Encouraging Human Ai Collaboration In Interactive Learning Environment
Humanities and Social Sciences Communications volume 12, Article number: 821 (2025) Cite this article The integrating AI into teaching and learning has the potential to transform traditional classroom environments into hybrid intelligence learning environments, whereby human teachers and AI teachers (educational robots) work together synergistically to enhance students’... To understand and optimize the synergistic effect of human–AI collaboration in hybrid intelligence learning environments, this study proposes a human–AI synergy degree model (HAI-SDM). A case study was conducted to examine the synergy degree and order degree in human–AI collaboration, involving forty students and one teacher from a class in a junior high school. The results indicate that the order degree between human teacher and AI machines remains at a moderate level while undergoing dynamic changes. The synergy degree fluctuates between low and moderate, reflecting relatively orderly development among the three subsystems (collaboration subject subsystem, collaboration process subsystem and collaboration environment subsystem), but one subsystem may exhibit disordered behaviours in...
These findings have implications for developing more effective human-AI classroom collaboration and promoting the effective integration of AI into teaching and learning. The rapid development of artificial intelligence (AI) technology has brought unprecedented opportunities and challenges to the education sector. Particularly, under the impetus of human–AI collaboration, AI not only serves as an auxiliary tool to support teachers’ instructional tasks but also actively participates in classroom interactions in an intelligent manner, facilitating a profound... 2024; Zhou and Hou, 2024; Hilpert et al. 2023). Traditional educational models have limitations in facilitating personalized learning and optimizing resource allocation.
Human–AI collaborative teaching offers an efficient and sustainable lens to address these challenges through close collaboration between AI systems and teachers (Díaz and Nussbaum, 2024; Chen et al. 2022). Human-AI collaboration in education, as an emerging interdisciplinary field, integrates cutting-edge theories and technologies from AI, education, cognitive science, and human–computer interaction. The Hybrid Intelligence Learning Environments design aims to develop and implement effective human–AI collaboration in education. Its core philosophy lies in the seamless integration of human intelligence and machine intelligence to achieve optimized teaching outcomes through their synergistic collaboration (Cukurova, 2024; Bredeweg and Kragten, 2022). Within this environment, AI not only functions as an assistant to teachers but also plays a vital role in personalized learning (Mittal et al.
2024), real-time feedback (Weber et al. 2024), cognitive intervention (Fan et al. 2024), and emotional engagement (Järvelä et al. 2023). In recent years, researchers started to look into the design of educational robots, the application of AI in teaching, and the cognitive and behavioural dynamics of human–AI collaboration (Schecter et al. 2022; Niu et al.
2024; Wu et al. 2024). Existing studies have demonstrated significant advantages of human–AI collaboration in enhancing learning efficiency and supporting personalized learning (Huang et al. 2021). For instance, the integration of AI applications in real-time question answering (Fang et al. 2023) and homework grading (Duan et al.
2023) has effectively reduced teachers’ workload while improved instructional quality. The most extensive literature on AI applications in education focused on technological aspects, lacking systematic examination of human-AI collaboration during classroom instruction (Vössing et al. 2022; Yue and Li, 2023). Given that effective human-AI collaboration relies on effective collaboration between humans and AI systems, investigating the effectiveness of collaboration and the degree of synergy in classrooms becomes crucial. To address this research gap, this study aims to develop a framework to evaluate and enhance the synergy and orderliness of human–AI collaboration in classrooms. Received 2023 Oct 2; Accepted 2024 Mar 23; Collection date 2024 Dec.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit... The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from... To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. In service of the goal of examining how cognitive science can facilitate human–computer interactions in complex systems, we explore how cognitive psychology research might help educators better utilize artificial intelligence and AI supported tools... We also aim to provide historical perspective, both on how automation and technology has generated unnecessary apprehension over time, and how generative AI technologies such as ChatGPT are a product of the discipline of...
We introduce a model for how higher education instruction can adapt to the age of AI by fully capitalizing on the role that metacognition knowledge and skills play in determining learning effectiveness. Finally, we urge educators to consider how AI can be seen as a critical collaborator to be utilized in our efforts to educate around the critical workforce skills of effective communication and collaboration. The purpose of this paper is to explore how the current model of instruction in higher education might respond to technological innovations in “artificial intelligence.” “Artificial intelligence” is in quotes because we are now... But since by the time you read this some of the information will be outdated due to the astounding pace of technological innovations, it is not unreasonable to think that true artificial intelligence might... In the current work, we will use AI as a placeholder for both the current large language models that are now available and more advanced versions that are yet to be. The goal of the current work is to recommend how higher education instruction can respond to widely available AI.
