Automatization for Finding Supplementary Materials for University Courses
Name
Anastassia Ivanova
Abstract
Gaining a degree can be a great challenge for students. Along with easy ones, there are courses that may be easy for some students or can be a great challenge for others. One of the possible reasons for such difficulties could be lack of proper studying materials available for course takers. When looking for help, students often turn to search engines that find articles which have answers to every question that a student may have. However, most materials found via Google contain inaccurate information, and since students are not able to separate high-quality teaching materials from the low-quality one, the subject of the course is misunderstood and the student gets confused.
The purpose of this thesis is to create a portal that searches for high-quality teaching materials on the Internet for each course in the current semester. The portal will automatically update the course list before the start of the new semester. The proposed application collects and analyzes the textual information from the course. Then the data is cleaned and converted to a format suitable for analysis. The next step is to search for materials via Google by filtering out non-related topics, low quality materials and unreliable sources, and returning to the student to read the best results.
The final result of this thesis is a working web application that performs a search for high-quality teaching materials via Google engine for each course in the current semester. The algorithm that has been created for this purpose, however, requires improvement to work faster and find more suitable materials for students. Currently, the final output of the algorithm may contain articles that are too simple to the University student or does not refer to course subject at all.
The purpose of this thesis is to create a portal that searches for high-quality teaching materials on the Internet for each course in the current semester. The portal will automatically update the course list before the start of the new semester. The proposed application collects and analyzes the textual information from the course. Then the data is cleaned and converted to a format suitable for analysis. The next step is to search for materials via Google by filtering out non-related topics, low quality materials and unreliable sources, and returning to the student to read the best results.
The final result of this thesis is a working web application that performs a search for high-quality teaching materials via Google engine for each course in the current semester. The algorithm that has been created for this purpose, however, requires improvement to work faster and find more suitable materials for students. Currently, the final output of the algorithm may contain articles that are too simple to the University student or does not refer to course subject at all.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Siim Karus
Defence year
2019