School of Marxism, Dalian Maritime University, Liaoning, Dalian, 116000, China.
School of Marxism, Dalian University of Technology, Liaoning, Dalian, 116014, China.
BMC Psychol. 2024 Mar 25;12(1):170. doi: 10.1186/s40359-024-01654-4.
As the primary domain of ideological and political education in higher education institutions, ideological and political courses must align with principles rooted in human psychology and education. Integrating educational psychology into ideological and political teaching in universities enhances the scientific, targeted, and forward-thinking nature of such education. The burgeoning exploration of knowledge graph applications has extended to machine translation, semantic search, and intelligent question answering. Diverging from traditional text matching, the knowledge spectrum graph transforms information acquisition in search engines. This paper pioneers a predictive system for delineating the relationship between educational psychology and ideological and political education in universities. Initially, it extracts diverse psychological mapping relationships of students, constructing a knowledge graph. By employing the KNN algorithm, the system analyzes psychological characteristics to effectively forecast the relationship between educational psychology and ideological and political education in universities. The system's functionality is meticulously detailed in this paper, and its performance is rigorously tested. The results demonstrate high accuracy, recall rates, and F1 values. The F1 score can reach 0.95enabling precise sample classification. The apex of the average curve for system response time peaks at approximately 2.5 s, maintaining an average response time of less than 3 s. This aligns seamlessly with the demands of practical online teaching requirements. The system adeptly forecasts the relationship between educational psychology and ideological and political education in universities, meeting response time requirements and thereby fostering the scientific and predictive nature of ideological and political teaching in higher education institutions.
作为高校思想政治教育的主要阵地，思想政治课必须遵循根植于人类心理和教育的原则。将教育心理学融入高校思想政治教学中，增强了这种教育的科学性、针对性和前瞻性。知识图谱应用的蓬勃探索已经扩展到机器翻译、语义搜索和智能问答。与传统的文本匹配不同，知识光谱图改变了搜索引擎中的信息获取方式。本文开创性地提出了一种用于预测高校教育心理学与思想政治教育关系的预测系统。首先，它提取了学生的各种心理映射关系，构建了一个知识图谱。通过使用 KNN 算法，系统分析了心理特征，有效地预测了高校教育心理学与思想政治教育之间的关系。本文详细介绍了该系统的功能，并对其性能进行了严格的测试。结果表明，该系统具有较高的准确性、召回率和 F1 值。F1 分数可以达到 0.95，能够实现精确的样本分类。系统响应时间的平均曲线峰值约为 2.5s，平均响应时间小于 3s，满足实际在线教学要求。该系统能够准确预测高校教育心理学与思想政治教育之间的关系，满足响应时间要求，从而促进高校思想政治教学的科学性和预测性。
