A Web-Based Prototype Course Recommender System using Apache Mahout

Mike Nkongolo

ISBN 10: 3668554366 / ISBN 13: 9783668554368

Published by GRIN Verlag, 2017

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Project Report from the year 2017 in the subject Computer Science - Miscellaneous, grade: BSc Honours in Computer Science, , course: Honors research project, language: English, abstract: Most universities offer a wide range of courses in which students can enrol. As a result, students may feel overwhelmed with the many possibilities and large amount of information, resulting in having a difficult time deciding what to sign up for. To this end, there is a need for a system that can assist students in this crucial process. Thus, we set out to develop a web-based recommender application that could generate a list of valuable, accurate course recommendations, taking into account a student's likelihood of succeeding academically.Choosing an effective and stimulating set of courses is not an easy task for a student. There are several factors at play when it comes to choosing courses that one must study. One of these factors may be the assumed difficulty of a course that a student is considering to take. Of course, if the course is compulsory, then the student has no choice but to enrol in it. However, in the situation in where there are many different subjects to choose from, the student may shy away from taking optional courses that might pose a significant challenge, in terms of workload or being unable to fully understand the course content. These courses would clearly have a negative effect on academic performance. However, there may also be some students who are looking to be challenged, and for whom choosing more difficult courses would be an exciting challenge. In terms of academic performance, effective course selection is of utmost importance in ensuring a student is able to succeed in her or his studies and obtain their qualification(s).

Seller Inventory # 9783668554368

Bibliographic Details

• Title: A Web-Based Prototype Course Recommender System using Apache Mahout
• Publisher: GRIN Verlag
• Publication Date: 2017
• Language: English
• ISBN 10: 3668554366
• ISBN 13: 9783668554368
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

Project Report from the year 2017 in the subject Computer Science - Miscellaneous, grade: BSc Honours in Computer Science, course: Honors research project, language: English, abstract: Most universities offer a wide range of courses in which students can enrol. As a result, students may feel overwhelmed with the many possibilities and large amount of information, resulting in having a difficult time deciding what to sign up for. To this end, there is a need for a system that can assist students in this crucial process. Thus, we set out to develop a web-based recommender application that could generate a list of valuable, accurate course recommendations, taking into account a student's likelihood of succeeding academically. Choosing an effective and stimulating set of courses is not an easy task for a student. There are several factors at play when it comes to choosing courses that one must study. One of these factors may be the assumed difficulty of a course that a student is considering to take. Of course, if the course is compulsory, then the student has no choice but to enrol in it. However, in the situation in where there are many different subjects to choose from, the student may shy away from taking optional courses that might pose a significant challenge, in terms of workload or being unable to fully understand the course content. These courses would clearly have a negative effect on academic performance. However, there may also be some students who are looking to be challenged, and for whom choosing more difficult courses would be an exciting challenge. In terms of academic performance, effective course selection is of utmost importance in ensuring a student is able to succeed in her or his studies and obtain their qualification(s).

About the Author

Mike Nkongolo received the BSc (Hons) degree in computer science from the University of the Witwatersrand, Johannesburg, South Africa, in 2016. He is currently working toward the Masters degree in the School of Computer Science and Applied Mathematics, University of the Witwatersrand. His research interests include the theory and applications of Intelligent Systems, Web-based platforms and Machine Learning, Sentiment detection in Web Mining, and Artificial Intelligence-Natural Languages Processing.