Scaling Mentoring Support with Distributed Artificial Intelligence
| Autor: | Peter de Lange, Alexander Tobias Neumann, Ralf Klamma, Jakub Kuzilek, Milos Kravcik, Benedikt Hensen, Xia Wang |
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| Rok vydání: | 2020 |
| Předmět: |
050101 languages & linguistics
Higher education business.industry Computer science 05 social sciences Learning analytics Cloud computing 02 engineering and technology Open source Work (electrical) Order (exchange) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Artificial intelligence Set (psychology) business Limited resources |
| Zdroj: | Intelligent Tutoring Systems ISBN: 9783030496623 ITS |
| Popis: | Mentoring is the activity when an experienced person (the mentor) supports a less knowledgeable person (the mentee), in order to achieve the learning goal. In a perfect world, the mentor would be always available when the mentee needs it. However, in the real world higher education institutions work with limited resources. For this, we need to carefully design socio-technical infrastructures for scaling mentoring processes with the help of distributed artificial intelligence. Our approach allows universities to quickly set up a necessary data processing environment to support both mentors and mentees. The presented framework is based on open source standards and technologies. This will help leveraging the approach, despite the organizational and pedagogical challenges. The deployed infrastructure is already used by several universities. |
| Databáze: | OpenAIRE |
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