Understanding Learner Engagement in a Virtual Learning Environment
| Autor: | Nadia Aloui, Fedia Hlioui, Faiez Gargouri |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Knowledge management
Computer science business.industry media_common.quotation_subject 05 social sciences 050301 education 020206 networking & telecommunications 02 engineering and technology Educational data mining Dreyfus model of skill acquisition Identification (information) ComputingMilieux_COMPUTERSANDEDUCATION 0202 electrical engineering electronic engineering information engineering Virtual learning environment Dialog box TUTOR business Function (engineering) 0503 education computer Dropout (neural networks) computer.programming_language media_common |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030166595 ISDA (2) |
| Popis: | The past few years has seen the rapid growth of educational data mining approaches for the analysis of data obtained from the virtual learning environments (VLE). However, due to the open and online characteristics of VLEs, vast majority of learners may enroll and drop a course freely, resulting in high dropout rates problem. One of the key elements in reducing dropout rates is the accurate and prompt identification of learners’ engagement level and providing individualized assistance. In this respect, this paper proposes a survival modeling technique to study various factors’ impact on attrition over the Open University in UK. We aim to perceive the learning from a psychological engagement perspective, which is necessary to gain a better understanding of learner motivation and subsequent knowledge and skill acquisition. In this way, we provide an innovative process that may help the tutor to interfere with weak learner at the appropriate time, such as dialog prompts, or learning resources to enhance the learning efficiency. It can help developers to evaluate the VLE effectively and expand system function for future development trend. |
| Databáze: | OpenAIRE |
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