In service of this goal, we will first provide an overview of how the education enterprise has previously reacted to potential disruptive technological innovations. AI tools will be considered in this context, with the suggestion that they may pose a unique challenge and opportunity that other technologies have not. We next develop a framework for understanding the role AI might play in the classroom by considering three components: a framework for categorization of educational goals in the cognitive domain (Bloom’s Taxonomy), the expectations... The result of this analysis suggests an increasingly important role for practices that improve metacognition. Finally, we will use this framework to suggest actionable practices that can incorporate, rather than work in opposition to, AI in its current or any future instantiation. In a ever-changing-world, more than 500 teachers from 38 countries are actively reflecting the role of AI in the teaching methods of tomorrow.
During this session, experts and participants agreed that learning is primarily experienced through human interaction, even in the age of digital tools. However, it is essential that teachers adapt their practices to discerningly integrate these new tools and methods that are changing the way of teaching. Davide Ruscelli, Coordinator of the Secretariat of the Teacher Task Force for Education 2030, hosted by UNESCO, opened the session. He recalled the central role of UNESCO, which established the first holistic frameworks to support ministries in managing the challenges posed by AI. The organization reaffirmed the need to promote learner-centered practices and teacher autonomy. Davide is clear: AI is only a tool, never the heart of the education system.
The challenges remain equitable access, the prevention of inequalities, and the fight against reductive standardization. According to the expert, professional training must integrate ethical reflection and critical dialogue, thanks to renewed national frameworks and spaces for exchange on the use of AI in the classroom. The guidelines published by UNESCO encourage the development of critical thinking and call on each country to guarantee a minimum technical foundation for teachers. Davide acknowledges that AI promises to reduce the planning burden but requires that access to resources be ensured. He emphasizes the need for social and cross-disciplinary dialogue within schools to prevent teachers from becoming isolated in the face of the complexity of AI, and to involve them in national and local discussions... Davide recalled the experience of teacherless classrooms, which demonstrates how AI, in order to be an educational tool, requires careful integration.
Teachers, as key players, must be recognized in their role as mentors and tutors. As experience has shown, AI introduces the lesson before the teacher takes over; it is not a question of replacing humans, but of equipping them with tools to adapt their support. Experimentation, encouraged on a small scale, allows new forms of learning to be tested, while keeping critical thinking at the center of educational activity. According to Davide, it is no coincidence that UNESCO now plays a central role; the organization is actively shaping the debate, while reminding us that teachers remain irreplaceable. This is still uncharted territory that is evolving at an incredible speed. We must be able to contribute to this reflection both as individuals and as UNESCO officials in order to put people at the center of this system.
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Humanities And Social Sciences Communications Volume 12, Article Number: 821
Humanities and Social Sciences Communications volume 12, Article number: 821 (2025) Cite this article The integrating AI into teaching and learning has the potential to transform traditional classroom environments into hybrid intelligence learning environments, whereby human teachers and AI teachers (educational robots) work together synergistically to enhance students’... To understand and optimi...
These Findings Have Implications For Developing More Effective Human-AI Classroom
These findings have implications for developing more effective human-AI classroom collaboration and promoting the effective integration of AI into teaching and learning. The rapid development of artificial intelligence (AI) technology has brought unprecedented opportunities and challenges to the education sector. Particularly, under the impetus of human–AI collaboration, AI not only serves as an a...
Human–AI Collaborative Teaching Offers An Efficient And Sustainable Lens To
Human–AI collaborative teaching offers an efficient and sustainable lens to address these challenges through close collaboration between AI systems and teachers (Díaz and Nussbaum, 2024; Chen et al. 2022). Human-AI collaboration in education, as an emerging interdisciplinary field, integrates cutting-edge theories and technologies from AI, education, cognitive science, and human–computer interacti...
2024), Real-time Feedback (Weber Et Al. 2024), Cognitive Intervention (Fan
2024), real-time feedback (Weber et al. 2024), cognitive intervention (Fan et al. 2024), and emotional engagement (Järvelä et al. 2023). In recent years, researchers started to look into the design of educational robots, the application of AI in teaching, and the cognitive and behavioural dynamics of human–AI collaboration (Schecter et al. 2022; Niu et al.
2024; Wu Et Al. 2024). Existing Studies Have Demonstrated Significant
2024; Wu et al. 2024). Existing studies have demonstrated significant advantages of human–AI collaboration in enhancing learning efficiency and supporting personalized learning (Huang et al. 2021). For instance, the integration of AI applications in real-time question answering (Fang et al. 2023) and homework grading (Duan et al.