Application status and development of big data in medical education in China

Ke-Jia Liu,Yu-Di Cao,Yue Hu,Li-Jiao Wei

School of Nursing,Tianjin University of Traditional Chinese Medicine,Tianjin,301617,China.

Abstract With the development of information technology,big data has been widely used in medical education in China.Through the analysis of the definition,characteristics and development process of big data,summarized the transformation of domestic big data medical education mode compared with the traditional medical education mode in the teaching mode reform,research method innovation,teaching courses optimization,teaching key extension and the teaching quality monitoring.Based on this,this paper expounds the impact and challenge of big data on medical education,and makes an outlook on its development prospect,indicating that the future development of big data will be open,popular and trending.At the same time,some suggestions on further optimization direction of China's big data medical education are put forward.

Keywords:Big data,Medical education,Education reform,Training mode

1.Introduction

With the development of information technology,big data,cloud technology and artificial intelligence have been gradually applied in our daily life and widely applied in the field of medicine.It has become an effective way to store and obtain important information by organizing,analyzing and collecting a large amount of original data into data sets[1].It can be said that we are now in the era of big data.Big data provides information in an efficient and accurate manner in the era of rapid development,which changes people's lives and affects their understandings about the world and their formation of value orientation[2].Meanwhile,big data has caused fundamental changes and progress to a variety of disciplines including medicine,politics,sociology,economics,etc[3].

Nowadays,big data has been basically popularized,becoming an important way to acquire knowledge.Therefore,teaching is no longer merely about knowledge delivery,but more about the guidance for students to learn as much as possible,and the cultivation of their ability of independent learning.Different from other disciplines,medical education emphasizes multi-level cultivation.Teachers should not only deliver medical knowledge to learners and develop their independent learning ability,but also attach importance to scientific research education,keep abreast with the latest research trends,and construct learners' scientific research ideas while paying attention to the cultivation of learners' practical ability and clinical practice ability[4].There are many defects in the traditional medical education system,such as unreasonable curriculum setting,single teaching methods,limited assessment system,insufficient medical education resources,and poor cooperation between teaching and clinical practices[5].

Therefore,on the basis of the traditional medical education model,it is necessary to continuously learn more about big data technology and update teaching concept, so that more suitable teaching and learning methods for medical students can be explored through data analysis and application to further promote the development of medical education in China[6].

This paper aims to summarize the transformation from traditional medical education mode to big data medical education mode in China from the perspectives of teaching mode reform,research method innovation,teaching courses optimization and teaching key extension as well as teaching quality monitoring.On this basis,the impacts and challenges of big data on medical education in China is analyzed.Finally,the development prospect is predicted and further optimization direction of China's big data medical education is proposed.

2. Concept of big data

2.1 Definition of big data

Big data,also known as massive data,is composed of a large number of data integration with diverse data types and complex structures[7].Data are processed,integrated or shared through cloud technology[7].International Data Corporation (IDC) defines big Data as:a new generation of technology and architecture with excellent capabilities in discovery,capturing and analysis,which is able to easily extract effective value from a large number of complex types of data[8].According to the bookBig data:A revolution that will transform how we live,work,and think,big data refers to a method that directly analyzes and processes all data without adopting the experimental method of sampling survey[9].Its core value lies in obtaining valuable products or insights by analyzing massive data,and finally forming the power of revolution[10].Medical big data includes not only a large amount of physiological data collected by a variety of devices,but also a huge amount of omics data generated by a new generation of technologies.The data involves in not only health records and medical records but also disease surveillance,public health and epidemiology on the Internet[11].

2.2 Characteristics of big data

The analyst Doug Laney of Gartner US defines the rapid growth of data in three dimensions:quantity,speed and variety[12].Quantity represents the growing number and scale of data generation[12].Speed represents the timeliness of data collection and analysis[12].Type means that the type of data includes not only structured data,but also semi-structured data and unstructured data such as:pictures,audio,video,network logs,information,etc[12].IDC proposes 4V features in the definition of big data,including:Volume,Velocity,Variety and Value[13].After the emergence of the Internet of Things (IoT),data types have become more and more diversified.It can be said thatevery existence is connected,and every connection is data.

2.3 Development of big data

The origins of big data can be traced back to the early 1980s when sociologist Alvin Toffler made forwardlooking predictions about the coming of Big Data Era[14].In March 2012,President Obama announced that the US government planned to invest 200 million dollars in researches to accelerate the development of big data and elevate big data researches into a national strategy of US[15].In the same year,the New York Times officially announced to the world about the arrival of big data[16].At present,the Chinese government attaches great importance to the development of big data and clarified its significant role and strategic position.The word Big Data was included in the government work reports of the Two Sessions in recent years[17].

