When we remove formal education and its trappings, what might teaching and learning look like in the (postdigital) wild?

This 15-minute provocation positions informal lifelong learning as a potential rewilding of education. Echoing Biesta (2017), the point of education is to "learn something, ... learn it for particular reasons, and ... learn it from someone” (pp. 27-28). What might this look like outside of the increasingly algorithmic structures of higher education? If as Cormier (2024) suggests, in times of digital abundance the community is the curriculum, what would be needed to support a learning society in which each of us is always a potential learner and teacher?

This conceptual presentation draws on theory from my doctoral research, which explores the value of informal lifelong learning practices of adults in conditions of digital ubiquity. I want to set aside the formal codification of higher education - qualification levels, rankings, measured outcomes, all the instruments through which education systems quantify and abstract learning itself.

Instead I consider the informal-yet-intentional forms of learning in which we engage to learn throughout life in the (post)digital age: YouTube tutorials, mentoring relationships, online communities of interest, writing workshops. They cannot easily be quantified. They frequently subvert the master-pupil dynamic of organised schooling. They inevitably straddle both digital and embodied worlds, and always hold the presence or echoes of others with whom to learn and teach.

Alheit, P. (2022). ‘Biographical learning’ reloaded. Adult Education Critical Issues, 2(1), 7–19. https://doi.org/10.12681/aeci.30008

Biesta, G. J. J. (2021). Holding oneself in the world: Is there a need for good egoism? Meeting the challenges of existential threats through educational innovation. Routledge. 115–126.

Biesta, G. J. J. (2017). The Rediscovery of Teaching (1st ed.). Routledge. https://doi.org/10.4324/9781315617497

Cormier, D. (2024). Learning in a time of abundance: The community is the curriculum. Johns Hopkins University Press.

Jackson, N. (2011). Learning for a complex world: A lifewide concept of learning, education and personal development. Authorhouse.

Jarvis, P. (2007). Globalization, lifelong learning and the learning society. Routledge.

Watters, A. (2025, February 14). Discrimination engines. Second Breakfast. https://2ndbreakfast.audreywatters.com/personalization-ruptured-were-all-in-this-together/

Is artificial intelligence a form of black magic (Lao, 2020)? Are we dragon riders taming a technological beast (Bozkurt, 2024)? Rich metaphors abound within the growing body of research surrounding AI literacy, and there is no better place to look for them than within the rapidly proliferating number of AI literacy frameworks.

Conceptual metaphors and AI literacy frameworks, which outline “the essential abilities that people need to live, learn and work in our digital world through AI-driven technologies” (Ng et al., 2021), complement each other by organizing our perception of this complex topic and coordinating our actions in response. Both are dynamic, evolving as our understanding of AI and literacy changes. However, they share common challenges: if too simple, they are deemed too essentialist or limiting; if too complex, they lack utility (Lakoff & Johnson, 2008; Petrie & Oshlag, 1993).

Through idiographic metaphor analysis (Redden, 2017), we coded the metaphors in eighteen AI literacy frameworks to uncover the underlying metaphorical relationships between AI, students, and teachers. We highlight the dominant metaphors for each actor: AI-as-tool-transformer-ubiquitary-artefact-threat; student-as-analyst-citizen-creator; and teacher-as-designer-guide. We then discuss the natural connections between these metaphors and several tensions that arise. Among these we include the need to converge diverse models of AI literacy, discordance between the metaphorical view of literacy as power and/or adaption within the frameworks (Scribner, 1984), and a misfocus on individual literacy at the expense of the collective.

At the end of the session, we discuss directions for AI literacy that address these tensions and consider our individual and collective capacity in higher education to shape or reject an AI-saturated future.

References

Bozkurt, A. (2024). Why generative AI literacy, why now and why it matters in the educational landscape?: Kings, queens and GenAI dragons. Open Praxis, 16(3), 283-290.

Lakoff, G., & Johnson, M. (2008). Metaphors we live by. University of Chicago Press.

Lao, N. (2020). Reorienting machine learning education towards tinkerers and ML-engaged citizens (Doctoral dissertation, Massachusetts Institute of Technology).

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041.

Petrie, H. G., & Oshlag, R. S. (1993). Metaphor and learning. Metaphor and Thought, Second Edition. Cambridge University Press.

Redden, S. M. (2017). Metaphor analysis. The international encyclopedia of communication research methods, 1-9.

Scribner, S. (1984). Literacy in three metaphors. American journal of education, 93(1), 6-21.

The growing presence of artificial intelligence (AI) is becoming difficult to deny. While some scholars and practitioners remain apprehensive, debating the benefits and drawbacks of technological innovation, others are beginning to embrace AI-enhanced tools. However, the rapid spread of AI poses profound challenges to traditional notions of creativity and learning (Hamed et al., 2024; Henriksen et al., 2024; Kosslyn, 2024). Grounded in frameworks of critical AI literacy (Velander et al., 2024) and theories of creativity as a process-oriented rather than product-focused experience (Blanche, 2007), this report introduces a conceptual framework for reclaiming creativity and human agency in post-AI higher education. It argues that fostering critical engagement, reflective practice, and problem-solving can promote meaningful learner engagement.

