Technological innovation is the fundamental driving force behind the progress of human civilization. Every technological and industrial revolution profoundly changes the world’s development landscape and power dynamics. In today’s era, with the rapid development of artificial intelligence, generative artificial intelligence brings profound impacts across various fields of society, including education, through continuous iteration and optimization. It is quietly transforming our accustomed modes of learning, working, and living. In 2022, ChatGPT emerged as a phenomenal application of generative artificial intelligence technology, capable of empowering various industries, and upon its launch, its user base reached unprecedented heights, quickly becoming a global topic of discussion. Those working on the front lines of education are also objectively reflecting on its value and applications: What attitude should we adopt towards generative artificial intelligence? What does it mean for teachers and students? What impact will it have on existing classroom teaching? Clarifying the advantages and limitations of generative artificial intelligence, assessing the challenges it may pose to classroom teaching, and exploring how the education system should prepare to meet these challenges is of great significance for promoting the high-quality development of AI-empowered teaching.
Challenges of Generative Artificial Intelligence to Classroom Teaching
From a technological perspective, while generative artificial intelligence is not yet perfect, it still holds milestone significance in the field of artificial intelligence, accelerating the expansion of human cognitive boundaries and providing ideas and technical support for the iterative upgrades of various intelligent education platforms. From an application perspective, generative artificial intelligence has a sustained substitutive effect on human self-function, which is enough to alert humanity to the potential challenges we may face in the future, and classroom teaching is no exception. In other words, these challenges have existed since the initial application of information technology and artificial intelligence in educational activities, and the emergence of generative artificial intelligence, represented by ChatGPT, has only intensified concerns about these issues.
(1) Confusion of the Subjective Position in Teaching
Subjectivity is the fundamental attribute of a person as an active subject. Faced with the iteration and upgrading of generative artificial intelligence and its intervention in education, people often become enamored with the technical appearances presented by generative artificial intelligence. The subjectivity of intelligent machines in the classroom teaching process is increasingly enhanced, neglecting the individual’s own needs, and indicating that generative artificial intelligence may trigger a new round of crises concerning teaching subjectivity, which may obscure and suppress human subjectivity to some extent, resulting in the overstepping of machine subjectivity. Specifically, as the primary teaching subject, the subjectivity of teachers will be obscured. Generally, people’s recognition of the value of teachers tends to remain at the level of “knowledge imparting”. However, the emergence of generative artificial intelligence has made people realize that the knowledge reserves of machines far exceed the cognitive capacities of individual teachers, and their superiority in knowledge impartation far surpasses that of teachers, thus leading to a questioning of the subjective position of teachers in the classroom teaching process. Furthermore, as an auxiliary teaching tool, students may also use the tool to complete assignments or even cheat on exams. This is because generative artificial intelligence provides answers to assignments and exam questions at a low cost, thereby altering the autonomy of students in their learning processes. Over-reliance on the instrumental value of generative artificial intelligence can easily lead to students losing their ability to think independently.
The function of education lies in developing the essential qualities of students, which is about training and cultivating students’ key competencies. The application of generative artificial intelligence replaces part of the intellectual and physical labor of students, skipping the process of cultivating students’ abilities and directly transitioning to the presentation of final results. Guided by the principle of energy conservation in the human brain, generative artificial intelligence can help students reduce energy expenditure and improve learning efficiency, making students naturally defenseless against generative artificial intelligence and instinctively choosing to think “efficiently”. Students find it easier to acquire knowledge and complete assignments, becoming immersed in the dopamine-driven pleasure generated by these easily accessible shortcuts, while their insights and wisdom about things diminish. In this context, the issue of the futility of studying will re-emerge from a new perspective: no matter how much one studies, they cannot surpass machines. Once this happens, generative artificial intelligence will occupy an important position among teaching subjects due to its rapid responses, rich content, and interactive generation features, leading to the illusion that it can replace teachers, thereby exacerbating the risk of emphasizing knowledge teaching while neglecting the fundamental purpose of education, hindering the emotional development of students and the formation of well-rounded personalities.
