ABSTRACT
This chapter states the different stages that are necessary to help learners discover their strengths and weaknesses through analyzing the data using the Waikato Environment for Knowledge Analysis (Weka) tool and determining the emotions based on acoustic cues. Artificial intelligence provides some software solutions; among them is Weka. Weka is a famous set of machine learning software written in Java, developed at the University of Waikato, New Zealand. The chapter briefly describes the architecture of the system and how to estimate the strengths and weaknesses of a learner from the processing of data, and how to determine the appropriate learning style and improve learners' motivation by using the self-determination theory (SDT). The great majority of digital natives face many problems when it comes to learning using e-learning applications or websites. The resolution of classification issues may be made by the Support Vector Machine (SVM) method inspired by the statistical learning theory; it was introduced by Vapnik in 1995.
