Date of Publication

9-20-2021

Document Type

Master's Thesis

Degree Name

Master of Science in Computer Science

Subject Categories

Computer Sciences

College

College of Computer Studies

Department/Unit

Computer Science

Thesis Advisor

Raymund C. Sison

Defense Panel Chair

Ryan Samuel M. Dimaunahan

Defense Panel Member

Raymund C. Sison
Niña Ana Marie Jocelyn A. Sales

Abstract/Summary

Difficulties hindering learning make fraction addition and subtraction hard for elementary students. These result in faulty procedures associated with misconceptions. A game-based intelligent learning environment (GILE) was developed to properly simulate fraction addition and subtraction procedures through mechanics, called learner outcome mechanics, derived from the literature on fraction arithmetic and fraction misconceptions. Results showed thorough play of the GILE seemed to yield positive results, such as removal of misconceptions, for playtesters who exhibit misconceptions in quasi-experiment short quizzes, though transfer of improvement from in-game context to formal mathematics context remained to be inconsistent possibly due to factors involving psychology. Intelligent components seemed to have better influence on correct addition and denominator equalization learning outcome (LO) mechanic usage than without, though the need for proper game level design and implementation may be needed to encourage consistent usage of all LO mechanics as well as promoting thorough play.

Abstract Format

html

Language

English

Format

Electronic

Physical Description

135 leaves

Keywords

Fractions; Competency-based education; Learning; Machine learning

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Embargo Period

9-20-2021

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