Knowledge tracking method based on learning migration

Abstract

The invention provides a knowledge tracking method based on learning migration, and relates to the technical field of education data mining. According to the method, a learning curve and an Ebbinghaus forgetting curve are used as priori to track the change of knowledge proficiency and abstract principle mastering degree of students along with time, the knowledge structure of the students is divided into two parts, one part is a deep knowledge structure obtained by understanding the abstract principle by the students, and the other part is an abstraction principle. The other part is a shallow knowledge structure representing shallow association between knowledge concepts, the model performance can be effectively improved, a Q matrix marked by an educational expert is used for describing the inclusion relation between the knowledge concepts and questions, the Q matrix serves as prior to generate a question embedding result, a probability matrix decomposition framework is designed, and the framework is divided into the following three parts: a first part, a second part and a third part; student knowledge proficiency and abstract principle mastering degree tracking, student practice feedback modeling and model parameter learning, and student knowledge mastering degree tracking through a learning migration-based multi-level knowledge tracking model.

Description

Technical field [0001] The present invention relates to the field of educational data mining techniques, and more particularly to a knowledge tracking method based on learning migration. Background technique [0002] In recent years, with the MASSIVE OPEN ONLINE COURS, MOOCS, Khanacademy, Online Juding Systems, OJS, a large number of online intelligent education-based applications quickly in the public It takes important positions, such as the recommendation, student performance forecasts and learning paths. [0003] A key issue in this type of application is knowledge tracking, that is, tracking students' knowledge in a period of time. However, existing knowledge tracking methods have not considered learning migration on knowledge tracking. In addition, they can only track students 'knowledge proficiency, and cannot track the level of students' abstract principles (common attributes between knowledge concepts, such as learning methods, learning style and learning habits) and kno...

AI Technical Summary

Problems solved by technology

[0005] However, when applying learning transfer theory to knowledge tracking, there are several technical problems: how to apply the cognitive structure transfer theory in the field of educational psychology across disciplines to the field of knowledge tracking, how to grasp the students' abstract principles, Knowledge proficiency and knowledge structure (the difference and connection between the knowledge concepts understood by students) are modeled, how to establish a knowledge tracking framework that can simultaneously track students' mastery of abstract principles, knowledge proficiency and knowledge structure

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