A Framework for AI Co-Creation in Pedagogy
Dr. Anjali Rajan Puthiyedath
Lead Teacher,English | Apple Distinguished Educator | Apple Professional Learning Specialist
As artificial intelligence (AI) increasingly becomes a part of everyday life, educators must consider pedagogical approaches and student learning when incorporating AI into the classroom. Integrating AI into education requires a deep understanding of teaching and learning theories to ensure meaningful and impactful experiences for students. Edtech frameworks, such as TPACK, SAMR, Bloom's Taxonomy, and the Universal Design for Learning (UDL), have guided the meaningful integration of technology into education. Similarly, AI integration must be grounded in learning theories and well-established, research-based pedagogical approaches.
AI-CoACT - A Framework for AI Co-Creation in Pedagogy
AI-CoACT is a TPACK-inspired comprehensive framework that consists of four interconnected components: Awareness, Integration, Collaboration, and Transformation. These components are designed to guide educators and learners in integrating AI co-creation into teaching and learning processes. The AI-CoACT framework draws inspiration from established EdTech frameworks such as TPACK, SAMR, and Bloom's Taxonomy, and aims to provide a flexible and adaptable roadmap for embracing AI's potential in education.
Awareness (A)
The first stage in the AI-CoACT framework focuses on building an understanding of AI technologies, their potential applications in education, and the ethical considerations involved. Educators and learners should develop a foundational knowledge of AI tools, their functions, and their limitations to make informed decisions about their use in pedagogical contexts.
Key activities in the Awareness stage:
The Awareness component of the AI-CoACT framework, which integrates various learning theories and research, emphasizes the critical role of human expertise in effectively integrating AI into education.
Educators and learners, drawing on their unique insights and experiences, play a vital role in the successful adoption of AI technologies in the classroom.
When exploring the potential of AI tools in their subject areas, educators can draw on their pedagogical expertise and experience to discern their relevance and applicability in real-world educational contexts.
For instance, when exploring the potential of AI tools in their subject areas, educators can draw on their pedagogical expertise and experience to discern their relevance and applicability in real-world educational contexts. By incorporating practical examples and situations, educators can demonstrate the value of AI technologies in enhancing teaching and learning experiences. For example, an experienced teacher might introduce AI-driven adaptive learning platforms to personalize lesson plans for students with diverse learning needs, ensuring that each student receives appropriate support and guidance.
Theoretical underpinnings, such as activity theory, provide a framework for understanding the complex interplay of human activity, consciousness, and the surrounding environment in the learning process. By adopting a socio-cultural and socio-historical lens, educators can design learning environments that replicate the activity structures, tools, and sign systems that learners encounter in real-world situations.
In the Awareness stage, educators and learners can explore the ethical implications of AI technologies, informed by their sociocultural contexts, to cultivate a responsible and informed approach to AI integration.
The?Awareness component of the AI-CoACT framework recognizes the importance of human expertise in the effective integration of AI in education.
Educators?can create meaningful learning experiences?by blending theory and practice while staying grounded in the realities of their educational contexts.
2. Integration (I)
Once educators and learners have developed a solid understanding of AI, the Integration stage focuses on incorporating AI tools into existing teaching and learning processes. This stage involves selecting the most appropriate AI tools and adapting them to suit the specific needs of learners and the curriculum.
Suggested activities in the Integration stage:
The Integration facet of the AI-CoACT framework is crucial for smoothly integrating AI resources into the current teaching and learning environments.
Educators are tasked with choosing relevant AI tools, modifying them to suit the distinct needs of their students and curriculum, and ensuring congruence with learning goals and outcomes. This stage utilizes various methodologies and teaching approaches, such as differentiated instruction, inquiry-based learning, and problem-based learning, to guide the successful integration of AI resources into educational practices.
Differentiated instruction takes on special significance in the context of AI integration. By utilizing AI tools, educators can deliver personalized learning experiences that address the varied needs and interests of their students. For instance, AI-enhanced adaptive learning platforms can dynamically tweak the pace, difficulty level, and content to align with each student's individual abilities and learning?progression. This integration enables educators to establish inclusive learning settings where students can flourish and maximize their potential.
Inquiry-based learning, another key teaching approach, dovetails with the Integration stage by stimulating students to explore, investigate, and find answers to their questions. AI tools act as invaluable aids in this process, allowing students to conduct research, analyze data, and extract meaningful insights. AI-fortified search engines and natural language processing tools enable learners to delve into their areas of interest, cultivating critical thinking, problem-solving, and information literacy skills.
Similarly, the integration of AI tools in problem-based learning equips students with the necessary resources to identify, analyze, and solve complex problems. AI-driven simulation software, for example, generates virtual environments where students can tackle authentic, real-world challenges and develop practical solutions. This integration augments students' analytical abilities, teamwork skills, and creativity, while also preparing them for the requirements of an AI-influenced future.