(2) Ambiguity of Students’ Moral Norms
Moral norms are widely present in the field of education and need to be guided by mainstream values to help teachers and students construct moral norms that constrain and guide their various behaviors. Although generative artificial intelligence should comply with legal and regulatory requirements when providing products or services, respecting social ethics and public order, science and technology are not value-neutral. As a product of the Western discourse system, the content generated by generative artificial intelligence inevitably carries ideological biases. At the same time, as previously mentioned, the content generated by generative artificial intelligence has issues of knowledge uncertainty, such as insufficient timeliness and factual errors, and continues to produce answers it considers correct. Therefore, it is particularly important for users to possess a certain level of digital literacy. Digital literacy refers to the ability of users to reasonably utilize information technology to acquire relevant information, helping individuals discover, analyze, and solve problems through the construction of new knowledge. It requires individuals to have corresponding digital awareness, knowledge, skills, and cultivation. However, for students, who are a group with limited knowledge sources, the lack of relevant experience and ability, coupled with their insufficient sensitivity and judgment towards information, makes them easily misled by some erroneous information or values generated by generative artificial intelligence. Over time, students’ beliefs, attitudes, and behaviors may change or deviate, thus affecting the construction of their moral norms and the formation of related boundaries.
Moreover, during classroom teaching activities, although generative artificial intelligence can mimic various languages in human interactions, providing some emotionally responsive feedback to signals emitted by students, these interactive functions are essentially results of data aggregation and statistical calculations. The originally warm and wise teacher-student relationship is alienated into a cold, symbolic interaction that cannot provide students with appropriate emotional feedback and cannot truly enter the students’ hearts to create emotional resonance. This lack of emotional exchange between teachers and students further dissipates the essence of the interpersonal activities carried out in classroom teaching, especially the spiritual encounters between teachers and students. Students, immersed in the experiences brought by virtual interactions, inevitably lead to a decline in their social emotional abilities in the real world. Over time, when faced with contradictions that require understanding of underlying meanings and logical relationships, students will also be unable to engage in reasonable logical reasoning and value judgments, thereby affecting the construction of their moral norms.
(3) Monotony of Classroom Teaching Methods
Teaching methods are the specific activity states within the teaching process, including how teachers teach and how students learn. The way teachers teach constrains how students learn, while students’ learning, in turn, influences how teachers teach. Additionally, individual cognition relies on the types of experiences, and the forms of knowledge should be embodied; otherwise, it will stifle human cognitive abilities. Students interact with generative artificial intelligence, obtaining experiences that are processed by computers into secondary materials, which should have been gained through students’ own engagement with the external world, but are instead alienated into one-dimensional knowledge transmission, directly transitioning to the acquisition of indirect or disembodied experiences. Disembodied experience refers to a learning method that relies on a single sense, a cognitive process detached from experiential foundations, and lacks the achievement of emotional experiential goals. In other words, digital technology places greater emphasis on the intent of knowledge; in this context, students’ learning process is primarily a “listen—remember—practice—reproduce” cycle, with very few opportunities to assign meaning to knowledge through personal experience. Students have developed a dependency on the technology of generative artificial intelligence, becoming accustomed to passive acceptance. Their embodied experiences are weakened, thus diminishing and eroding the enthusiasm for active learning, gradually abandoning thinking, exploration, and summarization, resulting in knowledge that cannot be transferred to real life or new contexts, failing to achieve the critical and creative thinking and abilities required for deep learning. Moreover, the intelligent recommendations of generative artificial intelligence represent a fragmented learning approach, making it difficult for students to access comprehensive and rich information, thereby hindering the construction and mastery of systematic knowledge, which does not constitute genuine learning.
