School of Tourism Culture, Tourism College of Changchun University, Changchun, 130607, China.
Faculty of Education, Northeast Normal University, Changchun, 130024, China.
PLoS One. 2024 Feb 29;19(2):e0296683. doi: 10.1371/journal.pone.0296683. eCollection 2024.
The motivation of this paper is to solve the problem of tourism majors' lack of theoretical knowledge and professional ability by building a capacity training mechanism model based on grounded theory. The goal of the study is to optimize the ability training strategies of tourism undergraduates and improve their professional quality and competitiveness. The paper adopts the ability training model based on grounded theory, and combines with Back Propagation (BP) neural network for optimization and evaluation. By comparing the performance of different ability training mechanisms, this paper explores the best training strategies to provide support and guidance for the training of tourism undergraduates. Firstly, the employment background of the current market is studied and analyzed. By sorting out the relevant documents of grounded theory and combining with the current training strategies of tourism majors, the students' personality characteristics and the basic principles of establishing models are integrated. The Back Propagation (BP) neural network is combined with the grounded theory. The data input of the student ability model is re-optimized. The undergraduate competency training mechanism model is constructed. The results show that when the number of iterations of the network model is 500.00, the evaluation accuracy of the competency training model based on BP neural network can reach 70.00%. At this time, the evaluation accuracy of competency training model based on content analysis method is only 55.00%. In addition, the results show that with the increase of model iterations, the recognition accuracy of the ability model based on grounded theory and the ability training mechanism of content analysis method is continuously improved. However, the ability evaluation model based on grounded theory has higher accuracy, and the accuracy of ability evaluation even exceeds 78.52% when the number of iterations of the network model is 600. Secondly, through the statistics and comparison of the grading results of students of different majors, it is found that the ability training mechanism based on grounded theory can improve the overall ability level of students more significantly. The research has important reference value for promoting the optimization and perfection of students' training strategies.
本文的研究动机是通过构建基于扎根理论的能力培养机制模型来解决旅游专业学生理论知识和专业能力不足的问题。本研究的目的是优化旅游本科生的能力培养策略，提高其专业素质和竞争力。本文采用基于扎根理论的能力培养模型，并结合反向传播（BP）神经网络进行优化和评价。通过比较不同能力培养机制的性能，探讨最佳的培训策略，为旅游本科生的培训提供支持和指导。首先，研究和分析当前市场的就业背景。通过梳理扎根理论的相关文献，并结合旅游专业当前的培养策略，整合学生的个性特点和建模基本原则。将反向传播（BP）神经网络与扎根理论相结合。对学生能力模型的输入数据进行重新优化。构建本科学生能力培养机制模型。结果表明，当网络模型的迭代次数为 500.00 时，基于 BP 神经网络的能力培养模型的评价准确率可达 70.00%。此时，基于内容分析法的能力培养模型的评价准确率仅为 55.00%。此外，结果表明，随着模型迭代次数的增加，基于扎根理论的能力模型和基于内容分析方法的能力培养机制的识别准确率不断提高。然而，基于扎根理论的能力评价模型具有更高的准确性，甚至当网络模型的迭代次数达到 600 时，其能力评价的准确率也超过 78.52%。其次，通过对不同专业学生成绩的统计和比较，发现基于扎根理论的能力培养机制可以更显著地提高学生的整体能力水平。该研究对促进学生培养策略的优化和完善具有重要的参考价值。
