The report of the 20th National Congress of the Communist Party of China first proposed to “promote digital education and build a learning society and a learning nation for lifelong learning.” In 2023, General Secretary Xi Jinping emphasized during the fifth collective study of the Political Bureau of the CPC Central Committee: “Digital education is an important breakthrough for our country to open up new paths for educational development and shape new advantages in educational development.” The 2024 World Digital Education Conference proposed, “Implement AI empowerment actions, promote the deep integration of intelligent technology with education and teaching, assist teaching and learning with intelligence, and develop intelligent learning companions and intelligent teaching assistants.” With the rapid development and increasing popularity of artificial intelligence technology, the deep integration of AI and education is imperative.

Generative artificial intelligence represented by ChatGPT has a significant impact on education. ChatGPT empowers teaching, shifting the teaching model from a binary structure of “teacher-student” to a ternary structure of “teacher-machine-student,” promotes the transition of teaching content from human production to intelligent production, and catalyzes the evaluation model of “knowledge + competence”; ChatGPT empowers learning, promoting the ubiquitous learning space, meeting the personalized needs of the entire learning process, and forming a human-machine collaborative learning model; ChatGPT empowers education, shifting the educational philosophy towards the cultivation of higher-order abilities and comprehensive quality, innovating the educational model of interdisciplinary integration.

The traditional embedded teaching model has several issues, such as low student interest and initiative, rapid updates and iterations of knowledge, few practical cases, and a single evaluation form, failing to meet personalized learning requirements. To solve these problems, this project uses generative AI tools like ChatGPT, Douyin, Wenxin Yiyan, and Xinghuo during the teaching process, transitioning the teaching interaction from “teacher-student” to “teacher/student/machine” deep interaction; updating teaching resources and content through AI, shifting teaching content from static subject knowledge to dynamic comprehensive tasks; changing the teaching model from teacher-centered to student-centered, combining project-based learning and human-machine collaborative learning, providing more intelligent and personalized teaching services and learning support, offering students better learning experiences and practices; shifting the educational philosophy from knowledge-oriented to emphasizing “capabilities first, values first”; and transforming evaluation methods from “result evaluation” to “diverse evaluation.”

1. Constructing a “Dual Teacher Classroom” Project-Based Teaching Model Based on AI

2. Teacher-Student Collaboration, Updating Teaching Resources and Content Based on AI, Constructing an Embedded Knowledge Graph

Relying on generative AI tools like ChatGPT, Douyin, Wenxin Yiyan, and Xinghuo, combined with embedded course resources, teachers and students collaborate to update teaching resources (digitally constructed basic materials, digital outlines, digital lesson plans, student-participated digital online courses, knowledge graphs, virtual teacher materials, digital ideological materials, etc.). With the help of digital platforms, teaching content and resources are updated in real-time, ensuring that teaching content synchronizes with the latest technological advancements. AI course teaching emphasizes students’ active participation in knowledge construction, actively exploring and posing questions, and through collaboration with others, continuously constructing, reconstructing, and optimizing their knowledge systems, helping students better understand the essence and core of knowledge and cultivating their higher-order thinking abilities. In AI course teaching, it is necessary to contextualize learning tasks, allowing students to engage in self-directed exploratory learning and group collaborative learning, creating project works, ultimately completing innovative projects. Therefore, knowledge construction theory can help students deepen their understanding of AI knowledge, promoting the application of knowledge and the formation of innovative thinking in practice.

3. Constructing Diverse Evaluation and Intelligent Evaluation Methods

In AI course teaching based on design thinking, emphasizing diverse and intelligent evaluations throughout the teaching activities. Using diverse evaluations allows for multi-dimensional consideration, focusing on the cultivation of various student abilities. Students’ innovative designs may not form at once; they need to be continuously improved and perfected through collaboration and communication with peers. Diverse evaluations increase interaction and communication between teachers and students, as well as among students, helping teachers and students view the project design process from multiple perspectives, thereby aiding students in forming outcomes. Intelligent evaluations can achieve efficient collaborative evaluations across multiple scenarios. The methods of diverse learning effect evaluation are shown in Figure 2.

4. AI Empowered Curriculum Ideological Reform

To cope with the uncertainties brought by digitization and the increasingly severe ethical and security challenges, it is essential to adhere to safety bottom lines and ensure the safe operation of digital educational technologies. Key points for curriculum ideology include data network security, personal privacy protection, intellectual property protection, anti-algorithm discrimination, and embedded ideological case studies, strengthening digital ethics and security education for teachers and students, enhancing the legal, safety, and risk prevention awareness of digital education participants, and constructing a safer, fairer, and more responsible global digital education environment.

5. Promoting the Digitalization of Education

Against the backdrop of educational digitalization, the “Embedded” course will fully utilize information technology to promote the digitalization of education and teaching. By building online courses, knowledge graphs, and other teaching resources, students will be provided with convenient learning experiences. At the same time, the course will also utilize technologies such as artificial intelligence to achieve personalized teaching and intelligent recommendations, enhancing teaching effectiveness and learning efficiency.

