Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Based on Knowledge Graphs and Virtual Simulation
Digitalization of Medical Education
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

This article received the “Best Practice” award at the Medical Education Forum (2023)

Authors: Jia Mozhi, Zou Qinghua, Yu Yanrong, He Xiaoyan, Peng Yihong*

(Department of Pathogenic Biology, Peking University School of Basic Medical Sciences, Haidian District, Beijing, 100083)

Abstract

The 20th National Congress of the Communist Party of China first included “Promoting Educational Digitalization” in its report, making educational digital transformation the primary task of current educational reform and development, while also providing opportunities for the transformation of medical education. Our team, based on digital technologies such as knowledge graphs and virtual simulations, has launched key teaching resource demonstration courses such as “Understanding the Novel Coronavirus” and “Isolation and Identification of Influenza Virus in BSL-2 Laboratories” as part of the strategic emerging fields “14th Five-Year Plan” textbook construction, promoting diversification in course models and resources. We have also explored the construction of capability maps for comprehensive student ability evaluation based on experimental courses, innovating the assessment methods for student competencies, laying a foundation for advancing the digital transformation of medical education. Our educational digitalization—from theory to medical education practice—has achieved multiple promotion results.

With the rapid development of digital technologies, educational digital transformation has become a necessary option for the survival and development of higher education. Recently, the Ministry of Education issued the “Action Plan for Deepening Curriculum and Teaching Reform in Basic Education” emphasizing the need to “promote digital empowerment for the enhancement of teaching quality,” indicating that pushing educational digital transformation and effectively improving teaching quality to cultivate professionals for the digital age has become the primary task of current educational reform and development.
Educational digitalization has brought significant changes and opportunities to education, including the construction of new types of textbooks, the reshaping of course models and resources, and the development of teacher teams, all of which are vital components of building a high-quality education system. Knowledge Graph (KG) is currently one of the fastest-developing and widely-applied artificial intelligence technologies in professional fields such as education, representing a semantic-based method that organizes entities into a graph, revealing the interrelationships and inherent laws among entities through a structure of nodes (entities) and edges (relationships between entities). KG uses visual graphs to vividly display the core structure, development history, cutting-edge fields, and overall knowledge architecture of specific domain knowledge.
The digital elements centered around digital technologies and data resources are key to advancing educational digital transformation, and KG, as one of the important tools of digital technology, plays a significant role in the process of educational digitalization. Our team, based on KG and other digital technologies, has focused on textbook construction, promoting diversity and variety in course models and resources, and exploring the construction of capability maps for comprehensive student ability evaluation based on experimental courses, laying the groundwork for a new ecosystem of digital teaching. Our team has explored and practiced in the following areas.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

