lines of Java code • Wrote 53 pages of manuals/guides • Created PowerPoint slides for classes • Ran exercises for more than 225 students, faculty, staff

4. Recent Activities • Referenced by Boston University Center for Team Learning • Spoke at NJ Faculty Best Practices • Accepted for League Conference on Information Technology • Begun data collection and analysis

5. Exercises • Pattern Creation • The Maze • Collaborative Pong • Collaborative Driving

6. Some Qualitative Observations • Groups don’t start out working together • until they realize they must. • It takes time to learn how to work together • involves experimentation. • A group does not immediately learn from its first experience. • By the third exercise, groups start to collaborate from the beginning.

7. More Qualitative Observations • Groups communicate minimally • Most people are not leaders • Many leaders are reluctant leaders • Reluctant leaders often give general instructions, not specific ones (e.g. “someone go red”, “half go green”) • Groups will typically produce more creative output than would otherwise be created by a single individual. • Output is different than envisioned at the start • Group efficiency – creativity trade-off.

8. Quantitative Results • Collected data from all exercises • Detailed data collected since 11/04 • Initial analysis uses only maze game 0 • 9 data samples • Created linear regression models

9. Initial Regression Findings • Factors that do not appear to be significant: • age • education • sports team experience • artistic ability • math ability • birth order • where raised

10. Initial Regression Findings Factors that appear to be significant • Size of the group • Diversity • Gender composition

11. 2 Variables Model ElapTime = β0 + β1*NoPlyrs + β2*NoRaces

12. Model StatisticsTwo Variables Model Dependent variable: ElapTime VARIABLE COEFFICIENT STDERROR T STAT 2Prob(t > |T|) 0) const 443.943 150.624 2.947 0.025701 ** 7) NoPlyrs 55.1994 15.2056 3.630 0.010962 ** 52) NoRaces -146.386 51.3920 -2.848 0.029242 ** Unadjusted R-squared = 0.710329 Adjusted R-squared = 0.613772 F-statistic (2, 6) = 7.35657 (p-value = 0.0243)

13. Forecasts vs. ObservedTwo Variables

14. 4 Variables Model ElapTime = β0 + β1*NoPlyrs + β2*NoRaces + β3*PctFem + β4*PctFem2 PctFem2 = PctFem2 = Percent of females squared

15. Model StatisticsFour Variables Model Dependent variable: ElapTime VARIABLE COEFFICIENT STDERROR T STAT 2Prob(t > |T|) 0) const 395.501 226.872 1.743 0.156239 7) NoPlyrs 48.0180 18.4029 2.609 0.059466 * 52) NoRaces -90.4160 82.3200 -1.098 0.333724 22) PctFem -592.728 894.186 -0.663 0.543662 70) PctFem2 725.287 890.377 0.815 0.461027 Unadjusted R-squared = 0.765205 Adjusted R-squared = 0.530409 F-statistic (4, 4) = 3.25903 (p-value = 0.139) Note that although the PctFem variables are not individually significant, an F test determines that they are jointly significant.

16. Forecasts vs. ObservedFour Variables

17. The Experience • Easily seen real-world metaphor • Variety of teamwork challenges in short amount of time • Collaboration skills improved • Move through “Forming, Storming, Norming, Performing” quickly • Learn quickly • Learn safely • More research data needed

18. Informative, Useful, Fun

19. 2 Variable Model Interpretation(all other factors held constant) • NoPlyrs • For each additional player added to a team, the team will take 55 sec. more • NoRaces • For each additional race represented on a team, the team will take 146 sec. less

20. 4 Variable Model Interpretation(all other factors held constant) • NoPlyrs • For each additional player added to a team, the team will take 48 seconds more • NoRaces • For each additional race represented on a team, the team will take 90 seconds less • PctFem and PctFem2 • At 10% females, adding 10% more results in 44 seconds less • At 20% females, adding 10% more results in 30 seconds less • At 50% females, adding 10% more results in 13 seconds more • At 80% females, adding 10% more results in 56 seconds more • At 90% females, adding 10% more results in 71 seconds more • Minimum is at 41%