Sentiment mining in student blogs in learning management systems for improved decision making in universities

• Autores: Abdullah Al Hussein
• Localización: QUID: Investigación, Ciencia y Tecnología, ISSN-e 2462-9006, ISSN 1692-343X, Nº. Extra 1, 2017, págs. 1216-1219
• Idioma: inglés
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• Resumen

  • At present, the Universities and Colleges in the Kingdom of Saudi Arabia used Learning Management Systems. Majmaah University uses D2L from this academic years onwards. This learning management systems supports for classroom instruction management, talent management, communication and collaboration, content management, assessment and testing, virtual classrooms, reporting and mobile learning and student interaction through blogs. These blogs generate voluminous of data which could be more useful to the teacher. The volume of the blog data increases over the time. Sentiment mining deals about extracting unique patterns from the online reviews. Sentiment mining is well applied to many leading social networking websites and found to produce quality results. These generated unique patterns will be much use to the faculty and administration to make important decisions. Applying sentiment mining on the blogs generated by the learning management system is the theme of this proposed research. The existing sentiment mining models will be analyzed and a new model will be proposed. This new sentiment mining model will be thus applied to the blogs generated by the D2L system to produce unique patterns. The unique patterns are the generated knowledge by the system. This generated knowledge will be used by the faculty and administration for improving the decision making.