Online learning is machine learning, in real time from successive data samples. Meta online learning consists in combining several online learning algorithms from a given set (termed portfolio) of algorithms. The goal can be (i) mitigating the effect of a bad choice of online learning algorithms (ii) parallelization (iii) combining the strengths of different algorithms. Basically, meta online l...

This study focused on the relationship between Kolb learning styles and the enduring time of online learning behaviors, the relationship between Kolb learning styles and learning outcomes and the relationship between learning outcomes and the enduring time of a variety of different online learning behaviors. Prior to the experiment, 104 students majoring in Educational Technology completed Kolb...

Aims: As a result of the novel coronavirus (COVID-19) pandemic, traditional face-to-face learning approach at tertiary institutions was replaced by an online model. This has significant impact on students, teachers, and administrators, particularly in Ghana, where not been widely used past. The current study looked how students' perceptions quality their experiences affected acceptance paradigm...

This paper presents the system targeted in the Divino project, funded under the Industria 2015 framework of the Italian Ministry of Industry. The resulting platform embodies an innovative portal technology where Social Web functionalities, User Profiling and Aspect-based Opinion Mining are integrated through Liferay, a well known Enterprise Portal Technology. The proposed approach allows analys...

A multi objective Honey Bee Mating Optimization (HBMO) designed by online learning mechanism is proposed in this paper to optimize the double Fuzzy-Lead-Lag (FLL) stabilizer parameters in order to improve low-frequency oscillations in a multi machine power system. The proposed double FLL stabilizer consists of a low pass filter and two fuzzy logic controllers whose parameters can be set by the ...