Application of Generative AI in High-Quality Education Development: Exploration and Practice for Quality and Efficiency Improvement
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Currently, educational digitization has become a crucial component of the Digital China strategy. China is deeply implementing digital education initiatives to drive educational reform and innovation, accelerating the construction of a learning society and nation where everyone can learn anytime, anywhere. As a key aspect of education, ideological and political education in higher education, adhering to the principles of value guidance and holistic human development, must embrace digital transformation and explore effective pathways to achieve high-quality development through AI.
The Prominent Potential of Generative AI in Empowering High-Quality Ideological and Political Education
In recent years, generative AI, represented by ChatGPT, has emerged as a significant branch of AI development, profoundly impacting education, technology, and even human thought and behavior. Ideological and political education is an educational activity that involves the laws of human thought and behavior, aiming to guide correct thought and action. In the era of global connectivity, China's ideological and political education faces challenges from diverse social trends and values, as well as limitations in narrative methods and technological means, necessitating urgent transformation and innovation. Generative AI products like ChatGPT, leveraging massive data, advanced algorithms, and powerful computing, utilize cross-modal deep learning models, diffusion models, and reinforcement learning based on human feedback to generate human-like dialogue, reshaping social interactions and human thought. This presents new opportunities for the innovative development of ideological and political education in the new era.
1. Generative AI Reduces Burden and Enhances Efficiency, Increasing the Dynamism of Ideological and Political Education.
With robust algorithmic support and open connectivity, generative AI like ChatGPT can link and create diverse educational resources, providing students with an open, free, and inclusive AI learning environment. It enriches resources for "comprehensive ideological education" classrooms and offers real-time feedback through human-machine interaction, deepening student engagement and expanding their cognitive scope and learning interests. This shifts the traditional one-way discourse of "spoon-feeding" and didactic teaching, fostering empathy between students and educational content. Additionally, generative AI efficiently integrates lesson plans, literature recommendations, multimedia content, and coding, offering rich references for teaching design. This allows educators to focus more on theoretical and practical exploration, improving teaching and research efficiency.
2. Generative AI Strengthens Life-Oriented Communication, Enhancing the Appeal of Ideological and Political Education Discourse.
The practice of ideological and political education discourse aims to guide and shape values through reasoning. Generative AI, like ChatGPT, engages in multi-turn dialogues via large language models, facilitating interactive discussions with audiences. It provides personalized responses aligned with human grammar and semantics through algorithmic information推送 and dynamic感知, meeting audience expectations. Moreover, generative AI connects vast online information, blurring boundaries between现实 and虚拟,在场 and离场,满足人类情感陪伴和社交需求. Daily life becomes a key arena for ideological influence. Through bidirectional diffusion models, generative AI links atomized individuals in the "lifeworld," guiding them to resonate with ideological discourse in daily behavior. It places students in mainstream ideological传播 scenarios, meeting their emotional and value expectations in拟态 environments. This聚焦 fragmented opinions into adaptable online spaces, using流行符号 and常识 to传递教育理念, fostering共识 and enhancing扩散度和感召力.
3. Generative AI Promotes Precision in Education, Supporting Scientific Decision-Making in Ideological and Political Education.
With data support, algorithmic推送, human-machine interaction, and deep learning, generative AI transforms ideological and political education from经验性,预判性, and "broad-brush" approaches into计算able, measurable, predictable, and highly personalized practices. It digitizes思想,情感,行为, and场景, enabling educators to identify亮点,痛点, and patterns,预测 trends, and optimize resources and决策. Additionally, generative AI精准感知 student needs, creating precise digital profiles for different groups. It builds mathematical models for learning patterns and behaviors, addressing general and特殊需求, ensuring精准对接 between teaching supply and student demand. This achieves精准施教,精确评估, and科学决策.