1. The Practice of New Textbook Construction Promoting Educational Digitalization

New types of textbooks are built on the foundation of digital textbooks, characterized by convenience, multimedia, personalization, openness, interactivity, and efficient dissemination, breaking through the limitations of traditional textbooks, and becoming an important support for the digital transformation of education. The development and use of new types of textbooks are key links in building a strong educational nation, serving as a carrier for implementing national educational policies, and embodying a new educational philosophy that serves the “digital natives” of the information age, carrying the mission of cultivating talents needed for a digital society.
New types of textbooks are products of the integration of traditional paper textbooks and modern digital technologies, inheriting the scientific rigor of traditional textbooks while presenting unique informational characteristics due to advanced digital technologies. Digital textbooks can be seen as electronic books used for course teaching, based on course knowledge content, presented with rich media digital elements, integrating various learning interactions and tools as needed for teaching activities, and packaged for formal publication according to certain standards, disseminated via the internet. Existing digital textbooks can generally be categorized into three types: electronic text, multimedia, and massive open online courses.
The team has summarized the advantages and characteristics of new digital textbooks through research, which should include but are not limited to:
Rich Media Presentation New digital textbooks can overcome the limitations of traditional paper textbooks, presenting immersive, vivid, and three-dimensional experiences to learners through videos and virtual simulations, achieving the “contextualization” and “visualization” of teaching content.
Personalized Customization New digital textbooks rely on platforms that can collect personalized learning data from learners, conduct comprehensive analysis and evaluation to understand each learner’s characteristics and needs, and customize teaching information that aligns with individual learning interests and needs. This “customized” textbook written for users of different levels and learning purposes can meet the needs of different individuals, achieving “teaching according to aptitude.”
Interactivity Learners can utilize various forms provided by digital textbooks for learning, submit assignments, self-test, and can also introduce a series of new learning experiences based on learner feedback at any time. Additionally, it can provide practical exercises or operations according to learners’ progress, helping them analyze learning outcomes and identify shortcomings. Furthermore, it can facilitate various direct and indirect interactions, enabling interactions between teachers and students, as well as among learners.
Coverage of the Entire Teaching Process New digital textbooks, based on digital platforms, integrate teaching content and activities, covering core teaching links such as teaching, learning, practice, assessment, and evaluation.
Rapid Updates and Efficient Dissemination In 2020, the novel coronavirus (SARS-CoV-2) spread globally, but relevant knowledge was missing in the “Medical Microbiology” textbook and could not be updated in time, exacerbating societal panic. Digital textbooks do not have the publishing cycle issues of traditional books and can be updated at any time. Based on the internet, they have the characteristics of wide dissemination and fast speed, allowing learners to obtain the necessary professional knowledge promptly. These characteristics of digital textbooks make it easier for learners to access the latest and best materials in a timely manner, while promoting resource sharing and educational equity.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Figure 1: Currently Launched New Textbooks
Based on a series of studies on new types of textbooks, the team proposed a construction plan for new textbooks that integrates KG and virtual simulation experimental projects, utilizing rich media technology to break through traditional textbook content and length, academic systems, and specialties, allowing for dynamic updates and open digital textbooks. Among them, Professor Peng Yihong, as one of the editors, has initiated the strategic emerging field “14th Five-Year Plan” textbooks “Medical Virology” and “Medical Virology Laboratory” (Science Press), and the core textbook of the “101” plan “Pathogenic Biology and Immunology Basics” (Peking University Medical Press), with the textbook writing kickoff meeting already held, collaborating with publishers to create national-level new textbooks that adapt to the digital transformation of education. Meanwhile, the team has constructed a digital case library for “Human Parasitology” based on learning feedback, creating KG-based learning resources (Figure 1).
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

2. Course Resource Construction Promoting a “Quality Revolution” in Medical Education

In 2020, the Ministry of Education initiated the construction of teaching resources in certain fields, building quality teaching resource libraries annually in key areas, exploring new paths for teaching resource construction and talent training models under the concepts of “new engineering, new medicine, new agriculture, and new liberal arts.” Professor Peng Yihong, as an expert in the Ministry of Education’s key teaching resource and new textbook construction expert group, led our team in building a demonstration course closely related to the pandemic in the field of virology (https://virology.spacekg.com), applying KG in the teaching process to comprehensively decompose the hierarchical structure of the knowledge system, clarify learning objectives and paths, and timely enhance teaching and learning quality. Additionally, as an important component of process evaluation and summative assessment, it optimized the structure of course evaluation, receiving widespread acclaim from learners after multiple rounds of teaching practice. Moreover, while teaching, educators can achieve the transformation of “systematic teaching resources, visualized learning feedback, and intelligent learning management” through relevant platforms, thereby promoting a “quality revolution” in medical education.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Figure 2: Course Design Based on Knowledge Graphs
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

3. Utilizing Virtual Simulation to Present Realistic Teaching

Virtual simulation uses computer technology and virtual reality technology to simulate real environments and scenarios, providing learners with a more authentic, vivid, and intuitive learning experience and practical operations. This multi-sensory immersive learning helps enhance learners’ understanding and learning outcomes. Using this technology, learners can “be on-site” without leaving home and can perform operations such as laboratory diagnostics (Figure 3). The National Virtual Simulation Experimental Teaching First-Class Course “Isolation and Identification of Influenza Virus in BSL-2 Laboratories” established by our team can avoid operational restrictions and dangers due to biosafety issues. Moreover, learners can repeatedly perform operations and practices, improving their practical skills. This form of experimental teaching aligns with the current learning habits of learners, and course feedback satisfaction is extremely high.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Figure 3: Teaching Scene Presented by Virtual Simulation
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

