Multi-Objective Heuristic Decision Making and Benchmarking for Mobile Applications in English Language Learning

Abstract

This research proposes to evaluate and analyze the decision matrix for learner's English mobile applications (EMAs) based on multi-objective heuristic decision making with a view to listening, speaking, reading, and writing. Because of the number of criteria, the significance of parameters, and variance in results, EMAs are difficult. Decision making has built on the combination of listening, speaking, reading, and writing and EMA evaluation criteria for students. The requirements are adapted from a framework of pre-school education. Six alternatives and 17 skills as a requirement are included in decision-making results. The six EMA are then assessed, with six English learning experts distributing a review form. The application subsequently is evaluated using the best-worst method and preference-order technique (TOPSIS) using multi-objective heuristic decision making methods. The best-worst method is used to measure requirements, whereas TOPSIS is used to test and assess the applications. In two cases, namely person and group, TOPSIS is used. Internal and external aggregations are used throughout the group context. In effect, the aim of evaluating the proposed study and comparing it to six relative studies with scenarios and benchmarking checklists is to develop an objectives validation framework for e-apps.