Research On Personalized Teaching Based On Learner Portrait

With the application of Internet technology in education and teaching,the storage of recorded learning data will become a valid proof of learners' learning performance.Personalized teaching is based on the individual characteristics and individual differences of learners.It is the current teaching trend and an important part of educational development.Therefore,using the learning data to draw accurate learner portraits will provide an objective basis for the smooth development of personalized teaching.However,the current research on learner portraits mainly focuses on the design process of the learner's portraits and the concept labeling.It is rare to combine the actual teaching situation,to draw the learner's portrait,and apply it to the subject for personalized teaching.Based on the above problems,this paper mainly studies how to design the learner's portrait,and use the learner's portrait for personalized teaching,so as to improve the learner's learning quality.Take the "Modern Educational Technology" course as an example,taking the preschool education students of a vocational college in Jinhua City as the research object.The first half of the semester's task is to collect learner behavior data,including basic information,classroom teaching data,online self-learning data,test and assignment data,questionnaire voting data,etc.Then use Microsoft Visual Studio and Unity software to write the code in C# programming language.The learner's portrait is design from four dimensions: media preference,learning style,learning engagement and knowledge level.Among them,media preferences include text,picture,audio and video.Learning styles include reflector,activist,pragmatist and theorist.From the aspects of behavior,emotion and cognition,learning engagement divides learners into three levels: high engagement,medium engagement and low engagement.Knowledge level divides learners into four levels:excellent,good,general and poor from three aspects: declarative knowledge,procedural knowledge and strategic knowledge.Finally,according to the individual portrait data,K-means clustering is carried out in R language,and three groups of learners with excellent,good and poor overall learning conditions are subdivided.In the second half of the semester,first of all,through the learner's portrait to understand each learner's learning state;Secondly,according to the teaching content,the courses are divided into three types: skill operation,independent practice and theoretical principle,and design a personalized teaching process.Finally,the learner's portrait and teaching design are applied to the teaching,and the data of the second half of the semester is compared with that of the first half of the semester.It can be seen that this teaching method is conducive to improving students' engagement and participation in learning and improving their learning quality.