<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, with the continuous development of the tourism industry, changing the education model has become a fundamental problem that must be solved to cultivate the quality of professional talents, and the OBE education model has become the trend of higher education development. In this paper, the program design of tourism management mode based on OBE education is carried out in two aspects of personality characteristics cognition and personality learning resources, then constructs the learner characteristics model from several aspects of style similarity, behavioral similarity, learner influence relationship, and proposes the personality recommendation method based on deep learning after the selected experimental objects are experimental class and control class respectively, and through the analysis of the cognitive level of the students, learning style, interaction behavior characteristics were analyzed to verify the validity of the learning characteristic model and program design constructed in this paper. After the experiment, the average post-test score of the experimental group was 84.91, which is higher than the average post-test score of the C1 group, which is 83.63, indicating that the OBE education model based on the deep learning recommendation can improve the student’s learning performance.</p>
</abstract>

In recent years, with the continuous development of the tourism industry, changing the education model has become a fundamental problem that must be solved to cultivate the quality of professional talents, and the OBE education model has become the trend of higher education development. In this paper, the program design of tourism management mode based on OBE education is carried out in two aspects of personality characteristics cognition and personality learning resources, then constructs the learner characteristics model from several aspects of style similarity, behavioral similarity, learner influence relationship, and proposes the personality recommendation method based on deep learning after the selected experimental objects are experimental class and control class respectively, and through the analysis of the cognitive level of the students, learning style, interaction behavior characteristics were analyzed to verify the validity of the learning characteristic model and program design constructed in this paper. After the experiment, the average post-test score of the experimental group was 84.91, which is higher than the average post-test score of the C1 group, which is 83.63, indicating that the OBE education model based on the deep learning recommendation can improve the student’s learning performance.

Personalized Learning Scheme of Tourism Management Professional Curriculum System in Colleges and Universities under Intelligent Recommendation System Based on OBE Education Model

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In recent years, with the continuous development of the tourism industry, changing the education model has become a fundamental problem that must be solved to...

Personalized Learning Scheme of Tourism Management Professional Curriculum System in Colleges and Universities under Intelligent Recommendation System Based on OBE Education Model

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 06 kwi 2024

Przyjęty: 25 cze 2024

DOI: https://doi.org/10.2478/amns-2024-2243

Słowa kluczowe
OBE education, Tourism management, Feature models, Deep learning, Personalized recommendations

© 2024 Chunlan Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Personalized Learning Scheme of Tourism Management Professional Curriculum System in Colleges and Universities under Intelligent Recommendation System Based on OBE Education Model

Data publikacji: 05 sie 2024

Zakres stron: -

Otrzymano: 06 kwi 2024

Przyjęty: 25 cze 2024

DOI: https://doi.org/10.2478/amns-2024-2243

Słowa kluczoweOBE education, Tourism management, Feature models, Deep learning, Personalized recommendations

© 2024 Chunlan Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
OBE education, Tourism management, Feature models, Deep learning, Personalized recommendations