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Curriculum Development of remote diagnosis and treatment courses traditional Chinese medicine IT in China

Year: 2024
Type: article
Abstract: This research aims to explore the curriculum development of remote diagnosis and treatment courses in Traditional Chinese Medicine (TCM), focusing on how information technology (IT) can be effectively integrated to enhance both the delivery and quality of TCM education. The study is structured around several key objectives: investigating the current state of remote TCM education, identifying critical issues such as insufficient content, lack of interactivity, and challenges in practical application, and proposing strategies for curriculum improvement. The research sample includes TCM educators and students from various educational institutions across China, with a focus on those involved in remote learning platforms. Research instruments include surveys, interviews, and direct observations, allowing for a comprehensive understanding of the existing educational environment. Data collection is carried out through a combination of qualitative and quantitative methods, providing a balanced analysis of both the strengths and weaknesses of current remote TCM courses. Research analysis involves statistical examination of survey data and thematic analysis of qualitative feedback, leading to a robust framework for curriculum enhancement. The research results found that remote TCM courses currently suffer from significant gaps in content coverage, particularly in areas related to practical diagnosis and treatment techniques. Additionally, there is a notable lack of interactive elements, which negatively impacts student engagement and learning outcomes. Based on these findings, the study proposes a revised curriculum framework that incorporates interactive digital tools, enhances content comprehensiveness, and provides more opportunities for practical application. These recommendations aim to improve the overall effectiveness
Language: Thai
Subfield: Education
Open Access status: diamond
OpenAlex ID: W7219320730
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