By tying the Integration component of the AI-CoACT framework with differentiated instruction, inquiry-based learning, and problem-based learning, educators can leverage the potential of AI tools to enhance teaching and learning experiences. The mindful integration of AI in these methodologies allows educators to craft engaging, personalized, and significant learning opportunities for their students. Furthermore, by incorporating AI tools during the Integration stage, students develop vital 21st-century skills, such as critical thinking, communication, collaboration, and digital literacy, furnishing them with the required competencies to succeed in an increasingly AI-dominated world.
The Intersection of Awareness and Integration?
Consider a teacher who has cultivated an understanding of AI-guided language processing tools during the Awareness stage. During the Integration stage, this teacher might opt to incorporate a language-processing AI tool into their English language classroom. They modify the tool to offer personalized language exercises for students, customized to their individual needs and language proficiency levels.
The intersection of the Integration and Awareness elements within the AI-CoACT framework is a pivotal juncture that links the fundamental comprehension of AI technologies with their practical application in educational settings. This convergence exemplifies the dynamic interplay between consciousness and action, theory and application, as educators orchestrate the integration of AI utilities into their teaching and learning methodologies.
As educators engage with the overlap of Integration and Awareness, they employ their newly acquired understanding of AI technologies and potential uses. They initiate the selection and modification of AI tools that align with their syllabus demands, learning objectives, and the specific needs of their students. This integration process is guided by the awareness accrued in the previous stage, guaranteeing that the application of AI tools is deliberate and in line with pedagogical ambitions.
Practical examples illuminate the importance of this overlap. Consider a teacher who has cultivated an understanding of AI-guided language processing tools during the Awareness stage. During the Integration stage, this teacher might opt to incorporate a language-processing AI tool into their English language classroom. They modify the tool to offer personalized language exercises for students, customized to their individual needs and language proficiency levels. Through this integration, the teacher utilizes the potential of AI to improve language learning, capitalizing on the theoretical awareness developed in the prior stage.
The overlap of Integration and Awareness also underscores the ongoing nature of the framework. As educators incorporate AI tools, they continually broaden their awareness and understanding. They reflect on the effectiveness of the tools, ponder ethical implications, and pursue professional development opportunities to stay updated about the evolving AI landscape. This iterative procedure reinforces the interconnectedness of the elements within the AI-CoACT framework, highlighting the importance of a continuous loop of awareness and integration in pedagogical practices.
The integration of AI and awareness within the AI-CoACT framework resonates with recognized educational theories such as constructivism and transformative learning.
Educators who endorse constructivist principles appreciate the merit of active, experiential learning opportunities. By incorporating AI tools, they create scenarios for students to formulate knowledge, explore concepts, and participate in authentic problem-solving activities. Conversely, the transformative learning perspective emphasizes the significance of critical reflection and the transformation of beliefs and assumptions. Educators functioning within the Integration and Awareness overlap continuously reflect on their practices, adapt their strategies, and question their preconceived ideas about the role of AI in education.
The intersection of the Integration and Awareness elements in the AI-CoACT framework acts as a vital crossroad where theoretical consciousness is transmuted into practical application. Educators employ their understanding of AI technologies to deliberately select, modify, and incorporate AI tools into their teaching and learning methodologies. This overlap emphasizes the dynamic interplay between consciousness and action, providing a link between theoretical knowledge and the practical implementation of AI in educational settings. As educators transition from the awareness to the integration stage, they can effectively harness the potential of AI tools to enhance teaching and learning experiences, ensuring a smooth integration that aligns with pedagogical objectives and the specific needs of their students.
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Collaboration (C)
The Collaboration stage emphasizes the joint efforts of educators, learners, and AI tools in co-creating knowledge, solutions, and learning experiences. In this stage, the focus is on fostering a collaborative learning environment where both humans and AI systems work together to achieve common goals.
Suggested activities in the Collaboration stage:
The Collaboration element within the AI-CoACT structure emphasizes the importance of cultivating a cooperative learning atmosphere where teachers, students, and AI systems work together towards mutual objectives.
This juncture signifies the merging of human and artificial intelligence, fostering a lively and interactive educational experience. It is within this space that the framework resonates with the principles of self-guided learning, encouraging collective problem-solving, brainstorming, and the joint creation of knowledge within various sociocultural environments.
In the Collaboration element, educators orchestrate learning tasks that stimulate active involvement and engagement among students, teachers, and AI tools. For instance, cooperative projects requiring students to work in unison using AI utilities to scrutinize data, formulate solutions, or generate innovative projects encourage collective problem-solving and critical thinking abilities. In this process, the educator's role transitions from being the sole knowledge provider to a facilitator and co-learner, steering students in their exploration and discovery.
