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Knowledge spillovers in active team learning
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Knowledge spillovers in active team learning

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Dra. Núria Hernández Nanclares (Universidad de Oviedo, Spain) presented in the 15th EARLI Conference celebrated in August in Munich, a summary of her research in collaboration with Prof. Bart Rienties …

Dra. Núria Hernández Nanclares (Universidad de Oviedo, Spain) presented in the 15th EARLI Conference celebrated in August in Munich, a summary of her research in collaboration with Prof. Bart Rienties (University of Surrey, UK). Using Social Network Analysis, the authors studied the learning networks in an active team learning classroom.

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  • 1. Knowledge spillovers in active team learning: transfer of learning between teams Dra. Nuria Hernandez-Nanclares University of Oviedo EARLI 2013, München, 28 August 2013 Dr. Bart Rienties University of Surrey
  • 2. Setting and instructional design • 3rd year course of Business Administration in the Economics Faculty at University of Oviedo • 57 Spanish and Erasmus students • Blended learning approach with collaborative learning methodology • Four –seven members working teams • Five authentic tasks related with international economics Active group learning but limited friendship
  • 3. Face-to-face environment Active group learning
  • 4. Face-to-face environment Active group learning
  • 5. Virtual environment Active group learning
  • 6. Virtual environment Active group learning
  • 7. Limited friendship Face-to-face environment Virtual Learning Environment Intra-team interaction Class time devoted to team working: teams work on their own elaborating materials, reading and summarizing, discussing… Private team forum Wikis to develop specific written assignments Feedback and corrections through the forum Inter-team interaction Class time devoted to whole class work: presentations, discussions, analysis and assessment of other teams’ products… Task-specific forum to discuss about tasks and analyse and assess other teams’ products. Feedback and corrections through the forum
  • 8. Initial learning network at week 4... ...how knowledge spillovers occur?
  • 9. Initial learning network at week 4... ...who learns from whom?
  • 10. ... position of students and teams Initial learning network at week 4...
  • 11. Dynamics of change: week 7
  • 12. Dynamics of change: week 14
  • 13. Quantifying knowledge spillovers Measurement after four weeks Team (members) Internal External E-I Team 1(7) 30 7 -0.62 Team 2(5) 20 1 -0.91 Team 3(4) 6 15 0.43 Team 4(6) 8 3 -0.46 Team 5(6) 24 1 -0.92 Team 6(5) 16 7 -0.39 Team 7(5) 20 8 -0.43 Team 8(5) 18 5 -0.57 Team 9(6) 24 7 -0.55 Team 10(5) 16 8 -0.33 Team11(5) 14 10 -0.17 Average 17.82 6.55 -0.53
  • 14. Quantifying knowledge spillovers Measurement after four weeks Measurement after seven weeks Team (members) Internal External E-I Internal External E-I Team 1(7) 30 7 -0.62 28 13 -0.37 Team 2(5) 20 1 -0.91 20 8 -0.43 Team 3(4) 6 15 0.43 6 20 0.54 Team 4(6) 8 3 -0.46 20 14 -0.18 Team 5(6) 24 1 -0.92 30 40 0.14 Team 6(5) 16 7 -0.39 14 29 0.35 Team 7(5) 20 8 -0.43 18 13 -0.16 Team 8(5) 18 5 -0.57 20 24 0.09 Team 9(6) 24 7 -0.55 24 27 0.06 Team 10(5) 16 8 -0.33 16 13 -0.10 Team11(5) 14 10 -0.17 18 19 0.03 Average 17.82 6.55 -0.53 19.45 20.00 -0.12
  • 15. Quantifying knowledge spillovers Measurement after four weeks Measurement after seven weeks Measurement after 14 weeks Team (members) Internal External E-I Internal External E-I Internal External E-I Team 1(7) 30 7 -0.62 28 13 -0.37 24 16 -0.20 Team 2(5) 20 1 -0.91 20 8 -0.43 20 7 -0.48 Team 3(4) 6 15 0.43 6 20 0.54 12 20 0.25 Team 4(6) 8 3 -0.46 20 14 -0.18 20 8 -0.43 Team 5(6) 24 1 -0.92 30 40 0.14 30 17 -0.28 Team 6(5) 16 7 -0.39 14 29 0.35 18 26 0.18 Team 7(5) 20 8 -0.43 18 13 -0.16 14 12 -0.08 Team 8(5) 18 5 -0.57 20 24 0.09 20 25 0.11 Team 9(6) 24 7 -0.55 24 27 0.06 28 30 0.03 Team 10(5) 16 8 -0.33 16 13 -0.10 18 16 -0.06 Team11(5) 14 10 -0.17 18 19 0.03 20 25 0.11 Average 17.82 6.55 -0.53 19.45 20.00 -0.12 20.36 18.36 -0.17
  • 16. Prior friendship and knowledge spillovers M SD Density (in %) 1 2 3 Friendship ties (M1) 11.00 3.89 3.83 Learning ties after four weeks 4.70 1.68 5.98 .250** Learning ties after seven weeks 7.47 3.00 9.21 .259** .532** Learning ties after 14 weeks 19.00 7.47 9.06 .235** .514** .534**
  • 17. Learning network at week 14 Model1 Model 2 Model 3 Friendship ties (M1) .23*** .11*** .07*** Learning ties after four weeks _ .49*** .31*** Learning ties after seven weeks _ _ .35*** R-square adj. 0.055 0.276 0.362 Multiple regression quadratic
  • 18. Discussion Knowledge spillovers evolution At the beginning, students learned mainly from the members of its own team. As time passed, most students learned beyond the borders of their own team and developed knowledge spillovers because teams had a lot of possibilities to exchange knowledge and expertise with the other teams in the classroom learning space.
  • 19. Discussion Impact of prior friendship Declined over time, indicating that some of the knowledge spillovers are unrelated to pre-existing friendship relations
  • 20. Discussion Networks are continuously constructed and broken down indicating that learners developed different types of internal and external learning relationships with different students and teams. Learning networks evolve over time
  • 21. Thank you very much for your attention!! Dra. Nuria Hernandez-Nanclares University of Oviedo Dr. Bart Rienties University of Surrey