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<record>
  <title>Recommendation Strategies for Personalize Mobile Educational Systems</title>
  <journal>International Journal of Computational Linguistics Research</journal>
  <author>Rizwana Noor, Farman Ali Khan</author>
  <volume>8</volume>
  <issue>1</issue>
  <year>2017</year>
  <doi></doi>
  <url>http://www.dline.info/jcl/fulltext/v8n1/jclv8n1_1.pdf</url>
  <abstract>Recent technological advancements shifted the trends of learning from e-learning to mobile learning, thus
added new dimensions such as learning process can take place at anytime and anywhere. However this shifts faces some
technological and design issues in m-learning and e-learning (i.e personalization). The factors that lead towards
personalisation are the frequent growth of learning resources as well as differences in the characteristics of learners.
Recently, recommender systems have been exploited as a new form of personalisation. This paper proposed a hybrid
recommendation approach for mobile learning environment, based on identified userâ€™s learning style for providing more
personalized recommendation. The reported results indicate significant differences in the performance of learners having
personalized recommendations.</abstract>
</record>
