The challenges of personalized learning and their solutions

Abstract

Since ancient times, the dream of realizing inclusive, fair and personalized learning has been chasing in the education filed all over the world. With the rapid development of information technologies, the traditional large-scale education system generated in the industrial revolution era cannot satisfy the increasing demand for personalized education services in the information era. Thus currently the reform and innovation of education is at a critical turning point. To specify, personalized learning is being focused on during the global education innovation and reform, and deep reform within the education field is being promoted by big data technology. Compared with other countries, during the current global education innovation and reform, China is facing more difficult challenges caused by a large number of active learners, complex learning environment, large-scale education resource supply, and a wide variety of learning service. Therefore the problem about how to provide large-scale, high-accuracy and personalized learning in China needs to be solved urgently, which is unique without precedents. The arising of information technologies, such as internet, cloud computing, big data, and artificial intelligent, has brought in not only diversified resources, scale data, and intelligent computing, but also the fusion between education and natural science. Consequently, the scientific paradigm of education has been changed from traditional experience-based research into data driven research. Such change, on the one hand, has offered a new approach to realize accurate and scientific education; on the other hand, has made an initial breakthrough in personalized learning. A historical opportunity to educate a learner according to his/her natural ability has finally arrived. To promote the data-driven application innovation as well as to achieve scale and personalized education, have both become an inexorable trend for the modern education. Due to the continuous influence of information technologies, the boundaries of learning time and space have both been broken completely. In addition, many great changes have taken place in learning environments, methods and contents, which obviously provide learners with more choices about what to learn and how to learn. In the future, the aim of personalized learning is to satisfy the personalized development demand for each learner, however it will definitely face serious challenges, e.g., how to understand learning subjects, how to construct learning environment, and how to implement teaching. In this paper, three basic scientific problems to be solved in personalized learning are discussed, which include (1) educational scenarios is calculable; (2) learning subjects is understandable; (3) learning services is customizable. Furthermore, in order to realize differentiated instruction, personalized learning, refined management, and intelligent services, breakthroughs in both theories and technologies needed are presented in this paper, including human-technology learning environment, learning data sensing and fusion, edge computing for education scenes, learning mechanism in digital environments, student modeling and analysis under data driven, group dynamics of the learner group, education resource supply, accurate education service, intelligent tutoring system. Education is a complex dynamic system, which needs both breakthrough research and systematic research. To effectively promote the research of personalized learning, actions needs to be taken, including for example implementing education research and experiment systematically, speeding up breakthroughs and talent training, solving scientific problems in the education field by means of multidisciplinary approach and wisdom as well as the multi-party cooperation mechanism named "politics-industry-academic-research-application". Based on a comprehensive analysis on counter-measures and research trends to personalized learning in western developed countries, in order to cope with challenges of personalized learning and help meet the goals of Education 2030 in China, the following four suggestions are proposed in this paper: (1) promoting the formation of educational science; (2) speeding up the construction of laws and regulations related to large-scale educational data; (3) exploring data-driven instructional evaluation mechanism and methods; and (4) increasing policy support in the research on teaching competency standards and teachers' promotion path in the new era.