Design of a game-based intelligent learning environment to remediate fraction addition/subtraction misconceptions through bar models and misconception-eliciting problems

• Main Author: Obedoza, Jarl Brent
• Format: text
• Language: English
• Published: Animo Repository 2021
• Subjects: Fractions; Competency-based education; Learning; Machine learning; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/etdm_comsci/10; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1012&context=etdm_comsci
• Institution: De La Salle University

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.