On Improvement of Teaching Quality for a Selected Mathematical Topic Using Artificial Neural Networks Modeling(With a Case Study)

• 作者: Ayoub Al-Hamadi Fadhel Ben Tourkia Hassan. M. H. Mustafa
• 来源期刊: 文学与艺术研究：英文版
• 学科: 文学
• 关键词: artificial neural networks LEARNING performance evaluation computer aided LEARNING long DIVISION process ASSOCIATIVE memory
• 年，卷（期）: wxyysyjywb,（2）
• 页码范围: 239-246
• 页数: 8页
• 分类号: I

摘要

This paper motivated and inspired by an interdisciplinary critical educational issue adopted for a research work approach. It concerned with application of realistic Artificial Neural Networks (ANNs) models integrating reading brain function with multi-sensory cognitive learning theory. Specifically, these models adopted to improve tutoring quality (academic achievement) while teaching children “how to read?” considering the analysis and evaluation of phonics methodology. Herein, quantitative analysis and evaluation of this issue performed by considering two computer aided learning (CAL) packages concerned with a specific selected mathematical topic namely: long division process. Via realistic modeling of packages using (ANNs) based upon associative memory learning paradigm. In more details, at educational field practice; both CAL packages have been applied for teaching children algorithmic steps performing long division processes. Moreover, learning performance evaluation of presented packages considers children outcomes’ achievement after tutoring for suggested Mathematical Topic either with or without associated tutor’s voice. Interestingly, statistical analysis of obtained educational case study results at children classrooms (for both applied packages) versus classical tutoring proved to be in well agreement with obtained after ANNs computer simulation results.