Wireless Network Technologies For Emergency Remote Teaching And Predicting Teaching Staff Performance

Abstract

Due to the impact of the COVID-19 pandemic crisis, academic institutions worldwide has transformed the teaching methodology from conventional to emergency remote teaching strategy. To support the online teaching and learning process the most innovative technologies are utilised and their possible impacts are explored. Data mining tools and techniques are extremely useful for analysing data and predicting patterns. Educational data mining is one of the important research areas for analysing educational data.  Data from E-Learning education systems is studied and concerned with extracting its hidden information. In this research paper, it has been investigated the use of wireless network technology for teaching / learning, communication, collaboration and attributes used for evaluating teachers’ performance at the College of Computer Science, Jazan University, Kingdom of Saudi Arabia. The data is collected anonymously from student side to evaluate the instructors’ performance on different dimensions / parameters. These parameters act as performance indicators for an individual or group of teachers and consequently they can be used as a basis for decision-making about their professional development and future. The data mining approach measures the performance of the teachers during the remote / virtual teaching and learning and suggests to them what knowledge, skills and prominent qualities they have. The outcome of this research provides an opportunity and a deeper understanding in improving the teachers’ performance in the academic institutions.