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

Abstract

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