Using an Intelligent Tutoring System as a Textbook Supplement for Personalized Learning

Digital teaching materials help to promote the vocationalization and intelligence of vocational education, however, the current digital teaching materials have some dilemmas at the resource allocation level. This paper begins with the data exchange link in the digital textbook management system and builds an ERDDS resource allocation system with multiple configuration centers and the introduction of scheduling servers. The resource scheduling optimization problem of the configuration system is mathematically modeled, and the multi-objective optimization mathematical model is solved by using the ant colony algorithm to achieve the purpose of improving allocation efficiency. The experiments on the download task show that the ACO algorithm is less time-consuming and stable, with good convergence. The solution accuracy of the algorithm is improved by 13.38%, 25.68% and 18.97% compared to PSO, ACO and MACO, respectively. The average efficiency of using digital textbooks in each college before and after the experiment has been improved by 19.77%, and the average efficiency of allocating digital textbooks has been improved by 11.83%. It shows that the proposed efficiency improvement path for digital textbook resource allocation is feasible and reasonable.

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Using an Intelligent Tutoring System as a Textbook Supplement for Personalized Learning

Cited by 2 publications

References 13 publications

Construction of guidance graph in blended learning based on knowledge point extraction

Construction of guidance graph in blended learning based on knowledge point extraction

Exploration of the Path to Improve the Efficiency of Digital Textbook Resource Allocation in Vocational Education Supported by Mathematical Modeling Technology

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