Study On Multidimensional Characteristics Of Adult Learners In Online Environment

In the information age,more and more adult learners are involved in online learning.However,opportunities and challenges of adult online learning coexist.This study hopes to start from the study of learner characteristics,a comprehensive understanding of online adult learners and their learning process,which found the existing problems and put forward the relevant improvement strategies and recommendations.This paper focuses on the adult learners involved in online learning.During the theoretical research period,this paper analyzes classical theory and model of psychology and behavioral science on "adult learning","learner characteristics" and"behavior" through the literature research,and sorts out the relevant research at home and abroad.With the guidance of Bandura's theory of triadic reciprocal determinism model,this paper puts forward the analysis model of the characteristics of online adult learners based on three dimensions:learner background,individual psychology,online behavior,and constructs the feature analysis system.Its main features are as follows:1)multidimensional features,which refer to three characteristic dimensions:learners' background,individual psychology,online behavior,each dimension contains multiple feature elements,the purpose is to have a comprehensive understanding of learning process;2)based on the process and method of learning analytics,the process of feature analysis is divided into three stages:data collection,feature analysis and result report;3)based on the combination of multidimensional features,online adult learners are divided into different groups,then the data analysis of the characteristics of these three groups is presented and the results are presented in visualization.In the case study,the distance learners who participated in an online course of Shanghai Open University online learning platform were selected for the research,and data of three-dimensional characteristics of learners are collected.A variety of data analysis methods are applicated to understand the basic learning situation of distance learners,to explore the relationship between the various characteristics of learners and their impact on academic performance.Then,based on the combination of multidimensional features,the K-means clustering algorithm is used to classify the distance learners into three groups:"active learners","ordinary learners","marginal learners"."Active learners" highlight their learning motivation of cognitive interests and career development,and they are good at communicating with others online."Ordinary learners" perform in a general level,and they just show some typical problems of online learning in two aspects:poor learning enthusiasm,online interaction is not deep enough and active."Marginal learners" are highlighted by lower learning motivation,which is largely due to the outside world.Finally,according to the results of data analysis and interviews,we found several real disadvantages of distance learners,such as lacking interests in learning,do not making full use of online learning resources,online communication is not active and in-depth and so on.Therefore,relevant improvement strategies and suggestions are put forward for different stakeholders.