Image from OpenLibrary
Custom cover image
Custom cover image

Prediction of students performance using decision tree towards improvement of FOMA course content/ Olivia D. Real .--

By: Material type: TextTextPublication details: Manila: Technological University of the Philippines, 2023.Description: xiii, 171pages: 29cmContent type:
Media type:
Carrier type:
Subject(s): LOC classification:
  • THE QA 14  R43 2023 c.2.
Dissertation note: College of Science .-- Master of Arts in Teaching Mathematics: Technological University of the Philippines, 2023. Summary: The study aimed to predict the performance of the students in Fundamentals of Mathematics Analysis (FOMA) using Decision Tree. It involved 348 students from the Computer Studies Department, College of Science, who are officially enrolled in Bachelor of Science in Computer Science (BSCS), Bachelor of Science in Information Systems (BSIS), and Bachelor of Science in Information Technology (BSIT). Based on the gathered data, the findings of the study are the following: the students have an average performance in the four (4) assessments (formative and summative) that include seatwork, assignments, long quizzes, and final examination; significant positive marked relationship exists between formative and students’ final grade in FOMA, marked relationship between summative assessment and their final grade in FOMA, and substantial relationship between formative assessment and summative assessment, the appropriate predictive modeling is CHAID on the ten-level category, but in the binary pass/fail category C & RT Model performance is better because of its high sensitivity and overall accuracy; CHAID model performed well if the dataset is a multi-level classification and C&RT performed better if the dataset is a binary level category, hence the best algorithm for the prediction of the performance of the students in FOMA among the Decision Tree models is based on the dataset and its classification. Keywords: Student Performance, Decision Tree, C5.0, C & RT, and CHAID
List(s) this item appears in: COS-MA- Teaching Mathematics
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)

Master's thesis

College of Science .-- Master of Arts in Teaching Mathematics: Technological University of the Philippines, 2023.

Includes bibliographic references and index.

The study aimed to predict the performance of the students in Fundamentals of Mathematics Analysis (FOMA) using Decision Tree. It involved 348 students from the Computer Studies Department, College of Science, who are officially enrolled in Bachelor of Science in Computer Science (BSCS), Bachelor of Science in Information Systems (BSIS), and Bachelor of Science in Information Technology (BSIT). Based on the gathered data, the findings of the study are the following: the students have an average performance in the four (4) assessments (formative and summative) that include seatwork, assignments, long quizzes, and final examination; significant positive marked relationship exists between formative and students’ final grade in FOMA, marked relationship between summative assessment and their final grade in FOMA, and substantial relationship between formative assessment and summative assessment, the appropriate predictive modeling is CHAID on the ten-level category, but in the binary pass/fail category C & RT Model performance is better because of its high sensitivity and overall accuracy; CHAID model performed well if the dataset is a multi-level classification and C&RT performed better if the dataset is a binary level category, hence the best algorithm for the prediction of the performance of the students in FOMA among the Decision Tree models is based on the dataset and its classification.

Keywords: Student Performance, Decision Tree, C5.0, C & RT, and CHAID

There are no comments on this title.

to post a comment.



© 2025 Technological University of the Philippines. All Rights Reserved.

Powered by Koha