Using DEMATEL for Contextual Learner Modeling in Personalized and Ubiquitous Learning
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Abstract
With the popularity of e-learning, personalization and ubiquity have become important aspects of online learning. To make learning more personalized and ubiquitous, we propose a learner model for a query-based personalized le... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Intelligent Tutoring Systems and Adaptive Learning · Educational Technology and Assessment · Educational Assessment and Pedagogy
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (30)
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1. A step towards smart learning: Designing an interactive video-based m-learning system for educational institutes10.4018/IJWLTT.2019100102 ↗
2. Students’ acceptance and readiness for e-learning in Northeastern Thailand10.1186/s41239-016-0034-x ↗
3. A semi-automatic metadata extraction model and method for video-based e-learning contents10.1007/s10639-019-09926-y ↗
4. Review of personalized recommendation techniques for learners in e-learning systems
5. Requirements for semantic educational recommender systems in formal e-learning scenarios10.3390/a4030131 ↗
6. Schugurensky · Centre for the Study of Education and Work · 2000
7. Distinguishing self-directed and self-regulated learning and measuring them in the e-learning context10.1016/j.sbspro.2014.01.1155 ↗
8. Systematic review of effectiveness of situated e-learning on medical and nursing education10.1111/wvn.12005 ↗
9. IMS Global Learning Consortium, Inc, “IMS learner information package accessibility for LIP information model,” IMS Global Learning Consortium, Inc., 2003. [Online]. Available: http://www.imsglobal.org/accessibility/acclipv1p0/imsacclip_infov1p0.html#1514869 [Accessed 11 March 2021].
10. On the dynamics of learner models
11. Bayesian knowledge tracing, logistic models, and beyond: An overview of learner modeling techniques10.1007/s11257-017-9193-2 ↗
12. Learner model in adaptive learning
13. Kaya · Metadata and Semantic Research · 2011 · 34910.1007/978-3-642-24731-6_35 ↗
14. Towards an ontological learners’ modelling approach for personalised e-learning10.3991/ijet.v8i2.2476 ↗
15. A trace-based learner modelling framework for technology-enhanced learning systems
16. Challenges and benefits of the semantic web for user modelling
17. Real-time learner classification using cognitive score
18. Fitbit for learning: Towards capturing the learning experience using wearable sensing10.1016/j.ijhcs.2019.102384 ↗
19. Using wearable physiological sensors for affect-aware intelligent tutoring systems10.1109/JSEN.2020.3023886 ↗
20. Context model and context acquisition for ubiquitous content access in u-learning environments
21. Automatic detection of learner engagement using machine learning and wearable sensors10.4236/jbbs.2020.103010 ↗
22. Bull · Advances in Intelligent Tutoring Systems · 2010 · 30110.1007/978-3-642-14363-2_15 ↗
23. A new learner model in adaptive learning system
24. Inclusive learner model for adaptive recommendations in virtual education
25. Enhanced learner model for adaptive mobile learning
26. Designing a practical learner model for adaptive and context-aware mobile learning systems
27. Adaptive context-aware pervasive and ubiquitous learning10.1504/IJTEL.2009.024865 ↗
28. A revision of Bloom’s taxonomy: An overview10.1207/s15430421tip4104_2 ↗
29. Facial emotion detection to assess learner’s state of mind in an online learning system
30. Knowing minimum mobile device delivery context to maintain standard for m-learning in university scenario