“Efficiency” and “Quality” have always been the two core elements of classroom teaching reform. Currently, in China’s basic education curriculum, there are still issues such as heavy burdens on teachers in lesson preparation and delivery, insufficient student exploration, and low teaching quality. In the past two years, the rapidly developing generative artificial intelligence has opened new avenues for high-quality educational development, igniting public expectations for the future of education and becoming a hot topic among educators.1. Why Apply Generative AI in TeachingAs a representative of new productive forces, generative AI, with its rich corpus and powerful interactive understanding and dialogue capabilities, presents opportunities for solving teaching challenges and innovating teaching methods. Its main advantages are reflected in the following four aspects.First, efficient text processing optimizes teaching design.Generative AI has the ability to perform logical reasoning, summarization, and deductive analysis in specific contexts, enabling it to derive diverse answers or problem-solving solutions. Teachers can utilize generative AI products like Spark, Wenxin Yiyan, and Doubao to efficiently search for teaching resources and automatically generate lesson plans, reducing their workload and allowing them to focus their time and energy on more valuable course design and student guidance. Teachers can also use generative AI as subject experts to analyze and evaluate lesson plans from multiple dimensions, helping them better grasp teaching key points and accurately design learning activities and targeted assignments.Second, multi-modal information processing generates digital resources.Generative AI has the ability to understand multi-modal data such as text, images, audio, and video, achieving cross-modal semantic analysis and transformation, generating multi-modal digital resources. With the help of generative AI, every teacher can become a creator of digital resources, easily and independently generating personalized digital resources without needing to master professional media production skills. Especially with the launch of products like Sora, various teaching short videos, animations, and 3D models can be automatically generated based on teachers’ needs, providing stronger resource customization services.Third, smooth human-computer dialogue aids in deep student exploration.Generative AI possesses strong contextual understanding and continuous dialogue capabilities. Teachers can guide students to conduct personalized explorations and critical learning based on competencies. Students can organize questions before class and use generative AI to answer them. During class, teachers can organize targeted discussions, guiding students to engage in collaborative exploration and critical questioning with generative AI, helping clarify conceptual misunderstandings and expand knowledge boundaries. Furthermore, generative AI can provide insightful questions and automatically adjust the difficulty of questions, promoting students’ deep understanding and creative processing of knowledge through continuous inquiry cycles.Fourth, anthropomorphic intelligent agents enhance learning engagement.Many generative AI products currently offer intelligent agent functions to create customized virtual characters. Teachers can construct teaching intelligent agents based on teaching needs, enabling natural dialogue between students and agents through text, voice, and other forms to answer student questions and guide activities. Compared to general large models, teaching intelligent agents can be assigned different character identities, such as “third-grade Chinese teacher” or “senior biology teacher,” simulating real characters’ images, voices, and dynamic behaviors to strengthen emotional connections with students, thereby increasing student interest and participation.2. How to Apply Generative AI in TeachingTo better leverage the aforementioned technological advantages and mitigate potential risks and drawbacks, the application of generative AI in teaching should adhere to the following three basic principles.First, enhance the cognitive initiative and depth of human-computer interaction.The core purpose of human-computer interaction is to stimulate students’ active thinking and exploration, aiming to awaken students’ mental vitality to the greatest extent, rather than allowing AI to replace their thinking and creativity. If generative AI is misused, it may lead to students’ excessive reliance on technology, gradually weakening their thinking and innovation abilities. To avoid negative impacts and ensure technology truly promotes students’ cognitive development, teachers must accurately identify students’ cognitive initiative and depth in human-computer interactions. Cognitive initiative reflects students’ active participation in generating AI prompts, while cognitive depth involves students’ cognitive processing and handling levels of the content generated by AI.Second, balance the ratio of “pre-set” and “dynamically generated” content.With the introduction of generative AI, the content generated in the classroom becomes more dynamic, random, and uncontrollable. Therefore, teachers need to reasonably set the time ratio of pre-set teaching content and generative learning activities in classroom teaching to ensure orderly classroom instruction. For younger students, teachers can enhance the proportion of pre-set content to help them build an understanding of basic concepts. Depending on students’ grasp of knowledge, teachers can moderately guide students to use AI for independent exploration. For middle and high-grade students, teachers can increase the proportion of generative learning activities, using open-ended questions, project-based learning, independent programming, and free creative image-making to promote broader and deeper exploration in the