Research On Personalized Learning Resources Recommendation Based On Students' Assessment Data Analysis

The main contradiction of Chinese education in the new era is the contradiction between the increasing individualized,high-quality,flexible,lifelong educational needs of students and the supply of schools-based,standardized,class-based,single-channel services.Personalized learning resource recommendation is an effective way to solve educational contradictions,meet learners' individualized learning needs,and improve their learning effects and interest.However,in the traditional teaching situation,the existing related research and the educational big data analysis system on the market are still difficult to meet the learner's personalized learning resource needs.Therefore,this study aims to analyze the student's assessment data from the perspective of cognitive learning theory,accurately locate the learner's learning needs,construct a personalized learning resource push model,and ultimately support learners to carry out personalized learning.The core research question is: How to accurately locate the learning needs of learners based on the analysis of student assessment data,and push personalized learning resources for learners? The problem is decomposed into three sub-problems:(1)According to the knowledge space theory,how to construct the subject knowledge structure,compile the subject test and organize the learning resource library?(2)Based on the cognitive learning theory,how to analyze the student evaluation data,construct the learner model and locate its learning needs?(3)In the traditional learning situation,how to choose the push algorithm,build a personalized learning resource push model and push personalized learning resources for learners? In view of the above research problems,the research adopts the positivist research paradigm,and the design-based research is the core research method.At the same time,the literature research method and the investigation research method are used for research.The research including five stages: first,the definition and classification of student evaluation data and personalized learning resource push system,and the status quo of research and application at home and abroad are systematically sorted out to fully grasp the research status and latest developments;second,based on knowledge Spatial theory,constructing knowledge models,organizing learning resource pools,compiling discipline tests,and obtaining effective student assessment data;third,based on cognitive learning theory,combined with CELTS-11 learner model norms and Bloom's educational goal classification theory,analysis Students evaluate the data,construct the learner model,and accurately locate the learner's learning needs.Fourth,select the hybrid push algorithm,construct a personalized learning resource push model based on the evaluation data,and determine the push content(corrected problem analysis,knowledge reproduction,consolidation practice and Pre-class study);Fifth,model application effect analysis and feedback evaluation,taking Zhejiang Province high school information technology course "algorithm and program design" as an example,applying the push model to analyze the students' post-use learning effect and feedback from teachers and students..The research conclusions mainly include:(1)experiments show that The model canimprove the learner's understanding level,and the improvement effect of the knowledge points is more significant than the moderate difficulty;(2)the model can improve the learner's academic performance,learning efficiency,learning interest and learning confidence;(3)learner pair The model is highly satisfied,and is willing to actively use the personalized learning resources recommended by the model and recommend it to other learners.(4)The optimization of the model should focus on the design of learning paths and learning resources,which can enhance the learner's perception.Usefulness and willingness to use.This study proposes a personalized learning resource push strategy based on evaluation data analysis,which further enriches the personalized learning theory.The personalized learning resource push model has strong practical application value and individualized education in the digital environment.Provide a new perspective.