3.The application of big data in medical education in China

3.1 Reform of the educational model

The traditional education mode flourished in the industrial era,consisting of school,teacher and student.Teachers deliver lessons and students listen to teachers'lessons.The talented students are cultivated through cramming education.However,big data education model presents new teaching features,including independent learning,personalized tutoring,flexible school system and family learning[18].The cramming education is changed into heuristic teaching for teachers[3].Students are gradually transformed from capable talents into quality talents,which specifically involves scientific,humanistic and life quality[3].The process makes it clear that teaching center officially changes from teacher to student under the big data education model[19].

Some researches put forward that the most typical exploration in the teaching mode is the flipped classroom between teachers and students where learners can select courses according to their own needs for knowledge and teachers can truly achieve individualized teaching[4].Luo[20]proposed that supportive medical education was gradually established under the big data teaching mode.Teachers no longer rely on experience,but improve details in the teaching process and then deliver those details to students accordingly,which is expected to achieve effective knowledge transfer[20].Meanwhile,online medical education is also being optimized.In addition to flipped classroom,Massive Open Online Courses(MOOCs) are also established to lay a foundation for new Internet-based education model worldwide[20].MOOCs are a process that integrates learning,social examination with recognition learning where online learning,big data analysis and social service are integrated with each other[21].Bai[22]holds that innovative Internet-based teaching mode includes online and off line mixed teaching and comprehensive quality cultivation.Other researchers believe that big data analysis on the resources of different medical colleges can integrate educational resources and achieve the survival of the fittest[23].Some medical colleges have gradually improved their teaching strategies to cater to the needs of big data era.as the strategies include reducing teachers' teaching and increasing group cooperative learning.It also includes the application of medical simulation teaching and standardized patient teaching in clinical teaching,and popularization of virtual reality (VR) medical treatment and simulation experiments[5,19].In addition,there is an electronic schoolbag (E-bag),which is a portable terminal with cloud-based digital education resources that can be used for teaching[19].The teaching resources like electronic textbooks,literature,question banks,dictionaries,etc.are also included to support and follow up the overall big data learning chain[19].

In short,compared with the traditional medical education model,the big data medical education model has many changes with distinctive characteristics of The Times (see Table 1).

Table 1.Comparison of medical education modes

3.2 Innovation of research methods

Big data is also being used in research reforms.The survey method is transformed from traditional sampling survey to full data survey,which is used to directly analyze all the data of the research object,intuitively reflecting the concept that the sample is the whole[5].The overall data can be analyzed to effectively avoid errors in research.Moreover,predesigned baseline requirements for large sample data is not required,and high-dimensional or missing and unbalanced data can be accepted in medical big data mining technology,which is more suitable for the explosive growth of modern medical data[24-25].In the era of big data,learners' scientific research thinking should be transformed from linear thinking to reticular thinking,from single focus on analysis results to overall comprehensive analysis[6].

Kong[26]applied big data technology to analyze the discipline distribution of research results of academic papers,and identified the discipline areas that needed to be strengthened.Chu[24]believed that regularity is a core concern for the analysis and research of big data,which is helpful to predict the occurrence,development and outcome of diseases.

3.3 Optimization of teaching courses

Firstly,it is necessary to cultivate learners' big data thinking,observe and analyze the research progress in a variety of fields of medicine from the perspective of big data,understand the difference and diversity of medical big data,grasp its dynamic changes,and explore hot spots in the fields[6].Secondly,a clinical teaching platform based on big data technology should be established to optimize the combination of data generated during teaching,clinical and research,so as to provide independent learning resources for medical students to maximize the value of big data[27].Meanwhile,the big data network reform should be adopted,including producing network materials,applying network technology,enhancing media information integration,and optimizing network teaching design[28].In addition,we have been trying to develop heuristic teaching,exploratory teaching and open teaching for new teaching methods such as PAD Class and Problem-Based Learning (PBL)to further develop learners' statistical ability and scientific research quality under the big data education model[29-30].In terms of curriculum setting,courses such as data mining and information analysis should be added,and emphasis should be laid on cultivating learners' computational thinking[5,30].

3.4 Expansion of teaching emphasis

The application of big data in the field of medical education in China has stimulated three major changes of educational focus:from passive education to independent education,from exam-oriented education to quality-oriented education,and from unified education to personalized education[23].The focus of traditional medical education is to ensure learners'solid grasp of knowledge.In the big data teaching mode,more emphasis is placed on cultivating learners'systematic thinking mode and independent thinking,where educators attach importance to enlightenment rather than indoctrination[5-6].Therefore,learners'ability of information discrimination,extraction and innovation should be cultivated.Meanwhile,the emphasis of medical education should be extended to data mining,and the application of technology should be emphasized in teaching.For example,Decision Tree and other methods should be reasonably used in medical researches,so as to transform medical big data into medical knowledge results[31].

Medical colleges should combine professional features with the characteristics of the times to cultivate not only knowledge but also wisdom.By integrating big data,medical students will be cultivated into applicationoriented technical talents with both political integrity and talent,so that they can effectively transform their own values into productive forces[3,32].Hu[33]conforms to the increasing application demand of big data,builds the educational practice center of medical information technology through the cooperation mode ofschool-enterprise-industry-student-research,striving to train practical and innovative talents in medical information technology.

