Implementation Strategies for Generative AI in Interdisciplinary Theme Learning

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The “Compulsory Education Curriculum Plan (2022 Edition)” clearly states that “each subject should design interdisciplinary theme learning for no less than 10% of class hours,” emphasizing the need to “carry out interdisciplinary theme teaching and strengthen the collaborative educational function of the curriculum.”In the context of the rapidly growing trend of subject integration, cultivating students’ interdisciplinary innovative thinking is one of the important goals of current education.How can we leverage generative artificial intelligence to optimize interdisciplinary teaching design and foster students’ interdisciplinary innovative thinking?“Education Insight ‘AI+'”column today takes you to explore theimplementation strategies of generative artificial intelligence in interdisciplinary theme learning in science and language arts——

Application of Generative AI in Interdisciplinary Teaching Process
The course is based on the core concepts of “energy transformation and conservation” and “engineering design and physical chemistry” as outlined in the “Compulsory Education Science Curriculum Standards (2022 Edition)”. It conducts interdisciplinary teaching activities themed around “Design and Production of a Mini Solar Car,” integrating knowledge from science, information technology, mathematics, and art. This approach guides students to complete the design and production of the solar car, achieving interdisciplinary knowledge integration and application, cultivating project design and practical abilities, and enhancing environmental awareness and sustainable development concepts.
Generative artificial intelligence provides students with a brand-new learning experience through personalized content recommendations, real-time interactive Q&A, personalized learning tasks, intelligent grouping, and learning support. This not only improves learning efficiency but also fosters students’ innovative and critical thinking abilities. Using the “Wenxin Yiyan” tool, we can design the interdisciplinary teaching process of “Design and Production of a Mini Solar Car” from the following six aspects.
(1) Situation Introduction, Discovering Problems.The teacher plays images and videos of solar cars, showcases the physical solar car, allowing students to touch and feel its structure, and guides students to discuss the uses and principles of solar cars. In this phase, the application of generative artificial intelligence mainly involves intelligently recommending video teaching resources related to solar cars.
(2) Task-Driven, Analyzing Problems.The teacher presents the challenge of designing and producing a solar car, guiding students to analyze the key issues that need to be resolved in the design and production process. In this phase, the application of generative artificial intelligence mainly involves creating and presenting various design concepts for solar cars, providing students with more inspiration; generating extended content for the mind map framework to help students understand the theme more comprehensively.
(3) Team Building, Division of Labor and Collaboration.The teacher guides students to form teams based on their interests and strengths, instructing them on team division of labor and clarifying their respective responsibilities. In this phase, the application of generative artificial intelligence mainly involves assisting teams in task allocation, providing personalized suggestions based on members’ skills and interests.
(4) Knowledge Preparation, Scheme Design.The teacher instructs students to research materials, understand relevant knowledge, and guides them to formulate design schemes, using various digital tools (such as 3D modeling software) to sketch ideas. In this phase, the application of generative artificial intelligence mainly involves providing personalized learning suggestions and resource recommendations, helping students quickly generate multiple design schemes, accelerating the design iteration process, and providing design feedback.
(5) Learning Support, Scheme Verification.The teacher provides experimental equipment and tools to support students’ practical activities; guides students in testing the performance of the solar car, exploring factors that affect the speed of the solar car; analyzes students’ test results, identifies shortcomings in the design, and proposes improvement plans, providing materials and technical support for improvements. In this phase, the application of generative artificial intelligence mainly involves predicting potential problems students may encounter during production and assembly, providing corresponding solutions; offering online technical support and real-time answers to technical questions students encounter during practice.
(6) Problem Solving, Reporting and Display.The teacher organizes students to showcase the finished solar car and evaluate it, guiding students to share experiences and lessons learned during the design process, summarizing the design process, and proposing improvement suggestions. In this phase, the application of generative artificial intelligence mainly involves assisting students in creating PPTs or video materials, enriching the display content, analyzing students’ reflective summaries, and providing directions for improvement and further learning suggestions.
Generative AI Empowers Learning Resources and Experiences
Generative artificial intelligence can provide technical support for language arts interdisciplinary theme learning. Based on deep learning algorithms, it can learn language rules from massive data and generate coherent and creative text content. With advanced algorithms and powerful data processing capabilities, generative artificial intelligence can also effectively integrate knowledge from multiple disciplines, providing students with a comprehensive and in-depth perspective for knowledge exploration. Below, we will specifically discuss the interdisciplinary theme learning of “Tea Culture” in the ninth grade (third year of junior high school) as an example——
1. Building Learning Scaffolds to Empower Learning Resources
