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Vol.11, No.4, November 2022. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Adaptive Neuro-Fuzzy Inference System(ANFIS) Formulation to Predict Students' Neuroscience Mechanistic: A Concept of an Intelligent Model to Enhance Mathematics Learning Ability
Mohamad Ariffin Abu Bakar, Ahmad Termimi Ab Ghani, Mohd Lazim Abdullah, Norulhuda Ismail, Salmi Ab Aziz
© 2022 Ahmad Termimi Ab Ghani, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 11, Issue 4, Pages 1942-1951, ISSN 2217-8309, DOI: 10.18421/TEM114-63, November 2022.
Received: 16 April 2022. Revised: 28 October 2022.
Abstract:
Students' mathematics learning ability should always be assessed, predicted and given appropriate interventions. However, due to lack of exposure and knowledge to mechanisms of neuroscience and Adaptive neuro-fuzzy inference system (ANFIS), both elements are not optimally applied in educational measurement and evaluation settings. Therefore, based on the findings of neuroscience through the AGES model and the ANFIS formulation as well as the mathematics learning model, this paper will discuss the development of a conceptual model for predicting students' neuroscience mechanistic. The significance of this model is to reveal students' mathematical learning ability and analyze the causes of weaknesses or attributes that affect learning.
Keywords – – adaptive neuro-fuzzy inference system, intelligent model, neuroscience mechanistic, mathematics learning ability, machine learning |
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