Content suggestion in e-learning


Content suggestion in e-learning


Self ??directed e-learning focuses on the independent learner one who engages in education at his own space free from curricular obligation. In this research, user's access interests were introduced into the design of a recommendation framework by using web browsing behaviour of the user. According to the user's access interest the recommendation framework can provide users with personalised information. The research thesis is to determine if users access interest can be extracted and to associate users access interest with other attributes to design a recommendation framework that attempts to recommend the information items, here the research papers to a researcher searching for interesting topics of research in her field. The proposed system is very useful to the new researchers as initially they are not aware of the research areas where they can work on. This system assists the researcher in searching the papers they are interested to search. The documents of interest to the user are used to build the user profile and this profile is used to re-rank the web search results. The paper presents the overall architecture of the proposed system and its implementation via a prototype design. In this dissertation an attempt is made to design a system prototype which will recommend the information items to the user according to the user access interest, which is captured from the web browsing behaviour of the user. The content similarity of the information items is also taken into consideration. The information items are suggested to the user based on the relevance. The organization of the thesis is done into various chapters. Introduction contains the brief introduction about personalisation services in e-learning scenario, recommender systems in e-learning. Literature review discusses about the web-based self-directed e-learning and the works done in the field of recommender systems in e-learning. Chapter 3 discusses the methodology adopted to design the system. In chapter 4 results are being analysed and discussed. Chapter 5 gives the future enhancement that can be done to the system design.


Kurian Latha


Computer Science




Kurian Latha, “Content suggestion in e-learning,” CHRIST (Deemed To Be University) Institutional Repository, accessed April 15, 2024,

Output Formats