The interdisciplinary theme learning design generated by the “Tongyi Qianwen” artificial intelligence system based on the theme of “Tea Culture” includes four thematic tasks: “Source of Tea,” “Way of Tea,” “Charm of Tea,” and “Etiquette of Tea.” This focuses on the language arts subject using excellent ancient poetry and integrates knowledge from other disciplines. In terms of activity implementation, generative artificial intelligence provides answers based on students’ keyword searches and questions, intelligently analyzing and integrating learning resources.
(1) Efficiently Pushing Relevant Resources Based on Different Thematic Tasks
For example, in the first thematic task “Source of Tea,” the intelligent system first pushes excerpts and interpretations from “The Classic of Tea” to help students understand the origin and classification of tea; simultaneously, it retrieves and generates knowledge content related to tea culture, such as the harmony, nature, tranquility emphasized in tea, and the cultural connotations represented by tea, such as “harmony, respect, purity, and tranquility.” Students can better analyze and summarize the tea culture embedded in the poetry they have learned, feeling the characteristics of tea from “Three Gorges” in “The clear brook and green pool, reflecting the clear image”; and experiencing the openness and spirit of tea in “Yueyang Tower” with “not being pleased by material things, nor being saddened by oneself.”
(2) Generating Implementation Steps Based on Students’ Questions
For example, regarding the third thematic task “Charm of Tea,” combining knowledge from physics and chemistry generates the following learning steps for students: first, students use generative artificial intelligence to gather scientific articles and research reports on tea leaf components; second, students learn about the components and effects of tea leaves from the knowledge pushed by generative artificial intelligence; third, generative artificial intelligence generates a set of tea brewing simulation experiment plans based on principles, including controlling variables (such as the impact of water temperature on tea soup color and aroma) and observation recording sheets, allowing students to analyze the underlying physical changes (such as diffusion, dissolution) and chemical reactions (such as oxidation-reduction).
(3) Providing Diverse Learning Materials Based on Different Student Needs
For different students’ learning styles, such as visual, auditory, and hands-on learners, generative artificial intelligence can generate personalized learning materials, such as illustrated articles, audiobooks, and interactive simulation experiments. For instance, in the learning of thematic task four “Etiquette of Tea,” the tea master guidance video generated by generative artificial intelligence can provide a vivid and intuitive animation demonstration of the tea ceremony process and a step-by-step analysis of etiquette for visual learners, allowing them to learn comprehensively about tea ceremony etiquette.
2. Creating Learning Situations to Empower Learning Experiences
Artificial intelligence tools can create learning environments that transcend time and space limitations, providing students with immersive and interactive language arts learning experiences.First, empowering the generation of personalized content.By integrating the history, legends, and anecdotes of tea based on students’ learning interests and cognitive levels, engaging learning materials can be created using image generation and video synthesis capabilities. These stories and scenarios are not only intuitive and interesting but can also be continuously adjusted based on student feedback.
Second, empowering interactive dialogue and creation.By using technology to recreate the tone and image of historical tea culture masters or literary figures, students can engage in “face-to-face” discussions with ancient individuals, discussing the philosophy of tea ceremony and the cultural connotations behind poetry creation. Additionally, an intelligent interactive poetry creation platform can instantly generate thematic poetry drafts based on students’ input keywords or emotional tendencies, allowing students to engage in poetry contests with “ancient figures” to deeply appreciate the content and rhythm of poetry.
Finally, empowering the simulation and experience of digital contexts.Using intelligent technology to create a virtual ancient teahouse environment, students can enter the scene with VR or AR devices, autonomously choose and dynamically adjust details, immersively observing and experiencing the daily operations of the teahouse, interactions between customers, and tea art performances, enhancing learning participation and deepening their understanding of the social context and situational experiences of that time.
Implementation Strategies for Generative AI in Interdisciplinary Theme Learning
Generative artificial intelligence can effectively support the implementation of interdisciplinary teaching. While discussing how to leverage generative artificial intelligence to empower interdisciplinary teaching and optimize interdisciplinary teaching design, teachers must not overlook the potential risks and challenges related to the quality and bias of data, ethics, and morality in generative artificial intelligence. Before widely implementing generative artificial intelligence-assisted interdisciplinary teaching, it is still necessary to strengthen risk awareness education for teachers and students, enhancing their ability to identify and properly handle potential risks to ensure the safe and compliant application of technology.

Implementation Strategies for Generative AI in Interdisciplinary Theme Learning

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Implementation Strategies for Generative AI in Interdisciplinary Theme Learning
Implementation Strategies for Generative AI in Interdisciplinary Theme Learning

Implementation Strategies for Generative AI in Interdisciplinary Theme Learning

Source丨Modern Educational Technology Journal, Primary and Secondary School Information Technology Education
Editor丨Yezi
Design丨Jiachen
Reviewers丨Yangyang, Xibei
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Implementation Strategies for Generative AI in Interdisciplinary Theme Learning

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