This paper conducts a comprehensive thematic review of research on ideological and political education in China from 2021 to July 2023, using ATLAS. ti 9 for analysis. The review aims to identify primary trends and challenges in this field, with a focus on the impact of the Big Data Era, technical applications, innovative countermeasures, resource integration, and evaluation and quality improvement. Key findings include: 1. **Quantitative Findings**: The number of articles on ideological and political education increased significantly in 2021, coinciding with the 100th anniversary of the founding of the Communist Party of China (CPC). The most frequent terms in the literature are "students," "education," "teaching," "collage," "network," "datum," and "system." 2. **Qualitative Findings**: Five main themes emerged: - **Big Data Era Related Problems**: Studies explore students' ideological dynamics, communication channels, and the integration of big data in education. - **Technical Application Problems**: Research focuses on using technology to enhance teaching effectiveness, student engagement, and learning experiences. - **Innovative Countermeasures Related Problems**: Scholars propose novel strategies leveraging big data analysis, technology integration, and curriculum reform. - **Resource Integration Related Problems**: Studies emphasize the importance of comprehensive integration, extracurricular practice, and ecological perspectives. - **Evaluation and Quality Improvement Related Problems**: Deep learning and AI technologies are used to enhance teaching quality and evaluation methods. 3. **Conclusion**: The review highlights the need for increased scholarly attention to address the challenges in ideological and political education. It also identifies key considerations such as ethical and privacy issues, limited generalizability of models, and the complexity of evaluating teaching quality. The paper contributes to the field by providing a comprehensive literature review and novel directions for future research, emphasizing the importance of integrating online and offline elements and exploring technological adoption. However, it acknowledges limitations, such as the restricted data collection to peer-reviewed journal articles in English.This paper conducts a comprehensive thematic review of research on ideological and political education in China from 2021 to July 2023, using ATLAS. ti 9 for analysis. The review aims to identify primary trends and challenges in this field, with a focus on the impact of the Big Data Era, technical applications, innovative countermeasures, resource integration, and evaluation and quality improvement. Key findings include: 1. **Quantitative Findings**: The number of articles on ideological and political education increased significantly in 2021, coinciding with the 100th anniversary of the founding of the Communist Party of China (CPC). The most frequent terms in the literature are "students," "education," "teaching," "collage," "network," "datum," and "system." 2. **Qualitative Findings**: Five main themes emerged: - **Big Data Era Related Problems**: Studies explore students' ideological dynamics, communication channels, and the integration of big data in education. - **Technical Application Problems**: Research focuses on using technology to enhance teaching effectiveness, student engagement, and learning experiences. - **Innovative Countermeasures Related Problems**: Scholars propose novel strategies leveraging big data analysis, technology integration, and curriculum reform. - **Resource Integration Related Problems**: Studies emphasize the importance of comprehensive integration, extracurricular practice, and ecological perspectives. - **Evaluation and Quality Improvement Related Problems**: Deep learning and AI technologies are used to enhance teaching quality and evaluation methods. 3. **Conclusion**: The review highlights the need for increased scholarly attention to address the challenges in ideological and political education. It also identifies key considerations such as ethical and privacy issues, limited generalizability of models, and the complexity of evaluating teaching quality. The paper contributes to the field by providing a comprehensive literature review and novel directions for future research, emphasizing the importance of integrating online and offline elements and exploring technological adoption. However, it acknowledges limitations, such as the restricted data collection to peer-reviewed journal articles in English.