Personalized adaptive content system for context-aware ubiquitous learning
| Autor: | Badr Eddine El Mohajir, Zakaria Bousalem, Inssaf El Guabassi, Mohammed Al Achhab, Ismail Jellouli |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
education.field_of_study
Computer science 05 social sciences Population 050301 education Context (language use) 02 engineering and technology Learning styles Constant (computer programming) Order (business) Human–computer interaction 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Content (Freudian dream analysis) education Adaptation (computer science) 0503 education General Environmental Science Ubiquitous learning |
| Zdroj: | Procedia Computer Science. 127:444-453 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2018.01.142 |
| Popis: | Nowadays, the world’s population is increasingly waiting for permanent and constant access to information. Accessing the right information at any time and any place is becoming a necessity. A learning system is called ubiquitous if it is able to adapt itself to its context (user, platform, environment, device, etc.). In this sense, theories and methods of adaptations keep rolling in order to make learning processes more efficient and relevant. In this paper, we propose an approach for providing personalized course content in ubiquitous learning, considering learning styles and context-awareness. The proposed approach aims to support learners by presenting course materials generated by an adaptive engine based on adaptation rules. |
| Databáze: | OpenAIRE |
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