AI and the Changing Nature of Learning

Artificial intelligence has been developing for decades, but the emergence of tools such as OpenAI marked a significant shift by making natural language interaction widely accessible. For the first time, individuals could engage directly with AI systems through everyday communication, using text to generate ideas, images, and even video.

This development builds on earlier transformations in how people access and participate in information environments—from the expansion of print, to the rise of the web and digital networks, to the widespread use of mobile technologies. Each of these shifts has reshaped how information is created, shared, and understood, increasing both access and participation.

Generative AI extends this trajectory by making the production of content more immediate and widely available, enabling new forms of expression and collaboration. At the same time, it raises important questions about originality, authenticity, documentation, and the ethics of meaning-making in digital environments. It also introduces new challenges related to how individuals interpret and trust information, particularly as AI-generated content—including misinformation, disinformation, and deepfakes—becomes more prevalent and difficult to distinguish from human-created content. As individuals increasingly work with AI to generate and interpret information, the need for thoughtful, reflective, and responsible engagement becomes more critical.

Education and the Need for a Framework

In this context, education plays a critical role in supporting learners to engage with increasingly complex information environments. Beyond learning how to use AI tools, individuals must develop the ability to reflect on their own thinking, evaluate the credibility and implications of information, and participate responsibly in the creation and sharing of knowledge.

Metaliteracy offers a framework for understanding this process, emphasizing learning as an active, reflective, and participatory experience in which individuals engage with information not only as consumers, but also as producers, collaborators, and contributors within dynamic digital environments (Mackey & Jacobson, 2022).

Metaliteracy as a Framework for Learning

Metaliteracy was first introduced as a concept to expand traditional understandings of information literacy in response to the participatory nature of digital environments (Mackey & Jacobson, 2011). Rather than focusing solely on the evaluation of information, metaliteracy recognizes learners as active participants who create, share, and reflect on information in collaborative and networked spaces.

Over time, metaliteracy has evolved into a holistic pedagogical framework for learning (Mackey & Jacobson, 2022). It emphasizes the integration of four domains of learning—affective, behavioral, cognitive, and metacognitive—along with key learner roles, including producer, researcher, participant, and collaborator.

The framework also identifies a set of learner characteristics, such as being reflective, adaptable, informed, and civic-minded. Together, these characteristics support learners in becoming ethically engaged by recognizing their responsibilities in social information environments.

Through this process, individuals develop as metaliterate learners, cultivating a reflective mindset that supports active and intentional participation. Learners not only think critically about information, but also contribute as producers who create, share, and shape knowledge in meaningful ways.

Metaliteracy has been applied across a range of innovative learning environments, including online courses, MOOCs, and global virtual exchanges, demonstrating its adaptability across disciplines and its continued evolution in response to emerging technologies.

Metaliteracy in an AI Context

In AI-mediated environments, the principles of metaliteracy take on new meaning as learners engage directly with systems that generate and shape content. Rather than simply locating or evaluating information, individuals interact with AI as part of an ongoing process of interpretation, creation, and revision.

In this context, learners take on multiple roles. As producers, they generate content in collaboration with AI systems, shaping outputs through prompts, selection, and revision. As researchers, they evaluate the quality, accuracy, and limitations of AI-generated information. As participants and collaborators, they engage in shared digital environments where content is created, circulated, and interpreted by both humans and machines. While AI functions as a tool in this process, it also shapes how ideas are developed and expressed, influencing how learners think, create, and communicate.

Working with AI requires a heightened level of reflection. Learners must consider how their inputs influence outputs, how biases may be embedded in generated content, and how their decisions shape the meaning and impact of what they create and share. Through this process, learners develop a metaperspective on their interactions with AI, becoming more aware of how they plan, prompt, revise, and interpret content. This awareness supports more effective use of AI, including the ability to identify appropriate tools and critically evaluate their outputs.