The integration of generative artificial intelligence and classroom teaching is unstoppable, driving profound changes in teaching methods. Only by actively embracing the significant changes brought about by new technologies and minimizing the side effects during the application process can we better serve educators. Specifically, in the context of generative artificial intelligence, based on the changes in teaching methods, classroom teaching aims to construct multi-dimensional real situations, ubiquitous learning spaces, collaborative inquiry methods, and personalized learning processes, thereby achieving competency-oriented teaching supported by generative artificial intelligence. In this process, transforming students’ “energy-saving” mentality and behaviors while assisting their autonomous learning undoubtedly presents a significant challenge for school education, especially for teachers. They need to continuously develop and enhance their relevant abilities to integrate education and nurture students, improving and optimizing existing teaching strategies and methods to prevent students’ creative cognitive activities from being replaced by technological logic, enabling them to achieve comprehensive and healthy growth through embodied experiences and integrated knowledge.
(4) Increased Difficulty of Assessment and Evaluation
With the deep involvement of generative artificial intelligence in classroom teaching, many repetitive and simple intellectual tasks in classroom teaching are gradually being replaced by artificial intelligence. This means that teachers and students need to engage in higher-level activities, which are more creative. This inevitably requires classroom teaching to shift towards cultivating creative talents, which not only raises higher demands on teachers’ abilities but also naturally increases the difficulty of assessment and evaluation. According to existing classroom teaching evaluation standards, the performance of generative artificial intelligence in examinations surpasses that of most students, further highlighting the drawbacks of comparison and competition among students based on exam scores. At the same time, the ethical controversies surrounding generative artificial intelligence can easily lead to panic over students committing academic fraud, that is, students using generative artificial intelligence to complete assignments, resulting in teachers facing a certain integrity crisis when evaluating students’ learning outcomes. Clearly, the traditional evaluation methods that rely on memorization to achieve high scores overlook the current societal emphasis on independent thinking, innovation, and critical awareness, which seems unreasonable in the era of generative artificial intelligence and calls for a reform of the evaluation system.
From the perspective of learning behavior, the emergence and development of generative artificial intelligence have greatly improved the efficiency of teaching work, making deep, understanding-based learning more important for educators. Coupled with the new changes in societal talent demands, the shift from knowledge-centered teaching to the cultivation of thinking and abilities means that future classroom assessments will increasingly focus on enhancing students’ practical problem-solving abilities. In light of these innovative practices, the existing evaluation system can no longer meet the developmental needs of students. Therefore, the assessment and evaluation in the era of generative artificial intelligence need to emphasize a transition from score-oriented evaluations to competency-oriented evaluations. Unlike traditional score evaluations that are simple and easy to implement, competency evaluations as qualitative assessments are comprehensive quality evaluations based on “knowledge + competency”. The formulation of evaluation standards, collection of process data, and how to scientifically and comprehensively reflect students’ development levels undoubtedly pose a significant challenge to existing school education.
Strategies to Address the Challenges of Generative Artificial Intelligence
The integration of generative artificial intelligence and classroom teaching is an inevitable trend. In the face of the aggressive arrival of generative artificial intelligence, it is necessary for the education system to guide and prepare for the challenges that technology may bring to classroom teaching, viewing these challenges as opportunities to reconstruct the relationship between humans and machines in teaching, achieving a mutual pursuit and transcendence between humans and machines, and cultivating more innovative talents with higher-order thinking abilities.
