Bipolar Neutrosophic Driven Approach for Assessing the Teaching Quality of English Language and Literature Learning Outcomes

The quality of teaching in English Language and Literature is a crucial factor in enhancing student learning outcomes, fostering critical thinking, and promoting linguistic and literary proficiency. Nevertheless, the procedure of assessing the quality of English teaching remains a thought-provoking task since it typically depends on individual judgments, variety in criteria, and inconsistency in human observation, resulting in intrinsic uncertainty. Bipolar Neutrosophic Sets (BNS) offer an expressive way to model ambiguity in a bipolar manner using three positive and three negative memberships. Motivated by that, we propose to explore the novel approach based on BNS to improve the judgmental process of evaluating the quality of teaching of Quality of English Language and related literature. To assess the relative importance of aggregated teaching criteria, we apply the Analytic Hierarchy Process (AHP) to drive representative weights that guide the later decision-making. We drive a new weighting scheme to apply the AHP weights into a bipolar decision matrix. Following, we introduce multi-criteria decision-making (MCDM) to determine the bipolar ideal solutions in a bipolar decision matrix, and then identify the relative closeness teaching techniques. Based on a numerical study, we conduct a holistic analysis of the results of the proposed framework, which demonstrates remarkable power in making appropriate decisions about the best scenario English teaching approach that achieves the optimal benefit for students.