Carlos Andrés Arango L. Tatiana Joya C. Mario Mayoral

# Carlos Andrés Arango L. Tatiana Joya C. Mario Mayoral

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## Carlos Andrés Arango L. Tatiana Joya C. Mario Mayoral

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1. Design, implementation and evaluation of an active learning activity in the teaching of Genetic Algorithms Carlos Andrés Arango L. Tatiana Joya C. Mario Mayoral

2. Active learning games

3. Some questions? • The game works? • If I want to improve my game, how can I DO?

4. Experimental design Design type: Factor design 2k. k=4.

5. Treatments

6. Experimental design • Figure1. Effect of the factors on the response variable Figure2. Pareto chart of effects

7. ANOVA All factors are significant at the a = 0.05

8. Results • Active and significant principal factors: GENDER METHOD http://www.pekesapiens.com/caricaturas-infantiles.html

9. Results • Active and significantinteractionfactors: GENDER WORKING STATUS INTERACTION http://vector-images.com/clipart.php?id=17618 http://www.pekesapiens.com/caricaturas-infantiles.html

10. Results • Active and significantinteractionfactors: WORKING STATUS METHOD INTERACTION http://vector-images.com/clipart.php?id=17618

11. Results • Active and significantinteractionfactors: ACADEMIC HISTORY METHOD INTERACTION http://urbantitan.com/10-greatest-cheating-scandals-in-college-history/

12. Results • Active and significantinteractionfactors: METHOD GENDER WORKING STATUS INTERACTION http://vector-images.com/clipart.php?id=17618 http://www.pekesapiens.com/caricaturas-infantiles.html

13. Conclusions • In some way the four factors has influence on the results variable. • Only in this case: • Student who works has better results with active learning games. • Students with low grades has better results with active learning games, as consequence students with high grades has better results with traditional methods.

14. Improvement oportunities • Improvement the active learning game. Example: • Design a second part game.

15. Thanks