Multimodal interaction technology has become a key aspect of remote education by enriching student engagement and learning results as it utilizes the speech, gesture, and visual feedback as various sensory channels. This publication reflects on the latest breakthroughs in multimodal interaction and its usage in remote learning environments, including a multi-layered discussion that addresses various levels of learning and understanding. It showcases the main technologies, such as speech recognition, computer vision, and haptic feedback, that enable the visitors and learning portals to exchange data fluidly. In addition, we investigate the function of multimodal learning analytics in order to measure the cognitive and emotional states of students, targeting personalized feedback and refining instructional strategies. Though multimodal communication may bring a historical improvement to the mode of online education, the platform still faces many issues, such as media synchronization, higher computational demand, physical adaptability, and privacy concerns. These problems demand further research in the fields of algorithm optimization, access to technology guidance, and the ethical use of big data. This paper presents a systematic review of the application of multimodal interaction in remote education. Through the analysis of 25 selected research papers, this review explores key technologies, applications, and challenges in the field. By synthesizing existing findings, this study highlights the role of multimodal learning analytics, speech recognition, gesture-based interaction, and haptic feedback in enhancing remote learning.

With advances in digital transformation (DX) in education and digital technologies becoming more deeply integrated into educational settings, global demand for video-based learning materials continues to rise, resulting in substantial effort being required from teachers to create e-learning videos. Furthermore, while many existing services offer visual content, they primarily rely on templates, making it challenging to design custom content that addresses specific needs. In this study, we develop a web service that facilitates e-learning video creation through integrated artificial intelligence (AI) and digital human technology. This service enhances educational content by integrating digital human characters and voice synthesis technologies, aiming to create comprehensive e-learning videos by incorporating visual motion and synchronized audio into educational content. In addition, this service also aims to enable the creation of engaging content through advanced visuals and animations, effectively maintaining learner interest.