Personalized Chinese Stroke Order Intelligent Teaching Research And System Development

Chinese characters are the carriers of the inheritance and dissemination of Chinese culture.Learning Chinese characters well requires not only mastering the pronunciation of Chinese characters,but also mastering standard writing skills.With the rapid development of information technology,computer-aided instruction has become a hot trend,but it has led to the decline of people's writing ability of Chinese characters and the phenomenon of non-standard writing stroke is widespread.In order to effectively teach the standard writing skill of Chinese character and correct the errors of stroke order writing,this paper designs a personalized Chinese character stroke order correction algorithm based on association rules and collaborative filtering,and develops an intelligent teaching system with the personalized Chinese character stroke order correction algorithm.Based on the massive users' handwriting and intelligent judgment records,this paper uses Apriori algorithm to mine the common Chinese characters with typical stroke order and easy to mistake,as well as the correlation between easy to mistake Chinese characters.In order to avoid the interference of pseudo strong association rules,the promotion degree is introduced to measure and reduce the number of unimportant rules.Taking the mined strong association rules as the basis and the general specification of Chinese character stroke order as the theoretical basis,through the study of the laws of typical wrong Chinese characters and Chinese character stroke order writing errors,such as the error prone situation and the causes of errors,and the same kind classification,a set of typical Chinese character error prone character set library is finally formed,so that users can correct the stroke order errors of this Chinese character and practice the same kind of stroke order error prone characters at the same time,Strengthen the correction effect.Using the constructed Chinese character error prone character set library,by collecting user basic information,user writing records,collection and search behavior data,and using the Project-based Collaborative Filtering Recommendation Algorithm to mine the Chinese characters that users may write wrong for Chinese character recommendation,so as to further study the personalized stroke order correction algorithm.Meanwhile,in order to avoid the influence of highly active users on the recommendation results,the performance of user activity optimization collaborative filtering algorithm is introduced,and a complete personalized Chinese character stroke order correction algorithm is constructed under the guidance of reinforcement theory.Finally,based on the development framework of wechat applet,the Chinese character error prone character set library and stroke order correction algorithm are applied to the system to realize a personalized Chinese character stroke order intelligent teaching system.Users can not only learn standard writing,but also correct the habit of non-standard writing.The experimental results show that the association rule algorithm can mine effective strong association rules,and provide important reference for the error-prone Chinese character dataset.The improved collaborative filtering algorithm can provide personalized error-prone Chinese character recommendation service,and the recommendation performance is higher than the traditional collaborative filtering model.In the writing proficiency test based on personalized Chinese stroke order correction system,users show obvious differences between the original state and the trained state,which effectively corrected non-standard writing habits.