Practical examples illuminate the real-world application of the Collaboration element. Consider a group of students participating in a project-based learning task focused on environmental sustainability. Collaborating with an AI-guided environmental monitoring system, students gather real-time data and work with their peers to analyze and interpret the information. The AI utility provides valuable insights, facilitates discussions, and elevates the overall learning experience by providing instantaneous feedback and directing students towards informed decision-making.
The Collaboration element is rooted in self-guided learning principles, which acknowledge the significance of students taking control of their learning journey. Within this structure, students are encouraged to actively partake in co-creating knowledge, solutions, and learning experiences. By engaging in collective problem-solving and brainstorming with AI, students refine their critical thinking skills, improve their teamwork abilities, and strengthen their communication and collaboration skills.
Additionally, the Collaboration element acknowledges the role of sociocultural contexts in shaping learning experiences. It highlights the influence of cultural diversity, social interaction, and community expectations in the joint creation of knowledge. By incorporating AI tools within a sociocultural structure, educators can endorse culturally pertinent pedagogy, respect diverse perspectives, and establish inclusive learning environments.
The Collaboration element of the AI-CoACT structure underscores the significance of cultivating a cooperative learning atmosphere where teachers, students, and AI systems work towards mutual objectives. By aligning with self-guided learning principles, the framework promotes collective problem-solving, brainstorming, and joint knowledge creation within various sociocultural environments. Through collaboration, students become active contributors to their learning, interacting with AI tools and their peers to refine critical thinking skills, encourage teamwork, and deepen their understanding of the subject matter. By embracing the Collaboration element, educators can utilize the potential of AI to generate transformative learning experiences that prepare students for an increasingly interconnected and collaborative world.
The Intersection of Awareness(A) and Collaboration (C)
The intersection of Collaboration and Awareness provides a compelling juncture where the understanding of artificial intelligence (AI) technologies converges with cooperative efforts among educators, learners, and AI systems.
In the context of the AI-CoACT framework, the intersection of Collaboration and Awareness provides a compelling juncture where the understanding of artificial intelligence (AI) technologies converges with cooperative efforts among educators, learners, and AI systems. This intersection signifies a dynamic fusion of knowledge and collective action, emphasizing the importance of cooperative engagements underpinned by an informed understanding of AI's potential and limitations.
Consider, for example, an educator who, upon gaining a comprehensive understanding of AI-driven data analytics tools, decides to incorporate these tools into a student group project. The outcome is a dynamic classroom scenario where learners engage with AI as an integral part of their learning process. Here, the educator functions as a facilitator, guiding learners in their exploration of AI and fostering an environment conducive to collaborative learning.
The intersection of Collaboration and Awareness also aligns with the principles of constructivist learning theory, which emphasizes the active construction of knowledge through social interaction and practical experience. As learners and educators collaborate with AI tools, they actively construct knowledge, transform information into insights, and become innovators in their own right.
Furthermore, this intersection highlights the need for critical thinking and ethical considerations in the integration of AI in education. As AI tools become integral to collaborative learning environments, the Awareness component underscores the need for conscious consideration of potential ethical challenges, such as data privacy and algorithmic bias. This intersection hence emphasizes the importance of continuous learning, reflection, and ethical mindfulness in the context of AI integration.
In summary, the intersection of Collaboration and Awareness within the AI-CoACT framework serves as a vibrant crossroads where knowledge and collaborative action meet. It underscores the importance of an informed, ethical, and collaborative approach to AI integration in education, paving the way for enriched learning experiences and the cultivation of 21st-century skills.
Transformation (T)
The notion of disruption readiness is a central part of the Transformation facet. It accepts that technological advancements are constantly reshaping traditional educational methods and calls for a forward-thinking approach to adopt these changes.
The final stage of the AI-CoACT framework centres on assessing the impact of AI co-creation on teaching and learning and refining the process accordingly. This stage involves continuously evaluating the effectiveness of AI integration, identifying areas of improvement, and adapting the approach to maximize the benefits of AI co-creation in education.
Suggested activities in the Transformation stage:
The Transformation facet within the AI-CoACT model is crucial in guaranteeing the persistent appraisal, introspection, and modification of AI's role in education. It underlines the necessity for disruption preparedness, empowering teachers and educational institutions to accommodate shifts in technology and pedagogy. Moreover, it emphasizes future readiness, making sure students acquire the abilities and competencies required to excel in an AI-oriented world.
The Transformation facet appreciates the necessity for teachers to consistently scrutinize and evaluate the efficiency of AI's incorporation into education. This involves the accumulation and examination of data concerning the effects of AI utilities on educational results, along with gathering insights from teachers and students about their experiences. Through this appraisal process, educators can discern areas for enhancement, identify obstacles, and make data-driven decisions about refining the AI co-creation process.
