Using Ordinal Regression Models to Predict the Difficulties of Blended Education and their Impact on the Teacher and Student. (As a Model for the Northern Technical University (NTU))
Abstract
The study aims to develop an ordinal logistic regression (OLR) model to identify the issues that face students, academic teachers, with blended learning with Coivd-19. Additionally, to explore the factors that influence the adoption of (BL) in Northern Technical University (NTU). Finally, to provide an analytical model to facilitate the task for university strategies and their decision-making for solving the problem and to deal with the present suggestions. An e-questioner study of the opinions of teachers and students were used to collect data. The data includes 214 that come from the e-questionnaire that was designed and distributed to the appropriate samples of educational groups. Then, ordinal logistic regression was used to develop 4 models of the effectiveness of each axis. It can be concluded that BL is a useful style of learning. However, it is still suffering from several impediments. One of the biggest obstacles students and staff are facing is the weakness of the internet network because of the inability to connect to fibreoptic Internet. Alongside it, the high prices of internet subscription and the lack of student’s modern devices (computer and mobile) to connect to the platform. Another disadvantage is the drop of opportunities for excellence and creative students due to online assessments that allows other students to check the internet for solutions and answers. According to the data, poor connection was the main issue of BL that is facing students and staff. Additionally, the difficulty to get devices and facilities by students was another limitation of BL (cost effectiveness).
Keywords
Ordinal logistic regression, blended learning, prediction models, Open lectures, Open collaboration, Open learning. Institutions of higher education.Metrics