Development of converted deterministic finite automation of decision tree rules of student graduation and adaptive learning environment

• Main Authors: Lagman, Ace C., Ballera, Melvin A., Contreras, Jennifer O., Raviz, Jennalyn G.
• Format: text
• Published: Animo Repository 2018
• Subjects: Machine theory; Formal languages; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/12721
• Institution: De La Salle University

In theory of computation, a deterministic finite automaton (DFA) is a finite state machine that accepts/rejects finite strings of symbols and only produces a unique computation. This study aims to convert the extracted decision tree rules sets from decision tree algorithm and the learning path sequence of the learning management system. This paper converts decision tree and learning management system rules into deterministic finite automaton. The decision tree rule sets are rule sets used to predict the vulnerability of not having graduation on time. The learning management system rules are the backbones of the learning management system in order to provide individualized learning scheme tailored to the preferences of the learners. The conversion of decision tree rules of student graduation and adaptive learning environment lead to easier interpretation and visualization of the methods and processes involved.