Towards Applying Real Time Physiological Data and Gamification to Machine Learning Educational Systems
| Autor: | Bryan Y. Hernández-Cuevas, Chris S. Crawford |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Data collection
Computer science business.industry 05 social sciences 020207 software engineering 02 engineering and technology Physiological computing Machine learning computer.software_genre 0202 electrical engineering electronic engineering information engineering Systems design 0501 psychology and cognitive sciences Artificial intelligence business computer 050107 human factors Educational systems |
| Zdroj: | SIGCSE |
| DOI: | 10.1145/3408877.3439597 |
| Popis: | In the data age, everyday devices and applications implement machine learning (ML) to enhance user experiences. However, everyday users usually do not completely understand the technology. Moving forward with ML education will require support for new forms of digital literacies involving machine learning. Physiological computing and gamification techniques can present engaging opportunities for dynamic personally-relevant data collection and manipulation. Our research proposes a system design that applies both real-time physiological data and gamification elements to provide novice users the opportunity to learn about ML concepts. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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