Evaluating human–computer interaction education based on active learning methods using the CRITIC and TOPSIS approach

Abstract

With the ever-growing development of information technology, the education sector has adopted advanced technologies to improve this field. Various procedures based on human–computer interaction (HCI) can be applied to enhance the efficiency of interaction between humans and computers, especially in education. Active learning is one of the major technological fields that improve the usability of active learning. The implementation of HCI approaches such as project-based learning (PBL), active learning classrooms (ALCs), and multi-user virtual environments (MUVE) can improve students' learning capabilities and teachers' teaching skills, making education more effective. After studying different applications of HCI in active learning, this study aims to extract common features and identify the most efficient ones. For the evaluation process, we presented two techniques: Criteria Importance Through Inter Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select the most effective HCI approach among various options. We chose nine criteria along with ten alternatives and ranked them based on their performance scores. For assigning weights to criteria, we utilized the CRITIC strategy, while the TOPSIS technique was applied to rank the alternatives. In the proposed study, we identified that the alternative with the highest performance score is placed in first place, while the alternative with the worst performance score is placed at the bottom. The study concluded that the most efficient and effective approach was selected among various options, which can be used as a suggestion for decision-related issues and future directions.