MARC details
| 000 -LEADER |
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| fixed length control field |
02500nam a22002777a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20260304100515.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
260304b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
TUPM |
| Language of cataloging |
English |
| Transcribing agency |
TUPM |
| Modifying agency |
TUPM |
| Description conventions |
rda |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
THE QA 14 |
| Item number |
R43 2023 c.2. |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Real, Olivia D. |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
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| Title |
Prediction of students performance using decision tree towards improvement of FOMA course content/ |
| Statement of responsibility, etc. |
Olivia D. Real .-- |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Manila: |
| Name of publisher, distributor, etc. |
Technological University of the Philippines, |
| Date of publication, distribution, etc. |
2023. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiii, 171pages: |
| Dimensions |
29cm. |
| 336 ## - CONTENT TYPE |
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| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
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| General note |
Master's thesis |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
College of Science .-- |
| Degree type |
Master of Arts in Teaching Mathematics: |
| Name of granting institution |
Technological University of the Philippines, |
| Year degree granted |
2023. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographic references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
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.<br/><br/>Keywords: Student Performance, Decision Tree, C5.0, C & RT, and CHAID<br/> |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematics |
| Form subdivision |
study and teaching |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Decision tree |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
FOMA course content |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Master's Thesis |
| Suppress in OPAC |
No |