An Adaptive Educational Game To Help Students Learn How To Solve Systems Of Linear Equations

<p>Educational games have been proven to be effective in developing problem solving skills in well-defined domain, such as Math and Physics. In this thesis, an educational game called Matrix was developed to foster problem solving skills in the domain of linear algebra, particularly solving a system of linear equations. Matrix is an adaptive educational game that uses intelligent tutoring modules to guide the student's learning process and provide feedback based on the student's performance. These modules are domain module, student module, pedagogical module and presentation module. The domain module contains all the concepts the student needs to learn and an automated solver for linear equations that adopts the rules of Gaussian Elimination. The student module records the student's performance and provides the pedagogical module with the required information about the student's current skills. The pedagogical module uses the automated solver to assess the student's performance on the designated task and a neuro-fuzzy system to decide on the next proper game level for the student. Matrix has been evaluated by 13 students from the Columbus State University. The results show that Matrix was well perceived by the students and that they were able to transfer the skills learned in the game to real world problems on systems of linear equations.</p>

Name thesis:degree_name

Computer Science - Applied Computing Track

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

TSYS School of Computer Science

Year dc:date.available

2014

Author dc:creator

• Zhang, Wang

Contributors dc:contributor

• Dr. Rania Hodhod
• Dr. Shamim Khan
• Dr. Rodrigo Obando

• MatriX
• Math
• Physics
• Gaussian Elimination
• Columbus State University
• Computer Engineering
• Graphics and Human Computer Interfaces

Language dc:language

English

Repository record dc:identifier

https://csuepress.columbusstate.edu/theses_dissertations/167

OAI identifier oai:identifier

oai:csuepress.columbusstate.edu:theses_dissertations-1165