Design And Implementation Of College Students' Professional Aptitude Assessment System Based On Blockchain Technology

With the improvement of the educational system,the evaluation of the students' professional ability gradually becomes one of the approaches to improve the teaching quality in universities.In addition,focusing on the student's learning process,and evaluating students' professional skills are important factors that assist students to identify their positions and to facilitate their developments in a desirable way.The assessment of students' professional aptitudes is based on the students' learning process,conducted by mining the relationship between learning content and learning efficiency,forming a dynamic development feature that can characterize students' professional aptitudes.In this background,assessing the aptitude of students' professional is the core of this subject,introducing the learning credit management mode of the fusion blockchain technology,and based on Java Web development technology to build a system platform which used to evaluate college students' professional ability.The first,at the beginning of building the system platform,data mining algorithms were used to analyze the existing data and establish a assessment system of students ' professional ability.Under this system,in order to distinguish the influence of different teaching activities on various professional abilities,Apriori algorithm analyzes the relationship between teaching activities and professional competence,and forms the weight matrix of teaching activities.Students as the main node and teaching activities is students' child node,in this condition,the eigenvalue of the child nodes is that the weight and scores of the teaching activities selected by students,and the similarity between the students is calculated by the Simrank algorithm,in this paper,there are two programs of student similarity calculation,the first one is based on the student's first classroom performance,the second is based on the first classroom score and the second classroom score,by comparing the experimental results,the second scheme is more scientific and reasonable.Finally,the students are clustered by the K-means algorithm.According to the clustering result,the student representatives are selected to analyze the strength index of the student's professional ability,the student is used as the evaluation criteria,and the professional aptitude of all students is judged by the group,in which the similarity between the students is replaced.Euclidean distance in the K-means algorithm.In order to verify the expediency and effectiveness of the system,some students' information was collected by questionnaire survey,and the feedback results were compared with the experimental results.It was confirmed that the student professional aptitude evaluation system based on data mining algorithm is expediency and effectiveness.Secondly,according to the system requirements analysis,from the logical structure level,the system is divided into system support layer,data acquisition layer and data analysis layer.From the function module,the system covers the rights maintenance function,data import and export function,training program management function,teaching activity management function and professional aptitude evaluation function.In the learning bill function module,the blockchain technology is integrated into the learning credits,the integrated learning bills,the learning bills are uploaded to the blockchain,and a decentralization is constructed.Learning credit chain that cannot be tampered with.This functional module not only provides students with a concise study credit report,but also effectively simplifies the process of certifying student learning information during the progression or job search process.Finally,the system tests are carried out in terms of function,performance and security,by analyzing the test results,the system is optimized,so that the system can achieve a good state in terms of function,performance and safety,and the system is fully prepared for use.