(1) Creating a Warm Classroom Teaching Space
With the further development of generative artificial intelligence, its advantages in knowledge integration and extraction are more pronounced than those of teachers, significantly improving students’ knowledge learning efficiency. However, the indirect transmission of experiences cannot replace the entire classroom teaching process. The process of students acquiring direct experiences through specific practical activities inside and outside the classroom, and the emotional experiences derived from face-to-face interactions with teachers in real classrooms, are things that generative artificial intelligence cannot accomplish. In other words, interaction in classroom teaching encompasses not only knowledge interaction but also behavioral and emotional interactions. Generative artificial intelligence is essentially an online education system that plays an important mediating and facilitating role in promoting knowledge interaction, but the behavioral and emotional interactions between teachers and students cannot be replaced by technology. Therefore, the iterative development of generative artificial intelligence demonstrates to us that, compared to the transmission of book knowledge, it is more urgent to guide students’ values, cultivate innovative abilities, develop good habits, and promote healthy physical and mental growth. The previously overlooked labor education and practical education become particularly important in students’ growth processes. The completion of these goals requires teachers, students, and technology—the three main subjects of classroom teaching—to complement each other without omission, fulfilling their respective tasks, missions, and responsibilities, rather than being coerced by technology, thus creating a warm classroom teaching space to promote high-quality educational development.
Specifically, the creation of classroom teaching space is inevitably linked to the transformation of roles and the restructuring of relationships among teachers, students, and technology. Teachers, besides being “knowledge transmitters”, are more importantly “mentors”—not only imparting knowledge but also providing wise guidance and cultivating relevant abilities. In this regard, teachers must continuously enhance their own capabilities, reflect on what to teach, why to teach, and how to teach in the context of the significant changes in the educational environment today, proactively promoting the shift of future education focus from knowledge transmission to fostering students’ independent thinking abilities, innovation and critical thinking, social and emotional skills, and interpersonal communication abilities, thereby creating more possibilities for students’ holistic development in morality, intelligence, physical fitness, aesthetics, and labor.
Students should become their own educators, transforming from passive recipients to active creators, cultivating well-rounded personalities, and consciously linking individual growth with the realization of social values, thus becoming fulfilling individuals. Generative artificial intelligence, like past tools such as blackboards and slides, serves as a new medium in the new era, providing humans with a convenient carrier and tool, but cannot surpass human subjectivity. Especially in the context of classroom teaching, which involves special interpersonal interactions between teachers and students, embedding generative artificial intelligence, represented by ChatGPT, into the new era of intelligent education should not replace teachers’ subjectivity but rather promote the realization of personalized education and the development of students’ individuality.
(2) Constructing a Deep Classroom Teaching Environment
A deep classroom teaching environment refers to the deep integration of generative artificial intelligence with classroom teaching, achieving a “leapfrog” in future classroom teaching to cultivate top innovative talents for national development in the intelligent era. From this perspective, there is a need for targeted education, meaningful learning, and wise classroom empowerment for the construction of a deep classroom teaching environment.
First, establishing educational goals. The ultimate purpose of education lies not only in the transmission of knowledge but, more importantly, in shaping students into individuals with well-rounded personalities and comprehensive development, with social and emotional skills being core to adolescents’ mental health and character quality. However, regarding the current training of students in China, the most pressing reality is the imbalance in the development of cognitive abilities and social-emotional skills, meaning that the education system still emphasizes cognitive capability development, always aiming at imparting specific knowledge and skills. Education in the intelligent era needs to aim for innovation as a higher-order goal, corresponding to the creation of knowledge rather than its inheritance, focusing on the cultivation of key abilities under the guidance of core competencies. In other words, compared to traditional artificial intelligence, generative artificial intelligence achieves a qualitative enhancement. At the same time, the development of students’ abilities also needs to be redefined. Based on previous analyses, among these abilities, the cultivation of social-emotional skills, digital literacy, and independent thinking abilities is increasingly significant in the context of classroom teaching in the intelligent era. In summary, we must not only focus on how to better apply generative artificial intelligence in classroom teaching but also on how to cultivate individuals capable of creating such tools. Therefore, education in the intelligent era aims to cultivate top innovative talents, developing students’ social-emotional skills, digital literacy, independent thinking abilities, and other non-cognitive skills.
