An Approach of Teachers' Quality Improvement by Analyzing Teaching Evaluations Data
With the increasing number of educational data the institutions are becoming more reliable on the technology to analyze the students' behavior, achievements, and qualities for decision making. The accomplishments of students do not only rely on their quality and passion but also the teachers' performance. By analyzing digital data generated by the students at the end of the semester while evaluating teachers can be a way to evaluate teachers' performances to make decision to assign course or advice teachers in next semesters. In this research, we focused on identifying the teaching attitude and expertise of a teacher based on the students' feedback which can be applied to better decision making and the improvement of the quality. We had offered the automatic decision-making system based on this research project and implemented it. By using our system which we developed using python pandas, we will offer the strengths and weaknesses of a teacher based on the subject-groups and which quality they should improve for getting better acceptance to the students. To evaluate the performance of our system we used survey data from Daffodil International University and generated the result that met our expectation.