摘要
在人工智能（AI）时代，研究生群体的心理社会性发展面临着新的机遇与挑战，该问题的关键在于如何识别和培育其内生增长点？本文基于模糊综合评价结果与GA-BP模型预测值的差异分析，识别出研究生心理社会性发展的潜在内生增长点，在一定程度上提升了分析结果的结构化和可解释性。数据分析表明，研究生心理社会性发展的内生增长点源于新型的“劳动对象、劳动关系和劳动者”3个维度的赋能。
关键词： 人工智能；心理社会性发展；内生增长点；GA-BP神经网络
Abstract
In the era of artificial intelligence (AI), the psychological and social development of the graduate student group faces new opportunities and challenges. The key issue lies in how to identify and cultivate its inherent growth points? Based on the analysis of the differences between the fuzzy comprehensive evaluation results and the predicted values of the GA-BP model, this paper identifies the potential inherent growth points of the psychological and social development of graduate students, which to a certain extent improves the structuring and interpretability of the analysis results. The data analysis shows that the inherent growth points of the psychological and social development of graduate students originate from the empowerment of the three new dimensions of "labor object, labor relationship and laborer".
Key words： Artificial Intelligence; Psychological and social development; Endogenous growth point; GA-BP neural network
参考文献 References
[1] 秦书生,闫萍.人工智能赋能特殊教育的逻辑理路与困境纾解[J/OL].当代教育论坛,1-16[2025-07-15].
[2] 马千贺.基于创新创业视角的高职院校学生心理社会性发展研究[J].产业与科技论坛.2025,24(15):121-123.
[3] 石林,徐梓凯.生成式人工智能在大学生心理健康教育中的应用研究[J/OL].武汉理工大学学报(社会科学版),1-7[2025-07-15].
http://kns.cnki.net/kcms/detail/42.1660.C.20250714.0945.022.html.
[4] 张迪.基于社会性发展视域的大学生心理健康教育探究[J].新课程教学(电子版).2024,(5):187-189.
[5] Tao W .Research on Fuzzy Comprehensive Evaluation Index System of Men-tal Health Education for College Students.[J].Journal of healthcare engineering,2022, 2022:7106926-7106926.
[6] 温婷.研究生社会性发展的影响因素及改善路径[J].吉林省教育学院学报.2016,32(8):147-150.
[7] Xu X, Liu F. Optimization of Online Education and Teaching Evaluation System Based on GA-BP Neural Network. Comput Intell Neurosci. 2021:8785127.
[8] Yang P, Hui Y, Xiaoyan W. The College Students' Mental Health Analysis and Application Based on Fuzzy Comprehensive Evaluation[C]// Proceedings of 2015 International Conference on Education Technology, Management and Humanities Science (ETMHS 2015). Qingdao: Atlantis Press, 2015: 1197–1200.
[9] Jiangning X .Research on Diagnosis and Management of Postgraduates Mental Health Status Based on BP Neural Network [J].Frontiers in Public Health, 2022, 10: 897565 -897565.
[10] 朱海华,陈柳钦.人工智能赋能新质生产力：现实支撑、理论框架与实践进路[J/OL].贵州省党校学报,1-15 [2025-07-16].
[11] 吴志先,蔡姿尧,詹菁,等.人工智能时代新质生产力需求与五年制高职人才培养策略探究[J].武汉船舶职业技术学院学报,2025,24(03):14-19.
[12] 石红梅，尚瑾. 新质生产力赋能高等教育创新发展的内在机理、价值意蕴与实践路径［J］. 西南石油大学学报（社会科学版）,2025,27（04）:48‒57.
[13] 李锐,吴荩萱,梁瑜倩,等.新质生产力视域下高等教育的价值意蕴与历史使命[J].教育评论,2025,(06):3-18.
[14] 贺祖斌,周润伍.发展新质生产力背景下研究生教育分类发展的逻辑、价值与路径[J].学位与研究生教育,2025, (03):44-51.
[15] He L ,Cao L ,Wang T , et al.A Bayesian Additive Regression Trees Framework for Individualized Causal Effect Estimation[J].Mathematics,2025,13(13):2195-2195.
[16] Xun G ,Zhouzhou R. Mental Health Path of College Students with SCL-90 under the Background of Cognitive Impairment[J].Psychiatria Danubina,2021,33(S8):342-343.
[17] Lijun C. Application of Fuzzy Comprehensive Evaluation Based on GeneticAlgorithm in Psychological Measure-ment[J]. Scientific Programming, 2021, 2021 :1-11.
[18] 吴宝峰,张鹏远. 基于GA算法优化BP神经网络的边坡稳定性预测模型研究[J].水利科学与寒区工程,2024, 7(12):1-3.