The Capital Medical University collaborates with XueTang Online
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The Intelligent Key to Mastering Medical English Terminology
Building a New Ecosystem for Medical Wisdom Education
Course Background
Artificial intelligence, as a leading technology driving a new round of technological revolution, industrial transformation, and social progress, is profoundly influencing the innovation and development of the education sector. It not only changes traditional teaching models but also provides new possibilities for education, making personalized, interactive, and intelligent learning methods a reality. General Secretary Xi Jinping emphasized that China attaches great importance to the profound impact of artificial intelligence on education, actively promoting the deep integration of artificial intelligence and education to facilitate educational reform and innovation.
The School of Humanities at Capital Medical University actively responds to the national call for the deep integration of artificial intelligence and education, using the “Medical English Terminology” course as a pilot project, leveraging artificial intelligence technology to empower English vocabulary teaching, and exploring new pathways for teaching medical English terminology in the era of digital intelligence.
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Overview of the “Medical English Terminology” Course
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Course Introduction
Medical English terminology is the foundation for medical students to engage in professional learning and academic research, characterized by long words, large quantities, and difficult pronunciations. The “Medical English Terminology” course offered by Capital Medical University deeply explores the word formation rules of medical English terminology, using the human body systems as the main thread, progressing from easy to difficult, from basic to clinical, layer by layer, transforming the vast medical English terminology into manageable, easily mastered categories, helping students quickly and firmly grasp the rules and methods of medical English terminology formation, effectively overcoming the challenges of complex and difficult-to-remember medical professional terms, and laying a solid professional language foundation for medical students’ professional learning and medical research.
The accompanying MOOC “Advanced Medical English Vocabulary” was launched on the XueTang Online platform in October 2019, and by September 2024, more than 60,000 students have enrolled. In April 2021, the course was launched on the Learning Power platform and has been streamed over 360,000 times. In April 2020, it was first launched on the XueTang Online International Version Platform, serving students worldwide, especially medical students from countries along the “Belt and Road”, actively promoting the global sharing of high-quality teaching resources from China. This MOOC was awarded the second batch of national-level online first-class undergraduate courses in 2023.
Relying on the high-quality teaching resources of the national-level online first-class undergraduate course, a high-quality course resource map is constructed, using technologies such as retrieval enhancement and generation, integrating “knowledge, large models, big data, and computing power”, to create an AI course for “Medical English Terminology” that has the characteristics of Capital Medical University’s medical English teaching and serves as a demonstration for a wide audience.
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AI Course Development Team
Team from the Department of Applied Linguistics, School of Humanities, Capital Medical University
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“Medical English Terminology” AI Course Objectives
Teaching Needs and AI Solutions for Medical English Terminology
Medical English terminology has professionalism and complexity, with long words, large quantities, and difficult pronunciations, and many terms originate from Latin or Greek, making students often find it difficult to memorize terms, leading to feelings of anxiety and loss of interest in learning.
Mastering medical English terminology not only requires understanding and memorization but also requires repeated practice and extensive application and practice. However, traditional classroom teaching usually has limited time and cannot fully cover all the learning needs for terminology. This requires students to make full use of their extracurricular time to strengthen their mastery of terminology. However, when students study independently outside of class, due to a lack of effective guidance and timely feedback, their efficiency in learning terminology is relatively low.
In the process of teaching medical English terminology, due to the uneven mastery levels of terminology among medical students, teachers find it difficult to meet each student’sindividualized learning needs. Some students need to practice memorizing roots and affixes, while others hope that teachers provide more opportunities to apply medical terminology in actual clinical situations.
To address the above issues, the “Medical English Terminology” course team hopes to introduce artificial intelligence technology to empower English vocabulary teaching, achieving the following construction goals:
Provide personalized and intelligent learning experiences
Improve medical students’ efficiency in learning terminology
Through 24-hour intelligent companions, knowledge graphs, resource retrieval, and other AI tools, AI provides real-time feedback and guidance for medical students learning medical English terminology, offering one-on-one question-and-answer support anytime and anywhere, assisting medical students in self-learning medical English terminology, and motivating students’ intrinsic drive to learn terminology. AI can plan personalized learning paths based on students’ learning data and performance. For example, AI can monitor students’ mastery of specific terms and provide targeted exercises and quizzes.
