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Detecting Creativity in Open-Ended Learning Environments

Detecting creativity in open-ended learning environments is crucial for promoting innovative outcomes. This study explores flexible models that allow exploration and trial-and-error approaches. Traditional creativity definitions may not fully capture creative leaps and user diversity. The research emphasizes the importance of algorithms and visualizations for identifying and nurturing creativity, calling for an evolution in educational data mining methods. Additionally, ethical considerations and the handoff problem in student modeling interactions are discussed to further enhance creativity detection strategies.

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Detecting Creativity in Open-Ended Learning Environments

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  1. Detecting Creativity in Open-Ended Learning Environments Roi Shillo, Nick Hoernle, Kobi Gal

  2. Creativity is… Machine recognisable [Newell, Shaw & Simon 62] Fundamental [Boden, 98] Ubiquitous [Schank & Cleary 95]

  3. Focus for EDM Open Ended Environments • Flexible • Allow exploration, trial and error Models for detecting and promoting creative outcomes [Manske and Hopee 14, Chuang 15] Amir et al. 16 Gal et al. 17

  4. The Task

  5. Shape Category Distribution

  6. Creative Leaps [Noy et al. 2012]

  7. User Diversity

  8. Detecting New Shapes

  9. Feature Design

  10. Measuring with traditional definitions of creativity (flexibility, originality, fluency) did not help Results Cutoff matters!

  11. Summary Creativity as a design principle; Algorithms for detecting and promoting creativity; Intelligent visualisations; • A call to arms for EDM!

  12. Evolution vs. Revolution [Roll and Wiley 16] Handoff problem Ethics [Doroudi and Brunskill 19] Closing the Loop Student Modeling Interaction

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