Learner-centered adaptive learning system

Abstract

The invention relates to the technical field of self-adaptive learning, and discloses a learner-centered self-adaptive learning system, which comprises an infrastructure support layer, a data resourcelayer, a core service layer and a visual presentation layer, wherein the infrastructure support layer is used for providing a development and operation environment, computing and storage resources and a data acquisition interface for the system; the data resource layer is used for providing data support and data archiving management service for the adaptive learning core business; the core business layer is used for realizing core business of adaptive learning; and the visual presentation layer is used for providing an input interface and output presentation for the system, providing visual interface service for self-adaptive teaching data retrieval and operation for a user and providing an operation and maintenance management service interface for system management. Students can be helped to construct a knowledge structure of the system, and learning efficiency is improved; teaching data service and teaching participation means are provided for teachers; and automatic generation anddigital asset conversion services of the domain knowledge model are provided for learning content service providers.

Description

technical field [0001] The invention relates to the field of self-adaptive learning technology, more specifically, it relates to a learner-centered self-adaptive learning system. Background technique [0002] Adaptive learning aims to provide different learners with adaptive learning content and learning paths, so as to achieve the purpose of personalized learning. Peter Brusilovsky, an information scientist at the University of Pittsburgh in the United States, first proposed the concept of adaptive learning in 1996, and proposed a general model of an adaptive learning system, which mainly includes domain knowledge model, learner model, teaching model, adaptive engine and interface model . [0003] Through the investigation and analysis of domestic and foreign research status and self-adaptive products, the following points are summarized as follows: (1) The construction of domain knowledge models is mostly based on the school’s curriculum outline and experts’ knowledge. T...

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Problems solved by technology

[0003] Through the investigation and analysis of domestic and foreign research status and self-adaptive products, the following points are summarized as follows: (1) The construction of domain knowledge models is mostly based on the school’s curriculum outline and experts’ knowledge. Teaching experience is a static model, ignoring the correlation between knowledge, dynamic development characteristics and the reverse influence of students on the domain model; (2) In the process of building the learner model, most of the acquisition of learning style and cognitive level Professional scales and test scores are used for representation, without considering the dynamic personality characteristics of learners reflected in the dynamic interaction with the system during the learning process; (3) The matching and recommendation rules for learning paths in the teaching model are mostly based on teachers’ teaching experience , the design of these rule steps takes a lot of time and investment, and only considers the influence of students’ unilateral factors on the rules, ignoring the influence of knowledge’s own characteristics on system recommendation performance; (4) The adaptive engine cannot achieve real “adaptive” , for example, cannot support the construction of modifiable and open domain knowledge models; cannot support the sharing of user models in multidisciplinary systems; cannot support the subject adaptability of teaching models; (5) the current domestic research on adaptive learning systems Most of them remain at the theoretical level, and the research and development of mature and commercially available adaptive learning systems are still in their infancy

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