@article{MAKHILLAJIT201615226506,
    title = {Mining Personalized E-learning System for Enhancing Learner Skills},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {22},
    pages = {4500-4511},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.4500.4511},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.4500.4511},
    author = {M.,Maganti,A. and},
    keywords = {E-learning system,personalization,auto-tagging,ato-suggesting,individual learner,India},
    abstract = {In a traditional classroom when a good teacher observes that a particular student is finding some
learning material to be hard to comprehend, he/she offers simpler materials and simpler explanations. The
teacher comprehends the complexity levels of the available learning materials, customizes the set of materials
offered to a student based on the classroom or homework performance of that student. In the age of open digital
learning, available learning materials have grown by orders of magnitude. Also, the likelihood of a good human
teacher paying direct attention to an average individual learner is very low now. Thus, it has become necessary
to build automated systems that can comprehend the complexity levels of learning materials, so as to auto-select
and auto-suggest suitable sets of learning materials for each individual learner. This study is an attempt to bring
personalization into massive online learning by auto tagging the content of topics and courses and also
auto-suggesting suitable materials based on the performance of the learner.}
    }