The notion of disruption readiness is a central part of the Transformation facet. It accepts that technological advancements are constantly reshaping traditional educational methods and calls for a forward-thinking approach to adopt these changes. Teachers and institutions need to stay informed about emergent AI technologies, pedagogical breakthroughs, and shifting educational demands to effectively incorporate AI into their teaching methodologies. This readiness necessitates opportunities for professional growth, teamwork with specialists and colleagues, and a mentality that welcomes change and innovation.
The Transformation aspect underscores the significance of future readiness, which entails equipping learners with the skills, competencies, and mentality needed for an AI-driven world. As AI technologies become more ingrained in various societal aspects, learners must cultivate critical and creative thinking skills, digital literacy, adaptability, and a solid ethical foundation. Teachers have a critical role in fostering these future-ready competencies by crafting learning experiences that utilize AI tools, encourage profound learning, and stimulate the development of 21st-century skills.
In summary, the Transformation facet of the AI-CoACT model is crucial for guaranteeing the persistent appraisal, introspection, and modification of AI's role in education. It stresses disruption preparedness to accommodate technological advancements, and future readiness to provide learners with the needed skills and competencies and utilizes educational theories and models to support this process. By engaging in the constant appraisal, introspection, and modification, educators can maximize the advantages of AI co-creation in education, stimulate innovation, and prepare learners for a future shaped by AI technologies.
The overlap of Awareness, Collaboration, Integration, and their role in Transformation within the AI-CoACT framework is a dynamic junction where the understanding of AI technologies converges with collaborative efforts and effective implementation, ultimately fueling the transformation of teaching and learning processes.
This intersection underscores the significance of a comprehensive understanding, synergistic collaboration, and informed implementation of AI in education, all underpinned by a robust ethical framework and sound policies.
Awareness sets the foundation by equipping educators and learners with a comprehensive understanding of AI technologies, their potential, limitations, and ethical implications. It involves not only technical knowledge but also an understanding of AI's societal impact and the ethical considerations that come with its use in education.
Collaboration then builds on this Awareness by fostering an environment where educators, learners, and AI tools work together to achieve shared learning objectives. This cooperative interaction enhances the overall learning experience, promoting mutual learning and idea exchange among all participants.
Integration comes into play when educators, leveraging their Awareness and fostering Collaboration, effectively incorporate AI tools into their teaching and learning processes. This involves selecting appropriate AI tools, adapting them to meet learners' unique needs, and ensuring alignment with pedagogical goals and learning outcomes.
The Intersection of these three components then plays a pivotal role in driving Transformation - the continuous evaluation, reflection, and adaptation of AI integration in education. Transformation underscores the need for disruption readiness, as educators and institutions must be prepared to embrace changes in technology and pedagogy and future-readiness, ensuring that learners are equipped with the skills and competencies needed for an AI-driven world.
However, this complex interplay of Awareness, Collaboration, and Integration in the context of Transformation must be guided by robust ethical principles and policies.
As AI technologies become increasingly integrated into education, ethical considerations such as privacy, fairness, transparency, and accountability become paramount. Furthermore, policies need to be in place to guide the responsible use of AI in education, ensuring that AI technologies are used to enhance teaching and learning experiences without compromising learners' rights or exacerbating existing educational disparities.
The intersection of Awareness, Collaboration, and Integration in the context of Transformation within the AI-CoACT framework highlights the dynamic relationship between understanding, cooperative action, and effective implementation of AI in education. It emphasizes the importance of a robust ethical framework and sound policies in guiding this process, ensuring that the integration of AI in education is not only effective but also responsible and equitable.
As artificial intelligence continues to revolutionize education, the community of educators and researchers needs to conduct rigorous, research-informed studies to develop and evaluate the usefulness and impact of AI Integration frameworks. A robust empirical evidence base is needed to validate and refine these pedagogical models, ensuring their alignment with learning theories and effectiveness in fostering meaningful AI integration in the classroom. An ongoing process of inquiry and critical reflection will enable educators to harness the full potential of AI co-creation while maintaining a solid foundation in research-based pedagogical practices.
Educator at University of Nigeria, Nsukka
10 个月This is excellent and explicit
Directeur Photo - Dévelopeur en Langage du Cinéma
1 年That’s the way to go Lissa. Lets talk soon.
Bitr?dande rektor p? Karsby International School
1 年Thank you Anjali, really interesting reading!
Lead Teacher,English | Apple Distinguished Educator | Apple Professional Learning Specialist
1 年Updated https://www.dhirubhai.net/pulse/framework-ai-co-creation-pedagogy-dr-anjali-rajan-puthiyedath
Digital Learning Consultant | mrcoby.com | The EduTec Alliance | Apple Professional Learning Specialist | Former educator and leader | MEd Technology | views are my own
1 年Really love this articulation Anjali ??