Prediction of Lecturers' Satisfaction Using M-Learning by Fast Learning Network

Abstract

M-learning, or mobile learning, has seen remarkable advancement in the past few years owing to the growth of mobile technology. This development has greatly improved the features and usability of mobile learning applications. This paper aims to present and analyze the accelerated learning network model, which identifies the determinants of mobile learning satisfaction of lecturers at Southern Technical University. The model employs a questionnaire given to 250 participating lecturers using multiple variables to examine the factors that affect their satisfaction levels. The study results revealed that the suggested model was more effective than others, including ANN, KNN, and MLP, in predicting factors affecting lecturers' satisfaction regarding accuracy and specificity. The model also showed good accuracy and specificity, with the latter reaching 93.55% in the prediction of the satisfaction factors of lecturers on mobile learning, with an accuracy of 92.00%. It emphasizes the need to consider the different aspects of different assessment methods and lecturers in research within an m-learning context.