The rise of digitalization and computing devices has transformed the educational landscape, making traditional teaching methods less productive. In this context, early and continuous user interaction is crucial for designing and developing effective learning applications. The field of Human-Computer Interaction (HCI) has seen significant technological growth, enabling educators to provide quality educational services through smart input and output channels. However, to prevent students from discontinuing their studies and help them grow their careers, a multimodal HCI approach is needed. This paper proposes a multimodal deep learning multi-layer Convolutional Neural Network (CNN) to improve the educational experience. Our designed system aims to create a promising solution for improving the educational experience and enabling educators to provide high-quality educational services to students. Our implementation results show promising real-time performances, including a high success rate in a constriction learning concept, a quality interaction experience, and enhanced educational services. We evaluated the accuracy of five multimodal inputs, including Finger Touch (FT), Hands Up (HU), Hands Down (HD), Voice Command (VC), and Click/Typing (CT). The results indicate an average accuracy of 90.8%, 87%, 88.6%, 91.8%, and 87%, respectively, demonstrating the effectiveness of our proposed approach.

With the formation and growth of the company, corporate law is continuously established and enhanced. It significantly contributes to the company’s healthy growth and brings business operations inside the legal framework. As a result, corporate law education is crucial for employees, particularly directors. Fundamentally, corporate law education is a learning process. The metaverse period has increased learners’ needs for learning environments, and human-computer interaction technology will offer all-encompassing support for the smart learning environment. The board of directors needs to adequately monitor each director’s learning level as they study corporate law, which will inevitably be detrimental to the company’s long-term growth. The most efficient method to address this issue is to use eye movement data to mine different eye movement patterns, followed by an analysis of the learning state of corporate law of directors. The scanning path analysis is used to examine the similarities and differences of the directors’ eye movement behaviors during the study of corporate law to enhance the state of corporate law learning. However, the learning status of corporate law cannot be determined only by the eye tracking of directors. We employ the convolutional neural networks (CNN) -based emotion recognition model to provide the directors constructive criticism about their learning state and offer suggestions for the learning mode. The experimental results demonstrate that time series-based eye movement pattern mining can identify directors’ viewing habits, and clustering can reveal different learning strategies that can be used to evaluate directors’ corporate law learning status. Additionally, the CNN-based emotion recognition model experiment also shows that the established model has an accuracy of 97.0035% and an F1 of 0.9412 in the CASIA-FaceV5 dataset, which helps evaluate the emotions of directors when learning company law.

This research examines the influence of digital literacy on preschool children’s school readiness and mental health. The analysis dissects psychological resilience’s role as a mediator among digitally literate-conscious kids. The underlying theory underpinning the literature is a social learning theory, which provides the paradigm lens for effectively accessing and evaluating available digital information. This study measures these proposed assumptions using structural equation modeling techniques. Data collection was carried out in structured questionnaires, and the target population was parents of preschool children. The study used a convenience sampling technique to select a sample of parents based on preschool children under five. The results show that digital literacy among preschoolers is directly and positively related to their school readiness, mental well-being, and resilience. Findings suggest that psychological resilience significantly mediates between children’s digital literacy and school readiness. The findings provide valued insight and further directions for policymakers and educators from developing countries. It offers valuable guidance for teachers and parents of preschool children. Findings will encourage them to allow children to use digital gadgets to build and enhance their understanding of digital information. Preschoolers should also receive implicit and explicit training in the practical and fundamental knowledge of digital technologies for their educational use. In theory, this study contributes to the scientific literature by answering how digital literacy and resilience positively impact children’s school readiness and mental well-being.