An Intelligent Tutoring System for Math Word Problem Solving with Tutorial Solution Generation

Wu, Shishun; Xu, Xuebi; Li, Rui; Liang, Guanghua; He, Bin

doi:10.1109/ieir56323.2022.10050083

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…However, current teaching systems usually lack the flexibility or adaptability to cope with the personal needs of different students [6][7][8], so it is a beneficial exploration to introduce the hybrid framework of reinforced learning and deep learning into smart teaching systems [9][10][11]. Smart teaching that is more dynamic, personalized, and efficient could be achieved with the help of advanced artificial intelligence (AI) technology, which is conducive to promoting reform and innovation in the field of vocational education [12][13][14][15]. This research is not only closely linked to current technological trends and educational needs, but it also has far-reaching strategic significance for the future development of the education system.…”

Section: Introductionmentioning

confidence: 99%

Smart Teaching Systems: A Hybrid Framework of Reinforced Learning and Deep Learning

Sun,

Huang,

Wang

et al. 2023

Int. J. Emerg. Technol. Learn.

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As vocational education is transforming constantly, there is an urgent demand in the field of education for smart teaching systems to be able to respond to students’ personal learning needs in a more dynamic way, but a review of currently available algorithms reveals that the common application of existing methods lacks a deep enough understanding of students’ individual differences. Out of these concerns, this study aims to propose a novel and hybrid framework for the design of smart teaching systems based on reinforced learning and deep learning, so as to overcome the shortcomings of existing research and more accurately predict students’ personal needs. Besides, an end-to-end model with a retrieval attention mechanism has been designed for generating responses with precise information about students’ learning needs. This study provides a smart teaching scheme for vocational education that is new, efficient, and humane, while also providing a solid theoretical foundation for the reform and innovation of the education system in the future.

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