Through contextualized and interactive learning
Enhance medical students’ interest and motivation in learning terminology
Mastering medical English terminology requires students to engage in extensive memorization and practice; however, traditional methods of reinforcing terminology learning through explanations and training can diminish students’ motivation to learn. AI can enhance student engagement and motivation through interactive learning and simulated clinical scenarios, such as virtual case discussions and dialogue simulations, allowing students to apply and reinforce terminology in practice.
Freeing Teacher Productivity
Promoting Teaching Innovation and Enhancing Teaching Quality
Traditional teaching of medical English terminology requires teachers to spend a lot of time and energy creating terminology exercises, searching for materials, and grading students’ assignments. By introducing intelligent lesson preparation assistants and intelligent grading AI tools, teachers can efficiently complete assignment grading, test question creation, and timely analysis of students’ learning performance, freeing teacher productivity, enabling teachers to focus more on top-level medical terminology teaching design, addressing students’ individualized needs, providing targeted guidance, and promoting teaching innovation and quality enhancement.
Data-Driven
Helping Teachers Improve the Effectiveness of Terminology Course Teaching
AI-enabled terminology teaching can collect a large amount of student learning data, and through data analysis, it can identify areas where students excel and which terms are easily confused or forgotten, understanding students’ learning status and adjusting teaching strategies in a timely manner. This not only helps students achieve personalized learning but also provides teachers with feedback on the effectiveness of terminology teaching. Teachers can continuously optimize teaching content and methods based on this data to improve the effectiveness of terminology course teaching.
Grasping Trends, Exploring New Pathways for
Medical English Terminology Teaching in the Era of Digital Intelligence
The “Medical English Terminology” course team collaborates with the AI4E (AI for Education) team from XueTang Online to create an AI course for “Medical English Terminology” that covers all teaching scenarios for teachers and students.
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Building a Course Knowledge Base Based on Intelligent Large Models
Relying on the Yu Classroom platform, the course team associates recorded MOOC resources, integrating course textbooks, lecture notes, exercise papers, and micro-course videos on medical English terminology, forming a dedicated knowledge base for the “Medical English Terminology” course. The establishment of the course knowledge base enhances the large model’s ability to recognize questions and improves the accuracy of responses, effectively reducing the hallucination of the large model.
At the same time, through continuous testing and Q&A feedback, the stability and usability of the course model are improved.
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Building Course Enhancement Models Based on RAG and Other Technologies
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Course Model
Various teaching analysis models established based on the local knowledge base, including knowledge base modeling and vectorization, knowledge graphs, capability models, question models, and various algorithms including adaptive learning paths, will serve as back-end support for the application layer, enhancing precision.
After generating a resource map based on the course knowledge base, the course team sets intelligent lesson preparation, intelligent grading, and 24H intelligent companion-related command tags, and constructs a course-specific enhancement model based on the actual teaching needs and characteristics of the “Medical English Terminology” course.
AI intelligently integrates learning resources based on teachers’ and students’ learning needs, summarizes course content, and forms a four-level knowledge graph for “Medical English Terminology”.
Students rely on the knowledge graph to engage in exploratory and autonomous learning, during which they can interact with AI, obtain learning resources related to knowledge nodes, and receive personalized learning path recommendations.
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AI Workbench and Command Library
XueTang Online provides teachers with an AI Teacher Workbench as the hub for AI course development, where teachers can set unified commands for courses based on subject characteristics and course needs, train Q&A templates, and facilitate more efficient and convenient use of AI capabilities by teachers and students.
The course team has carefully designed roots and affixes, medical terminology, descriptions and explanations, translations, spelling checks, question generation, body/subject terminology, doctor-patient communication, and medical record writing into10 command groups, with 31 preset commands, aimed at guiding students to deeply learn professional terminology according to teaching key points and teachers’ expectations, answering questions encountered in terminology learning, and providing timely and accurate feedback and effective guidance, overcoming the limitations of traditional teaching where extracurricular independent learning lacks guidance.
Setting up thematic commands for roots, affixes, and terminology to help students accurately master medical English terminology and cultivate a spirit of excellence in the medical field.