3.5 Monitoring of teaching quality

In the big data mode,the quality monitoring of teaching and learning in medical education has formed a relatively complete system,and accurate data information makes teaching quality more intuitive[3].Macro teaching quality evaluation indexes are subdivided into several micro indexes,so that some unmeasurable factors can be quantified[3].The application value of big data in teaching quality monitoring is mainly reflected in three aspects,including scientific decision-making of teaching,safety management of teaching data,and intelligent control of teaching resources and equipment,which are further ref lected by both teachers and students[34].

The teaching quality monitoring database is formed after personal information,teaching method,teaching attitude,classroom effect,professional quality and other indicators of the teachers of medical colleges are sorted and recorded[23].Through the analysis and application of relevant data,dynamic monitoring of the whole teaching process can be achieved[23].The evaluation of teachers and relevant courses by learners can be obtained through satisfaction survey or scale evaluation,and the selection behavior and retention rate of subsequent courses can be calculated[23].After class,students can directly test their mastery of key knowledge in this class through app or teaching platform,so as to evaluate learning effect and test teaching quality[5].It is also possible to evaluate each student's learning situation from multiple dimensions through progressive video learning and homework mutual evaluation,and integration with teaching feedback,so as to monitor teaching quality[22].

4.Impacts and challenges

4.1 The impacts of domestic big data medical education

The application of big data in medical education in China enables both educators and learners to make common progress.In the continuous reform of education and research mode,learners no longer solely rely on textbook knowledge,but carry out personalized independent learning in big data platform.Medical students no longer rely heavily on memory,but on cognition.Educators can also dynamically evaluate their own teaching quality through big data technology,which can improve their overall teaching level.It can be said that the application of big data in higher medical education not only integrates educational resources,but also optimizes educational content and improves the educational quality evaluation system[23].

4.2 The challenges of domestic big data medical education

Big data brings not only opportunities but also a series of challenges to medical education in China.Medical knowledge and life science knowledge are constantly updated,generating new data all the time.The knowledge structure of medical students can never fully satisfy the needs of the rapid development of society[35].Big data is constantly expanding information,and medical students can only keep up with the speed of knowledge development by constantly learning the latest conclusions,resulting in great pressure on medical students and even all medical practitioners.Meanwhile,information can be easily obtained,making medical knowledge more widespread.Patients are willing to spend time and energy in paying attention to their own diseases and learning relevant disease knowledge through a variety of channels [18].However,patients' non-professional medical thinking can put medical staff in dilemma.This requires medical students not only to increase their knowledge reserves,but also to develop good communication skills[18].In addition,a series of problems such as how to train medical technical talents and specific ways of data sharing,still need to be further explored and improved.

5.Development analysis

In this information age,big data is widely used in a variety of disciplines and industries,and its development has become a national strategy.The application of big data in the field of medical education in China is increasingly mature.Traditional medical education is rigid and boring,and students' learning autonomy is poor.While under the big digital medical education mode,teaching mode reform,research method innovation,teaching courses optimization,teaching key extension and teaching quality monitoring increase medical students' interest in learning,improve their learning autonomy,and enhance learning efficiency,which further will help to cultivate intelligent high-quality talents in the era of big data.As a newly sprouted thing,big data technology has primarily realized resource sharing of medical information,and the overall open resources is just around the corner.With more and more researches on big data in the higher medical education,it is bound to become a trend in the field of medical education.In general,the future development of big data will beopen,popular and trending.

In view of the challenges faced by big data medical education,the following suggestions are put forward:

(a) Although the big data technology has primarily realized the resource sharing of medical information,the search and application of resources are still limited at present.A systematic open platform or system of medical big data can be established to connect different data in different carriers and truly achieve information sharing.

(b) Medical college teachers should also receive trainings about big data,and stop the cramming teaching,so as to comprehensively realize the big data transformation of medical education.

(c) The cultivation of medical technology-oriented talents should be started by offering compulsory or optional courses of medical big data.In this way,medical students are generally equipped with basic big data thoughts,and then medical technical talents who are proficient in big data can be widely cultivated.

6.Summary

With the application of big data in domestic medical education,the traditional medical education mode has been gradually improved and optimized with more abundant educational resources,more convenient learning methods and higher educational level.The big data medical education model can not only provide a better educational environment for medical students in China,but also stimulate the progress of medical knowledge system and even the whole discipline.In spite of a series of challenges,we believe that all problems will be solved gradually with the rapid development of China's information technology,and that the prospects of big data medical education mode will be achieved to eventually promote the development of medical education.

Authors' contributions

LKJ completed the topic selection and research design.LKJ and CYD collected and analyzed the data.All the authors made suggestions for the analysis and interpretation of the data.LKJ completed the writing of this paper.All the authors read and approved the final manuscript.

Acknowledgments

The authors express their gratitude to the authors of the literature cited in this review.