DNA Sequence based Advanced Technique for Prediction of Hereditary Diseases using Support Vector Machine (SVM)

The COVID-19 pandemic has had a significant impact on higher education, disrupting traditional modes of teaching and learning in universities. As a response, many institutions have adopted online (distance) learning. However, this transition has brought about varying effects on students' academic performance. It is critical to investigate and improve online education in the context of the pandemic, considering the central role that higher education plays in technology innovation and societal development. To this end, a study was conducted using online questionnaires to evaluate the strengths, weaknesses, opportunities, and threats (SWOT) of transitioning from traditional learning to online learning during the pandemic. The survey was distributed to college students in China's 30 provinces or municipalities. The SWOT analysis identified 16 internal and external evaluation factors, leading to four improvement strategies for assessing online education. The survey results were used to determine the weight values of the SWOT factors using the subjective weight method of the Analytic Hierarchy Process (AHP). The fuzzy macros are the approach, which are used for the implementation of effective strategies. The most effective strategy identified was to reform and innovate teacher-based teaching mode for making students to grow their interest in learning new things to keep them away from boring state of learning. Here, creating a good learner-friendly environment is very important for improving the teaching quality. The methodology proposed here is applied on the students as case study during the pandemic and their results demonstrated the SWOT method's suitability for evaluating online education research.