Calculus video recommender system

• Main Authors: Adam, N.L (Author), Aiman Sulaiman, M.S (Author), Jaini N.I (Author), Jamil N.M (Author), Jonovich A.A.A (Author), Jusoh @ Awang R. (Author), Kasim A.R.M (Author), Soh, S.C (Author), Zabidi S.F.A (Author)
• Format: Article
• Language: English
• Published: Institute of Physics Publishing 2019
• Subjects: Calculations; Content-based recommendation; Cosine similarity; Education computing; Face-to-face learning; Level of educations; Recommendation techniques; Recommender systems; Students; Text processing; Text-based documents; User's preferences; Vector space models; Vector spaces
• Online Access: View Fulltext in Publisher; View in Scopus
• ISBN: 17426588 (ISSN)
• DOI: 10.1088/1742-6596/1366/1/012080

Mathematics had been taught from the lower level of education to the higher level of education. Basic mathematics had been exposed since pre-school to give a good foundation on mathematics so that they can learn better in primary school and also in secondary school. At a higher level of education, the basic calculus is offered and it is one of the core components in mathematics that needs for technical studies. With the advancement on information technology, the students are no longer bound to the face-to-face learning. A plenty of online sources are available to help them learn anytime they want. The text based documents and tutorial videos can be accessed easily. In this research, we had studied the existing recommender system features and the recommendation techniques. Here, we had emphasized on finding the tutorial video based on the user's preferences particularly on basic calculus topics. A YouTube API is used to retrieve the basic calculus online videos. The YouTube API will send back a list of videos based on the searched keywords. The content-based recommendation technique known as keyword-based vector space model has been chosen because the results tend to show lots of similar videos than any other recommendation techniques. The keyword-based vector space model will convert the video title into a vector space and it will calculate the cross multiplication of the term frequency and the inverse document factor and it will also determine the closeness of the title by using the cosine similarity. The aim of the video recommender system is to help the students in searching an online video tutorial from the internet especially from YouTube and also to give a recommendation of a video based on it's suitability. © Published under licence by IOP Publishing Ltd.