Second, implementing meaningful learning. Meaningful learning in the classroom teaching process refers to the establishment of connections between meaningful information in the content taught by teachers and students’ existing knowledge structures. Under the influence of generative artificial intelligence, implementing meaningful learning primarily requires reshaping teachers’ competencies, with the prerequisite being that students possess the inclination towards meaningful learning and foundational knowledge. In this regard, it is essential to recognize that teachers are a unity of “knowledge transmitters” and “mentors”, with their roles in classroom teaching primarily manifested in their guardianship and exemplary roles over life. Therefore, teachers should respect and affirm their value in the teaching practice process, striving to find points of integration between classroom teaching and generative artificial intelligence with a more positive attitude, thereby continuously improving their teaching abilities while achieving the high-quality development of classroom teaching empowered by generative artificial intelligence. These teaching capabilities mainly include the ability to select teaching content, the ability to explore the value of nurturing, and the ability to collaborate in multi-faceted nurturing. With the powerful knowledge reserves of generative artificial intelligence, teachers need to devote more time and energy to imparting knowledge and cultivating abilities that artificial intelligence cannot replace, focusing on reflecting students’ value cultivation, enhancing thinking methods, developing willpower, and learning social-emotional skills in their content selection. With generative artificial intelligence, classroom teaching can involve dialogues between teachers and machines, between students and machines, between students and teachers, and among students, teachers, and machines. In these multi-dimensional human-machine interactions, not all possess nurturing value; thus, teachers must develop the ability to extract nurturing value from these dialogues. Moreover, in these multi-faceted interactions, teachers need to possess the capability to collaborate with different subjects to maximize their integrated nurturing value. Regarding students’ inclination towards meaningful learning and foundational knowledge, it is crucial to establish a correct psychological inclination for students to use generative artificial intelligence, that is, to use it rationally and enhance efficiency. Education in the era of generative artificial intelligence has shifted from traditional learning to innovative learning, requiring students to become active participants and self-guided learners. At the same time, it is essential to think comprehensively, objectively, and rationally about the accuracy and credibility of the content generated by generative artificial intelligence.
Finally, creating a smart classroom. Generally speaking, education is scaled, while students’ learning is personalized. The classroom serves as the main venue for teaching and nurturing. Educators leverage the powerful assistance of generative artificial intelligence’s thinking chain to provide various teaching tools or models for classroom teaching, creating corresponding scenarios to build an intelligent and efficient classroom teaching environment that attracts students to learn autonomously. In these conflicts between scale and personalization, maximizing the realization of personalized learning and fostering creative thinking is essential. Specifically, teachers should maximize the use of generative artificial intelligence technology to collect academic data, automatically generating suitable learning paths and resources based on recorded data from students’ learning processes, including academic performance, learning habits, interests, and hobbies. Simultaneously, leveraging its high-precision assessment of students’ personalities and commonalities allows for real-time monitoring of students’ engagement, learning progress, and other learning conditions, thereby providing technical support for the realization of personalized teaching and achieving the results of “intelligent emergence” in the gradual and proactive construction of learning processes. Furthermore, in this process, teachers should also pay attention to exemplifying their technical ethics, emphasizing the value guidance of technical ethics to students, including imparting knowledge related to technical ethics and potential risks and benefits, preventing students from deviating in behavior during the use of technology and reducing their learning engagement.
(3) Implementing Robust Classroom Teaching Regulations
To address the risks and challenges that generative artificial intelligence may bring to classroom teaching, the fundamental requirement is to enhance autonomous innovation capabilities. The most urgent need is to break down institutional and systemic barriers to maximize the liberation and stimulation of the immense potential of teachers and students as subjects of classroom teaching, allowing all sources of innovation to flow freely. Therefore, while formulating clear and executable relevant institutional norms, it is also necessary to advocate for users to adhere to these norms and ethical guidelines during use, ensuring that technology is not only utilized well but also reasonably regulated. Currently, some countries, regions, and schools have begun to formulate institutional norms and ethical guidelines for the use of generative artificial intelligence to ensure that teachers and students utilize it in a manner that conforms to norms and ethics.
