Personalised web search for e-Learning using group-based recommendation approach / Mohammad Mustaneer Rahman

Mohammad Mustaneer, Rahman (2019) Personalised web search for e-Learning using group-based recommendation approach / Mohammad Mustaneer Rahman. Masters thesis, University of Malaya.

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      The increasing dependency of students on the Web for learning is fuelled by the increasing availability and unprecedented growth of the Internet. Popular Web search engines in the market which depend on the right use of keywords in order to search the relevant learning materials do not take into account the learning proficiency of their users. Consequently, students will receive the same set of search results when the same keywords are used regardless of their differences in learning competency and knowledge level in that particular subject. This situation hinders the optimised use of Web search engines in finding relevant learning materials that match students’ individual profiles. In this study, a Personalised Web search approach for E-learning is proposed. This proposed system augments the Web search engine. It provides recommendations of search results to students by using the group-based recommendation approach. The proposed approach is able to recommend results which match the students’ learning competencies and behaviours. To evaluate the effectiveness and acceptance of the proposed system, an experiment was conducted among students. The results from the experiment suggest that the proposed approach created a notable improvement in terms of performance and satisfaction for the students.

      Item Type: Thesis (Masters)
      Additional Information: Dissertation (M.A.) – Faculty of Computer Science & Information Technology, University of Malaya, 2019.
      Uncontrolled Keywords: e-Learning; Group-based recommendation; Personalised web search; Recommender system; Student profiling
      Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
      Divisions: Faculty of Computer Science & Information Technology
      Depositing User: Mr Mohd Safri Tahir
      Date Deposited: 24 Dec 2019 08:02
      Last Modified: 18 Jan 2020 10:23

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