Convergence of Gamification and Machine Learning: A Systematic Literature Review
| Autor: | Alireza Khakpour, Ricardo Colomo-Palacios |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Context (language use) 02 engineering and technology Machine learning computer.software_genre Science education Field (computer science) Education Personalization Mathematics (miscellaneous) Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 [VDP] 0202 electrical engineering electronic engineering information engineering Learning Point (typography) business.industry Systematic literature review 05 social sciences Educational technology 050301 education Teaching machine 020207 software engineering Computer Science Applications Human-Computer Interaction Systematic review Behavioral change Gamifcation Artificial intelligence business 0503 education computer |
| Zdroj: | Technology, Knowledge and Learning |
| ISSN: | 2211-1670 2211-1662 |
| Popis: | Recent developments in human–computer interaction technologies raised the attention towards gamification techniques, that can be defined as using game elements in a non-gaming context. Furthermore, advancement in machine learning (ML) methods and its potential to enhance other technologies, resulted in the inception of a new era where ML and gamification are combined. This new direction thrilled us to conduct a systematic literature review in order to investigate the current literature in the field, to explore the convergence of these two technologies, highlighting their influence on one another, and the reported benefits and challenges. The results of the study reflect the various usage of this confluence, mainly in, learning and educational activities, personalizing gamification to the users, behavioral change efforts, adapting the gamification context and optimizing the gamification tasks. Adding to that, data collection for machine learning by gamification technology and teaching machine learning with the help of gamification were identified. Finally, we point out their benefits and challenges towards streamlining future research endeavors. |
| Databáze: | OpenAIRE |
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