4. Capability Map Construction to Promote High-Quality Talent Output

A capability map includes the KG of learner ability evaluation. By utilizing the underlying principles of KG, we match and identify relevant capability elements (“attributes of entities”) contained in each knowledge point (“entities””), integrating the capability evaluation system into the basic units of KG (points and lines), where points and lines include subject knowledge and multi-dimensional capability evaluation elements that match the knowledge, combined with indicators such as trial-and-error and problem-solving processes during the experimental process, to complete the construction of capability maps based on practical course capability cultivation. This utilizes massive data to form learner capability profiles, promoting scientific and personalized teaching evaluation, implementing technical means and specific parameters for teaching according to aptitude. Based on the capability map, a blended teaching platform is established to promote innovation in teaching paradigms.
For example, our team, based on the intermediate KG of the National Virtual Simulation Experimental Teaching First-Class Course “Isolation and Identification of Influenza Virus in BSL-2 Laboratories”, enables learners to guide their own learning and thinking through problem-solving, design and practice independently, and develop higher-order thinking skills, achieving a transformation from unthinking to thinking, from shallow thinking to deep thinking, and from linear thinking to reflective thinking. In the creation of advanced KGs based on capability dimensions, we continuously enrich the practical teaching resource library, allowing KG-based course construction to approach perfection, thereby truly reflecting the integration of teaching, learning, and practice (Figure 4). The establishment of the capability element system will start from core competency goals, process and method goals, and emotional attitudes and values goals, sorting out capability evaluation points that match the KG framework, forming a corresponding capability map integrated with KG. Additionally, the map can establish connections with teaching resources (textbooks, test questions, teaching videos, exam papers, etc.), thereby accurately depicting learners’ knowledge mastery and resource characteristics, facilitating precise assessments of users’ learning conditions and capability development.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Figure 4: Capability Map Construction Based on Influenza Virus Virtual Simulation Experiment
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

5. Achievements Obtained

1. New Textbook Construction: ① Strategic Emerging Field “14th Five-Year Plan” textbooks: “Medical Virology” and “Medical Virology Laboratory” (Science Press); ② Core textbook of the “101 Plan”: “Pathogenic Biology and Medical Immunology Basics” (Peking University Medical Press); ③ Construction of the Human Parasitology Case Library based on KG.
2. Demonstration course in the field of virology as a key teaching resource from the Ministry of Education: The series of micro-courses “Understanding the Novel Coronavirus” is launched on the virology teaching resource sharing service platform (https://virology.spacekg.com) and is recommended for the third batch of national first-class courses as a demonstration course in the field.
3. Establishment of the National Virtual Simulation Experimental Teaching First-Class Course “Isolation and Identification of Influenza Virus in BSL-2 Laboratories” (2020).
4. The research project “Construction of Medical Virology Capability Map Based on Practical Ability Cultivation” has been included in the 2023 work plan of the National Virtual Simulation Alliance’s Basic Medicine Professional Committee (Figure 5).
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Figure 5: Summary of the National Virtual Simulation Alliance Basic Medicine Professional Committee 2023 Work Plan
5. Approval of two related research funding grants:
① Ministry of Education Industry-University Cooperation Collaborative Education Project “Construction of Medical Virology Experimental Course System Based on Knowledge Graphs,” project leader Peng Yihong (Figure 6);
② Peking University Undergraduate Teaching Reform Project (2023): Research on the Construction Plan of Medical Virology Digital Textbook, project leaders Peng Yihong and Jia Mozhi.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Figure 6: Ministry of Education Industry-University Cooperation Collaborative Education Project Approval
6. Invited by the National Center for Medical Education Development and the National Teaching Development Alliance for Medical Schools, Professor Peng Yihong, along with experts from Fudan University, Peking Union Medical College, and the Ministry of Education’s Key Teaching Resource Management Office, hosted the 14th Medical Education Debate Teaching Seminar (Figure 7), receiving widespread attention and praise from teachers and administrators of medical schools nationwide.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Figure 7: 14th Medical Education Debate Teaching Seminar
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

References

[1] Li Lin, Lin Wei, Chen Ye, Xia Changqing, Chen Zhenxin. Understanding and Reflection on Digital Textbook Construction. Chinese Editor. 2021(5). 58-61.
[2] Zeng Bin, Liu Haili. Exploration of Paths for Digital Textbook Construction and Application in China. Science and Publishing. 2023(2). 62-68.
[3] Wang Liyong. Discussion on the Necessity of Digital Textbook Development in Higher Education Institutions in the New Era. Communication and Copyright. 2020(3). 116-118.
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation
Best Practices in Medical Education Digitalization Based on Knowledge Graphs and Virtual Simulation

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