Setting up thematic commands for descriptions, explanations, translations, and medical record writing to guide students in applying terminology in practical contexts, aiding in medical students’ professional development.
Setting up thematic commands for exploring etymology and culture to guide students to pay attention to the cultural characteristics behind professional terminology, cultivating students’ cross-cultural abilities and enhancing their global perspective and cultural confidence.
Setting up commands for stories of famous medical figures to help students learn about the perseverance and exploratory spirit of renowned figures in the field of science, and to inspire students to establish a correct professional outlook, cultivate a sense of responsibility and mission.
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Integrating AI Throughout the Teaching Process
Creating a Dedicated Intelligent Teaching Assistant for Teachers
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Intelligent Lesson Preparation Assistant
During the lesson preparation phase, the course team utilizes artificial intelligence technology to optimize the lesson preparation process. AI can deeply understand the teaching needs and characteristics of the “Medical English Terminology” course, assisting teachers in automatically generating outlines, case studies, and detailed explanations of knowledge points, thereby enhancing teachers’ lesson preparation efficiency.
During lesson preparation, the AI one-click question generation function automatically generates various types of exercises and inserts them at appropriate locations in the courseware based on contextual knowledge points, and can easily change or modify questions.
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Intelligent Grading
Grading assignments occupies a significant amount of time for the course team. After introducing AI, the burden on teachers has been greatly reduced, improving students’ assignment quality and teachers’ grading efficiency.
AI grading sets grading rules according to the scoring framework in the AI workbench for students’ submitted assignments, allowing AI to perform intelligent grading based on the corresponding grading rules.
Teachers review and confirm AI’s grading content, including scores, comments, and annotations, and if there are no issues, the results are sent to students.
Students can also engage in dialogue with AI regarding the feedback provided by AI, which helps students develop the ability to analyze, question, and filter AI feedback, thereby enhancing their logical analysis, evaluation, and judgment skills.
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24-Hour Intelligent Companion
AI is no longer just a tool but a smart learning partner available to students around the clock.
With around-the-clock assistance, students can effectively engage in self-directed learning and explore learning through interaction with AI. The AI companion provides customized exercises and suggestions based on students’ learning progress and terminology mastery, helping students strengthen their weaknesses and achieve personalized learning.
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Intelligent Agent Collaboration
The next step will be to develop AI agents that assist students in doctor-patient dialogues and case discussions among doctors through role-playing, creating realistic scenarios for students to apply professional terminology in practice.
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More Intelligent Management:
Facilitating the Leap from “Management” to “Intelligent Governance” in Teaching
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Intelligent Management Assistant
AI provides visual data support for teaching management
The smart teaching platform collects teaching process data through non-intrusive, accompanying methods, accumulating vast amounts of educational data and response materials, and through deep analysis and precise predictions, identifies students’ learning difficulties and common errors, thoroughly analyzes students’ learning situations, and deeply understands their learning needs, assisting teachers in quickly adjusting teaching strategies to ensure teaching is more targeted and effective.
Based on learning situation analysis, a one-click teaching report is generated for evaluation and teaching summary, providing scientific and precise data support for teaching management personnel, thereby promoting teaching decisions to develop in a more intelligent and efficient direction.
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Intelligent Research Assistant
AI Propelling the Intelligence and Efficiency of Research Work
The “Medical English Terminology” AI course combines cutting-edge large model technology and intelligent retrieval tools, fully utilizing user learning behavior data to achieve personalized resource recommendations. Relying on the rich MOOC resources of XueTang Online, the course can accurately match students’ learning needs and intelligently push the most appropriate medical English content. In addition, AI can efficiently retrieve relevant materials from external public resources, further expanding access to learning and research resources.
Through this intelligent platform, teachers and students can not only efficiently improve their medical English skills but also continue to progress in research and teaching, obtaining the latest and most valuable reference information.
With the support of generative artificial intelligence technology, the Applied Linguistics team at Capital Medical University’s School of Humanities collaborates closely with XueTang Online to create a new ecosystem for basic medical wisdom education, providing more intelligent and personalized educational services, injecting new momentum into the continuous improvement of educational quality.
Source | XueTang Online
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