At the same time, developing as a metaliterate learner involves understanding the broader systems in which AI operates. Learners begin to recognize that AI platforms are shaped by the decisions of organizations and developers, and that these systems reflect particular values, assumptions, and commercial interests. This awareness encourages learners to consider how their use of AI aligns with their own values and responsibilities.

AI-mediated environments also amplify the need for civic-minded and ethically engaged participation. As AI-generated content becomes more prevalent, individuals are not only consumers of information but also contributors to information ecosystems that shape public understanding. Developing a metaliteracy mindset in this context prepares learners to engage with a wide range of evolving environments, not just a single tool or platform. Rather than focusing on discrete skills, this approach emphasizes ongoing reflection, adaptability, and responsible engagement as learners make informed choices about how to use, share, and create content.

Connection to the Toolkit

This toolkit applies these principles through a sequence of four modules and adaptable assignments designed to support learning with AI through a metaliteracy framework. The modules align with the metaliteracy learning goals and guide learners from identity formation to evaluation and production, collaborative participation, and ongoing development as metaliterate learners.

Assignments encourage learners to evaluate AI systems and their outputs while also creating with AI in ethical and responsible ways. Rather than focusing on specific tools, the toolkit emphasizes conceptual understanding and reflective practice, supporting learners in developing as effective participants in AI-mediated environments. Through this process, learners gain insight into their own learning, the distinctions between human and machine contributions, and how these interactions shape information production.

The toolkit is also designed to be open and adaptable, supporting use across disciplines and contexts while encouraging broader participation and civic engagement. It models collaboration not only among educators and learners, but also with AI itself, demonstrating how human intention, critical reflection, and iterative interaction can guide meaningful and responsible use of these technologies.

Selected Resources

These resources provide additional context for understanding how metaliteracy has developed as a framework for learning and how it continues to evolve in response to emerging technologies, including artificial intelligence.

• Allain, N. M., & Mackey, T. P. (Eds.). (2027). AI and Metaliteracy: Empowering learners for the Generative Revolution. Bloomsbury.
• Griesbaum, J., Dreisiebner, S., Mackey, T. P., Jacobson, T. E., Thadathil, T., Bhattacharya, S., & Adilović, E. (2023). Teaching Internationally, Learning Collaboratively: Intercultural Perspectives on Information Literacy and Metaliteracy (IPILM). Communications in Information Literacy, 17 (1), 260–278. https://doi.org/10.15760/comminfolit.2023.17.1.4
• Jacobson, T., & Mackey, T. (2025). 2025 Metaliteracy Goals and Learning Objectives. Metaliteracy. https://metaliteracy.org/learning-objectives/metaliteracy-goals-and-learning-objectives-updated-2025/
• Mackey, T., & Jacobson, T. (2011). Reframing Information Literacy as a Metaliteracy. College & Research Libraries, 72(1), 62-78. doi: https://doi.org/10.5860/crl-76r1
• Mackey, T. P., and Jacobson, T.E.. Metaliteracy in a Connected World: Developing Learners as Producers. Chicago: ALA Neal-Schuman, 2022.
• Mackey, T. P., & Aird, S. M. (2021). Integrating Metaliteracy into the Design of a Collaborative Online International Learning (COIL) Course in Digital Storytelling. Open Praxis, 13(4), pp. 397–403. DOI: 10.55982/openpraxis.13.4.442
• O’Brien, K. L., Forte, M., Mackey, T. P., & Jacobson, T. E. (2017). Metaliteracy as a pedagogical framework for learner-centered design in three MOOC platforms: Connectivist, Coursera, and Canvas. Open Praxis, 9(3), 267–286. DOI: 10.5944/openpraxis.9.3.553
• Wikipedia contributors. (2025, December 14). Metaliteracy. In Wikipedia, The Free Encyclopedia. Retrieved 15:31, April 12, 2026, from https://en.wikipedia.org/w/index.php?title=Metaliteracy&oldid=1327466876