Abstract-Outcome Based Education (OBE) or student centered learning is one of the key component in quality assurance and enhancement in the higher education. The OBE approach encourages students to become active learner rather than being passive as in the traditional teacher-centered learning approach. In OBE, teacher is a facilitator of the teaching learning process; therefore the quality of teaching learning process does not depends on how a Lecturer teaches the course, but on the skill or knowledge achieved by the students. The level of the attainment of Course Level Outcomes (CLOs) is the indicator of the skill, knowledge and behavior that students acquired at the end of the course. Therefore each and every activity conducted in the classroom has to be reflected in the assessment of course outcome, which is measurable. In this paper, an efficient way of assessing the course learning outcome using Fuzzy Logic is presented. The uniqueness of the method is it will give an accurate measure to assess the attainment level of the course by considering every parameter enabling the learning process.

The present novel coronavirus (COVID-19) infection has engendered a worldwide crisis on an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is always at the forefront to understand and provide an adequate description of the transmission of any disease. In this research work, we have formulated a deterministic compartmental model (SEAMHCRD) including various stages of infection, such as Mild, Moderate, Severe and Critical to study the spreading of COVID-19 and estimated the model parameters by fitting the model with the reported data of ongoing pandemic in Oman. The steady-state, stability and final pandemic size of the model has been proved mathematically. The various transmission as well as transition parameters are estimated during the period from June 4th to July 30th, 2020. Based on the currently estimated parameters, the pandemic size is also predicted for another 100 days. Sensitivity analysis is performed to identify the key model parameters, and the parameter gamma due to contact with the symptomatic moderately infected is found to be more significant in spreading the disease. Accordingly, the corresponding basic reproduction number has also been computed using the Next Generation Matrix (NGM) method. As the value of the basic reproduction number (R0) is 0.9761 during the period from June 4th to July 30th, 2020, the disease-free equilibrium is stable. Isolation and tracing the contact of infected individuals are recommended to control the spread of disease.

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