6. AI Empowered Course Competition Integration, Enhancing Students’ Innovation Levels

Focusing on the concept of “promoting teaching through competition and integrating courses with competitions,” leveraging AI to extend teaching beyond the classroom, allowing teachers both in and out of class to obtain real-time learning conditions of students, and conducting digital evaluations through smart platforms, establishing personalized evaluation models for each student, assisting students in conducting personalized project designs and innovations. Students participate in various subject competitions based on innovative projects, continuously improving their innovation levels.

1. Established a Quality-Ability-Knowledge System Structure

AI empowers the embedded course quality-ability-knowledge system structure, which refers to enhancing and optimizing the structure of individuals or organizations in terms of quality, ability, and knowledge through artificial intelligence technology, specifically as follows:

(1) Quality: Enhancing students’ digital literacy, AI literacy, professional ethics, safety awareness, environmental awareness, and social responsibility; cultivating students’ innovative thinking, critical thinking, and lifelong learning abilities; nurturing innovative talents with good professional ethics, teamwork spirit, innovative awareness, and international vision.

(2) Ability: Training students’ AI application abilities; improving students’ abilities to use AI tools to solve practical embedded problems; enhancing students’ abilities to collaboratively complete design project implementations.

(3) Knowledge: Utilizing AI to quickly and conveniently acquire a large amount of embedded knowledge, learning knowledge integration and content updating.

2. Teaching Chapter Design – Constructing the “Dual Teacher Classroom” Project-Based Teaching

The process of constructing the “Dual Teacher Classroom” project-based teaching based on artificial intelligence is shown in Figure 3, where the teaching process is divided into three steps: pre-class, in-class, and post-class. Human teachers serve as the leaders, taking on project planning and guidance roles; students are the main participants, undertaking project exploration and research roles; virtual digital teachers serve as the main speakers, responsible for course teaching and consulting services.

Virtual digital teachers (ChatGPT, Doubao, Wenxin Yiyan, etc.): Virtual digital technology is a fusion of various technologies, including voice recognition, voice synthesis, natural language understanding, and animation generation. Creating virtual digital teachers involves importing the text of the teaching content into a production platform, driven by AI to generate teaching videos. Before class, students watch the teaching videos of the virtual digital teachers for preview; during class, the virtual digital teachers teach the content, and students can replay the virtual digital teachers’ explanation videos until they fully understand all the content; after class, if needed, students can review at any time. At the same time, students can communicate with tools like ChatGPT to complete information collection and organization.

Human teachers: Responsible for project planning and classroom activity guidance, human teachers can focus their main energy on solving students’ ad-hoc problems that arise during project planning and design, guiding students in designing plans, helping them find effective ways to realize their ideas, and paying attention to individual student needs, providing immediate guidance.

Students work in small groups relying on human teachers and AI to complete three tasks: pre-class project research, in-class project reporting, and post-class summarization and evaluation.

3. Achievements in Teaching Resource Construction

(1) Constructed virtual digital teachers: All embedded courseware, lesson plans, PBL problems, and related materials from recent years were uploaded to the AI system to build virtual digital teachers.

(2) Constructed a digital teaching resource library: Including online courses (building student-participated online courses for new energy technology projects), chapter-based project cases (constructed by students + human teachers + AI), smart maps (constructed by students + human teachers + AI), digital outlines, digital lesson plans, digital ideological materials, video analyses, etc. With the help of digital platforms, teaching content and resources are updated in real-time, ensuring that teaching content synchronizes with the latest technological advancements.

Figure 4 Knowledge Graph + Online Resources + Textbook Diagram

(3) Established diverse evaluation and intelligent evaluation methods. Including student self-evaluation, group peer evaluation, teacher evaluation, AI intelligent evaluation, etc.

(4) Formed the “Dual Teacher Classroom” project-based teaching model based on artificial intelligence and conducted practice.

(5) AI empowered curriculum ideological reform, forming a case library focused on AI ethics, data network security, personal privacy protection, intellectual property protection, anti-algorithm discrimination, and traditional new energy.

(6) Integrated course competitions, with students achieving over 300 subject competition awards, continuously enhancing students’ innovative abilities.

Figure 5 Undertaking Subject Competitions and Some Award Certificates

4. Conclusion

This case study utilizes generative AI tools such as ChatGPT, Douyin, Wenxin Yiyan, and Xinghuo during the teaching process, promoting the transition of teaching from “teacher-student interaction” to “teacher/student/machine” deep interaction, enhancing students’ interest in learning and personalized learning needs; updating teaching resources and content through AI, constructing an embedded course knowledge graph, transitioning teaching content from static subject knowledge to dynamic comprehensive tasks, enriching teaching resources; shifting the teaching model from teacher-centered to student-centered, combining project-based learning and human-machine collaborative learning, providing more intelligent and personalized teaching services and learning support, offering students better learning experiences and practice opportunities; shifting the educational philosophy from knowledge-oriented to emphasizing “capabilities first, values first”; transforming evaluation methods from “result evaluation” to “diverse evaluation,” changing the single evaluation model; and integrating AI with course competitions to enhance students’ innovative abilities.