CCSE Reading Group: Student learnability in online learning using learning interactions
The use of the Internet as a means through which the educational process takes place between the teacher and the student revealed many technical capabilities and at the same time revealed the existing challenges, especially at present with Covid 19. Many teachers use multiple means to interact with their students to involve them in the educational process and ensure that their access to distance education will not reduce their understanding of face-to-face classes. Modern technologies, which relied mainly on the use of many tools for the educational process to deliver different measurements about the student’s educational content learning, came out with systems that predict the student’s performance and others that measure the student’s knowledge rate. From the educational side, teachers think that using tools based on numbers (numerical representations) to measure student learning rate is not enough to describe students' knowledge or learning status in the different educational platforms. Hence, there is a need to simulate the learning observations into a technical form that allows a better understanding of student learning status. This research aims to reveal the student's learnability in online platforms through learning patterns that student use to learn content efficiently. The study looks at the case from an educational perspective where teachers can define the possible meanings of a student's understanding of the content
My name is Maha Alanqoudi, a 2nd year full-time PhD student at UofG-SCS. I did my MSc in Science of Big Data at Stirling University, 2016. My bachelor degree is in Software Engineering from Nizwa College of Technology(NCT), 2013. I am a lecturer at the University of Technology and Applied Science, Nizwa College of Technology, IT department. I worked as an SAP MM associated consultant at Abraj Energy Services SOAG 2014-2015.
First published: 25 January 2021