classroom.Third, reinforce the verification and safe use of generated content.The large-scale datasets used to train generative AI come from a wide range of sources, but due to algorithmic biases and corpus quality issues, the authenticity and accuracy of generated content cannot be guaranteed, and the output information may contain errors or fabrications. Therefore, both teachers and students should avoid “blind trust and blind following” during the use of generative AI, carefully evaluating the generated content and enhancing the identification of information accuracy and authority to prevent scientific errors in classroom teaching. Additionally, both teachers and students need to understand and emphasize the data security and privacy issues brought by the use of generative AI, fostering awareness and enhancing preventative capabilities.3. Issues to Note When Applying Generative AI in TeachingThe empowerment of teaching by generative AI should emphasize an “effect-oriented” approach, and it should not be used for its own sake. Frontline teachers need to proficiently use various intelligent tools, focusing on standardizing the use of prompts, designing deep learning tasks, reinforcing the effectiveness of technology, creating supportive roles, and choosing appropriate application timings.Enhance students’ ability to use prompts correctly.Effective human-computer interaction relies on users being able to express their needs clearly and accurately through prompts. Teachers should teach students how to use prompts correctly and normatively. Based on the cognitive initiative in human-computer interaction, prompts can be categorized from low to high involvement: “directly using existing prompts,” “modifying prompts based on templates,” “writing prompts that are refined by AI,” and “completely rewriting prompts.” Teachers can select suitable starting points according to students’ cognitive levels and guide them from lower to higher cognitive involvement methods. Younger students should start their attempts at human-computer interaction under teachers’ guidance by “directly using existing prompts” or “modifying based on templates.”Design learning tasks with cognitive processing depth.To mitigate the potential cognitive inertia induced by AI use, teachers need to comprehensively innovate traditional learning task design concepts from the perspective of enhancing students’ cognitive processing depth. Specific strategies include designing creative and analytical learning tasks, avoiding single, fixed-answer questions, and using open-ended, unstructured questions and projects; employing diverse evaluation methods such as oral reports, group discussions, and peer evaluations when assessing learning task results; and cultivating students’ self-monitoring abilities regarding their cognitive processing depth during learning tasks completed with AI.Pay high attention to the effectiveness of technology application.To ensure the effectiveness of human-computer interaction in the classroom, teachers need to analyze the cognitive processing depth required for learning tasks beforehand, clarify the minimum cognitive input needed to complete tasks, and develop feedback plans for students using AI-generated content. Teachers should carefully plan the learning activity scenarios and task types and sequences for students using AI to ensure that generated content can facilitate the achievement of teaching goals. For example, in a third-grade Chinese writing class, the teacher designed an activity where “students use their imagination to verbally describe autumn scenery and generate creative images using a large model through voice input.” During implementation, although students showed strong interest in the independently generated images, the teacher did not timely summarize the descriptive language used in students’ verbal expressions regarding the features of the generated images. Although AI applications stimulated learning interest, they fell short in achieving the goals of the Chinese language subject.Create rich, subject-specific supportive roles.Generative AI can assume diverse roles in classroom teaching, including subject experts, tutoring teachers, learning partners, and speaking practice companions. Teachers can utilize generative AI to set up various teaching intelligent agents that fit the characteristics of different subjects, such as virtual engineers, virtual researchers, and virtual tour guides, greatly enhancing the immersive experience of project-based learning and interdisciplinary thematic learning. Of course, the classroom, as the primary place for education, should always keep human interaction at the core of teaching activities, with human-computer interaction serving as a supportive role in the triadic relationship among teachers, students, and machines. The emotional experiences and humanistic care in real exchanges and interactions cannot be replaced by even the most sophisticated anthropomorphic intelligent agents.Select appropriate timings for teaching applications.Although generative AI can enhance the interactivity, dynamism, and participation of classroom teaching, its application is not suitable for all teaching segments. Introducing generative AI too early or casually may disrupt teaching order and affect teaching quality. Generally, there are three appropriate timings for applying generative AI in the classroom: first, when students are confused and at a loss regarding their understanding of knowledge; second, when conducting group exploratory tasks with a certain level of challenge; and third, when teachers need to activate classroom dynamics based on teaching progress and changes in student learning states. Of course, the specific timing needs to be flexibly handled by teachers in consideration of factors such as student conditions, subject characteristics, goal attainment, and content difficulty.
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