Risks and Governance Strategies of Generative AI in Empowering High-Quality Ideological and Political Education
As a disruptive technology, generative AI empowers the transformation of ideological and political education, presenting new paradigms of intelligence, precision, and personalization. However, we must also recognize that the prevalence of technological pragmatism has led to the expansion of instrumental rationality, potentially overriding value rationality. This can result in issues such as information cocoons, technological dependence, and digital hegemony, along with ethical dilemmas like the loss of value judgment, academic integrity, and humanistic care. Technical flaws, such as algorithmic black boxes and accountability gaps in ChatGPT-like products, also pose ideological security risks. Therefore, from a collaborative governance perspective, we should establish a risk management strategy that emphasizes digital justice, holistic intelligence, and efficient coordination to promote the integrity and innovation of ideological and political education in the new era.
First, strengthen value guidance by integrating technological logic with value logic. The subjects of ideological and political education should select and apply intelligent technologies based on the core objectives of ideological and political education. Upholding mainstream ideological discourse as the core, they should understand the discourse production patterns and algorithmic rules of ChatGPT-like products and actively innovate discourse methods and structures in ideological and political education using intelligent technologies. During the application of these technologies, priority should be given to value rationality, ensuring that technological logic is guided by intrinsic values. This ensures that ideological and political education, while empowered by technology, remains human-centered, adhering to its original mission of nurturing souls and fostering comprehensive human development.
Second, enhance technological ethics by regulating the technological behavior of ideological and political subjects through institutional norms. Given the current state of AI applications in Chinese universities and the nature of AI technology, it is essential to promptly establish AI technical standards and ethical guidelines tailored to China's national conditions. Key measures should include clarifying ethical principles, improving governance mechanisms, strengthening ethical reviews and oversight, and promoting ethical education and awareness. Strengthening AI review mechanisms is critical, with relevant laws addressing copyright issues in linking different databases and the use of generative AI. Additionally, a data security governance platform should be established to monitor algorithmic models in real-time, enabling digital risk perception and data sharing. This provides institutional safeguards and ethical guidance for ideological and political subjects to manage data security and utilize generative AI responsibly.
Third, improve digital literacy to foster a harmonious digital media environment. Comprehensive training programs should be implemented to enhance digital literacy, covering generative AI basics, digital access, communication, resources, empowerment, and smart classrooms. Cross-disciplinary knowledge in digital skills and humanities should also be promoted. At the same time, ideological and political subjects should receive education on intelligent application skills, value rationality, and security responsibility awareness. This will improve the adaptability, competence, and creativity of educators and students, fostering a harmonious digital media ecosystem where decisions align with educational benefits, technological efficacy, and ethical considerations.
Fourth, advance technological breakthroughs to build a Chinese-style intelligent technology system. In response to Western technological hegemony and high-tech containment, China must accelerate breakthroughs in critical technologies, developing generative AI systems that align with Chinese cultural contexts. Data aggregation and secure sharing in ideological and political work should be standardized. Algorithmic operations should be regulated using discourse systems and corpora suited to China's national conditions, ensuring algorithms serve ideological and political discourse while mitigating potential ideological risks from ChatGPT-like products. Gradually, a Chinese-style intelligent technology ecosystem should be established, contributing Chinese wisdom and solutions to global AI governance.
With the emergence of generative AI products like ChatGPT, New Bing, and Wenxin Yiyan, these rapidly evolving and fiercely competitive technologies are expanding their functionalities, profoundly influencing human thought and behavior. They are driving the transformation of China's ideological and political education toward personalization, intelligence, and precision. Given the double-edged nature of intelligent technologies, generative AI's role in advancing high-quality ideological and political education encompasses both the significant benefits of its technological advantages and the risks posed by technological pragmatism and flaws.
Therefore, while clarifying the interplay between ideological and political education and generative AI, we must establish the dominant role of socialist core values in intelligent technologies. By integrating technological development with intrinsic value cultivation, we can construct an effective risk governance model encompassing value guidance, role relationships, institutional support, and literacy development. This will drive paradigm shifts and normative construction in ideological and political education under intelligent technologies, promoting high-quality development in university ideological and political work.