Shi Panfeng, Liu Weijun
School of Marxism, Chengdu Normal University, Chengdu, 611130, China.
School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China.
Sci Rep. 2025 May 5;15(1):15661. doi: 10.1038/s41598-025-00536-y.
This work intends to meet China's need for high-quality talents and optimize the current college classroom teaching modes. It first investigates the current situation of college history classroom teaching from the perspective of positive psychology and adaptive deep learning. Then, the work formulates a new teaching strategy. This teaching strategy is divided into five parts: verbal information, smart skills, cognitive strategies, action skills, and learning attitudes. Then, the proposed new teaching strategy is applied to practice. Sixty students from a university in Anyang are recruited and divided into Class A (experimental class) and Class B (control class). The average score of Class A using the proposed teaching strategy has increased by 18%, from 68 to 86 points. The average score of Class B without using the proposed teaching strategy has decreased by 1%, from 68 to 67 points. This indicates that the college history classroom-oriented teaching strategy based on adaptive deep learning is both scientifically sound and effective.
这项工作旨在满足中国对高素质人才的需求，并优化当前的大学课堂教学模式。它首先从积极心理学和适应性深度学习的角度调查大学历史课堂教学的现状。然后，这项工作制定了一种新的教学策略。这种教学策略分为五个部分：言语信息、智慧技能、认知策略、行动技能和学习态度。接着，将提出的新教学策略应用于实践。招募了安阳一所大学的60名学生，并将他们分为A班（实验班）和B班（对照班）。使用所提出教学策略的A班平均成绩提高了18%，从68分提高到86分。未使用所提出教学策略的B班平均成绩下降了1%，从68分降至67分。这表明基于适应性深度学习的大学历史课堂导向教学策略既科学合理又有效。
