Ibigkas! Math 2.0: An Intelligent Computer-Supported Collaborative Learning Application for Grade 5 Mathematics
Abstract
This paper reports the design and development of an intelligent mobile computer-supported collaborative learning (mCSCL) application in mathematics for Grade 5 elementary students named Ibigkas! Math. In the first experiment, we deployed the non-adaptive version of Ibigkas! Math. This software is a collaborative mobile-based game application where a team of students answers basic arithmetic problems. The player has to read aloud the arithmetic problems and answer multiple-choice items. The correct answer appears on one of the team members’ devices. A team consists of three students with varying mathematical competencies and personality types. Thirty-seven Grade 5 students (male = 25, female = 12, average age = 10.5 years old) participated in the initial experiment. The initial results of the study revealed that the students always chose problems involving addition with the same level of difficulty throughout the game sessions. It was also observed that students exhibited “button-smashing” – a gaming behavior where students guess a game answer. These game behaviors lead to higher game scores. However, the game scores could not reflect the mathematical competencies of the students. A collaborative-intelligent math CSCL was developed to make the software adaptive to these behaviors. Aggregated model of constraint-based collaborative filtering algorithm (CBCF), Rasch model (RM), and computational fluency (CF) (e.g., trials-to-criterion approach) were integrated into the software. The revised version will then be deployed in the same setting to test its impact on students’ learning and gaming behavior.