From a macro perspective, at the national level, it is essential to strengthen the top-level design and leadership of regulations. It is necessary to improve the formulation of policies and regulations related to generative artificial intelligence, such as usage norms, risk prevention, regulatory methods, and accountability mechanisms, and establish strict data privacy protection regulations, timely supervising and correcting errors that arise during the use of intelligent technology, thereby providing a bottom-line guarantee for concerns regarding generative artificial intelligence technology. In this regard, countries around the world have begun to draft relevant laws and regulations. For instance, the European Parliament has voted to pass the “Artificial Intelligence Act”, and in China, the National Internet Information Office, the National Development and Reform Commission, the Ministry of Education, and other seven departments jointly issued the “Interim Measures for the Management of Generative Artificial Intelligence Services”, which officially came into effect on August 15, 2023, aiming to promote the healthy development and standardized application of generative artificial intelligence. It is noteworthy that the formulation of relevant policies and regulations should not be a “violent response to violence”—that is, administrative power should not intervene and interfere coercively—but rather should “defeat magic with magic”, using more powerful artificial intelligence technology to regulate artificial intelligence, adopting legal means to achieve traceability of generated content and enhancing the transparency of products and services. At the same time, it is crucial to emphasize the ethical attributes of artificial intelligence policy regulations, prohibiting actions that undermine human dignity, democracy, equality, freedom, privacy, and rights, thus highlighting their practical operability.
From a meso perspective, at the social level, various parties should play a collaborative role. First, educational management departments at all levels should clarify the specific links and corresponding usage norms, regulatory methods, and accountability mechanisms for the use of technology in education. For instance, abandoning the existing assessments that emphasize knowledge memorization, forming a new evaluation mindset that prioritizes “thinking over knowing, questions over answers, and logic over listing”, introducing multi-dimensional assessment standards, accelerating the transition from score-based evaluations to competency-based evaluations, highlighting fairness and scientificity in assessments, and ensuring adherence to educational ethical norms. Second, with the support of government departments, social organizations and groups should quickly develop generative artificial intelligence products suitable for teachers and students in China, establishing a corresponding system of standards and norms for intellectual property protection and continuous supervision, assisting the high-quality development of classroom teaching while ensuring safety. For example, to effectively respond to and prevent the misuse and abuse of generative artificial intelligence, the 2023 World Artificial Intelligence Conference’s “Technology Ethics Governance” forum proposed the “Self-Regulatory Convention on Generative Artificial Intelligence Ethics (Draft for Consultation)”, and several leading companies are strengthening the development of similar products.
From a micro perspective, at the school level, relevant personnel should enhance their proactive awareness and sense of responsibility. As previously mentioned, the rise of generative artificial intelligence, represented by ChatGPT, will inevitably have profound impacts on talent cultivation standards, curriculum design, textbook writing, examination evaluation, and management methods. This suggests that school administrators and teachers must inevitably improve their understanding of the profound influence of generative artificial intelligence technology on education, grasp the close relationship between technology and classroom teaching, proactively adapt, and assume responsibility, thereby promoting the high-quality development of classroom teaching empowered by technology. For instance, school administrators should enhance their understanding of the impact of generative artificial intelligence technology on school education, elevate their sense of responsibility in promoting the transformation of classroom teaching empowered by generative artificial intelligence, and strictly examine, supervise, and provide feedback on all aspects of the use of generative artificial intelligence in classroom teaching. At the teacher level, it is essential to persist in manually screening, verifying, and confirming generated content, supervising and guiding students throughout the entire process of using generative artificial intelligence, and utilizing generative artificial intelligence to collect students’ process data to innovate and design teaching based on students’ development. At the student level, they should also proactively adapt, actively increasing their knowledge about generative artificial intelligence, consciously using it objectively and scientifically, and becoming self-educators.
Source: “Curriculum, Textbooks, and Teaching Methods” Educational Informatization 100 People
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