An analytic hierarchy process–based student arrangement in post-COVID-19

Abstract

In the post-COVID-19 era, balancing public health and maintaining teenagers´ education is critical. Hence, schools have started implementing in-person and distance learning classes simultaneously to avoid large-scale gatherings. Traditionally, many Taiwanese elementary schools prefer employing the randomization method in arranging students in classes to promote fairness. However, the randomization method does not provide an avenue for differentiated learning that takes into account students´ academic performance levels to improve their overall learning. Primary education is an important stage in fulfilling students´ needs in the first few years to ensure their development. Thus, teachers should pay more attention to students who have low academic performance. Therefore, this paper uses the analytic hierarchy process (AHP) method to effectively evaluate students´ overall academic performance, which is also used as the benchmark for student arrangement. In particular, pupils´ midterm test scores at a Taiwanese public elementary school (N = 25) were adopted as an empirical case. Results indicated that the AHP method reduced the respective internal academic performance gaps in in-person classes (Nï¼12, Mï¼80.33, SDï¼6.52) and distance learning classes (Nï¼13, Mï¼93.38, SDï¼2.03). Furthermore, the academic performances of the two types of classes had significant differences (tï¼6.58, p＜0.001). The AHP method effectively selects students with similar academic performance levels into the same learning group, reducing the troubles of students´ with different learning levels within the class and improving their overall learning performance. Moreover, the evaluated results of the subjects´ relative importance are expected to meet future education trends.