ABSTRACT
The increasing influence of globalization and the emerging information society have set new requirements for all areas of social life, including higher education. Today, e-Learning is fundamental tool in every high education institute in Malaysia. E-Learning is a platform where students can access anytime and anywhere whilst instructors can view the pattern of students’ access to online course materials, interacting, and participating in LMS. Decision Tree is a decision support system that uses a tree-like graph decision. It can be directly transformed into IF-THEN rules which is more simple and comprehensible beside easy to understand. The objectives of this final year project are to design and develop a system that helps an instructor evaluate students’ access pattern in LMS and stimulate the usefulness of LMS for students. The decision tree algorithm is applied to classify students’ access pattern and the LMS prototype is implemented. Herein, the LMS prototype is focused on applying the decision tree algorithm to analyse data.
KEYWORDS: decision tree algorithm, LMS, e-Learning, access pattern
KEYWORDS: decision tree algorithm, LMS, e-Learning, access pattern
INTRODUCTION
Learning Management System or LMS is designed to allow instructors to deliver and manage instructional content, including tracking and reporting of students’ work. Most Learning Management Systems are web-based. There are a great variety of scenarios whereby instructional content is applied in LMS. The content includes resources such as pdf documents, power point slides, and videos. Besides, LMS can be used as discussion and forums platform, quizzes, worksheets and assignment submission. It could be advantageous to instructors by knowing whether, who and when the student is engaging in course content materials and taking part in learning exercises before assess execution evaluation. Herein, data collection student from using LMS will be collected into database, and therefore will be used for analysis and reporting.
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OBJECTIVES
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METHODOLOGY
Decision Tree Algorithm The decision tree algorithm was chosen for classify student data usage in this final year project system.
STEP 1: Get the value of contribution from student data usage. s.note, s.forum and s.quiz.assignment are the input value of student data usage while l.note, l.forum and l.quiz.assignment are the input value of lecturer and alphabet A, B, C as variable that hold an answer. After getting value for Information, Contents, Activities and Assessment, total up all the values to get the value of the Contribution. STEP 2: The value of the contribution will be tested in the decision tree that was converted to set of classification rules. STEP 3: Analysis of student classification based on student data usage will be formed. |
CONCLUSION
In conclusion, this project focused on implementing the decision tree algorithm to analyse data and the LMS prototype is developed in order to get the input from user and to test the new algorithms. Decision tree is predictive model in which an instance is classified by following the path of satisfied condition from the root of the tree until reaching a leaf, which will correspond to a class label.