Central to this framework is the need to clearly define the role AI plays and its limitations in higher education. By building on Kosslyn’s (2024) idea of AI as a “cognitive amplifier,” this framework reconceptualises AI as a technology that enhances human strengths and compensates for our limitations without displacing uniquely human qualities. The concept of “critical creativity” (Titchen and McCormack, 2010) underpins this perspective, providing a foundation for integrating reflective and imaginative methodologies into educational practices that prioritise process over results. This framework positions learners as active participants, critically engaging with AI as a collaborative partner in co-creating knowledge and generating ideas. However, as Kosslyn (2024) notes, AI lacks volition or agency, and therefore cannot share responsibility in the same way a human collaborator can. Engaging critically with AI requires mastering a range of mental skills, including attention to detail, language comprehension and expression, and ethical discernment.

While concerns over the automation of human tasks and the commodification of creativity are valid, they reflect a narrow focus that limits our ability to address the broader implications of AI in higher education. This framework advocates for a shift in thinking: what if we prioritise the process of learning and creating rather than the outcomes? Instead of competing with AI or resisting its presence, educators can adopt emerging frameworks that empower learners to develop uniquely human skills. By reclaiming creativity and human agency in the post-AI era, this approach envisions a future where learners navigate and shape their world with imagination, ethical awareness, and a sense of purpose. Ultimately, this conceptual framework ensures that AI serves as a catalyst for human flourishing rather than a force of dehumanisation in education.

References:

Blanche, E. I. (2007). The Expression of Creativity through Occupation. Journal of Occupational Science, 14(1), 21–29. https://doi-org.dcu.idm.oclc.org/10.1080/14427591.2007.9686580

Hamed, A.A, Zachara-Szymanska, M., & Wu, X. (2024). Safeguarding Authenticity for Mitigating the Harms of Generative AI: Issues, Research Agenda, and Policies for Detection, Fact-Checking, and Ethical AI. iScience, 27(2), 108782. https://doi.org/10.1016/j.isci.2024.108782

Henriksen, D., Mishra, P., & Stern, R. (2024). Creative Learning for Sustainability in a World of AI: Action, Mindset, Values. Sustainability, 16(11), 4451. https://doi.org/10.3390/su16114451

Kosslyn, S.M. (2024). Learning to Flourish in the Age of AI (1st ed.). Routledge. https://doi-org.dcu.idm.oclc.org/10.4324/9781032686653

Titchen, A., & McCormack, B. (2010). Dancing with stones: critical creativity as methodology for human flourishing. Educational Action Research, 18(4), 531–554. https://doi-org.dcu.idm.oclc.org/10.1080/09650792.2010.524826

Velander, J., Otero, N., Milrad, M. (2024). What is Critical (about) AI Literacy? Exploring Conceptualizations Present in AI Literacy Discourse. In: Buch, A., Lindberg, Y., Cerratto Pargman, T. (eds) Framing Futures in Postdigital Education. Postdigital Science and Education . Springer, Cham. https://doi-org.dcu.idm.oclc.org/10.1007/978-3-031-58622-4_8

The US band Rage Against the Machine's epnymously titled first album featured the iconic photograph of Vietnamese monk Thích Quảng Đức enaged in an act of self-immolation. This session will be a discussion of how we can delve into the details of Buddhist psychological theory (as in the Abhidhamma texts) which repsent a complex account of consciousness, with some purpose. These texts offer an orientation to the analysis of cosnciousness which seeks to ultiemately forgeround ethics. What can we learn as we wrangle with the shuffling simulcra of thought that GAI offers?

This session will be based around some short pre-shared readings (shared before the event) and participants will work as a team to see iif we can (non-artificaly) generate a short blog post which articulates the Buddhist psycholoigcal ethics onto the ethical lacunae of generative AI.

Higher education is facing imminent and significant crises in a number of countries, including Canada, Australia, and the UK, as a result of chronic neglect by governments, declining public trust and interest in the sector, and populist and xenophobic policies targeting marginalised international students. With higher education institutions (HEIs) in Canada, the UK and Australia all facing the real prospect that not just individual institutions, but whole sectors may collapse in the very near future, there are increasingly extreme measures being taken in attempts to reach fiscal sustainability. Leaders are trying to balance the damaging impact of short-term fiscal strategies (e.g. cutting staff and programs) against maintaining enough of the core functionality to be able to rebuild in the future (Hale et al., 2006). In the scramble to find efficiencies and transform processes, higher education institutions (HEIs) often turn to consultants with thoughts of “digital transformation” as a ready-made solution, examining all processes for ways to use technology to increase productivity, reduce the time needed for tasks, and often ultimately to reduce the size of the workforce (Blackburn et al., 2020).

In the past, the potential for achieving cost savings through digital transformation have been modest, and were rarely a quick fix, requiring capital, human and cultural investments to see dividends (Rof, Bikfalvi & Marques, 2020). In the current zeitgeist however, a combination of near-possibilities and magical thinking related to generative AI’s transformational capabilities may trigger poorly controlled changes in higher education that may be undesirable and irreversible. While there are competing narratives of AI as a replacement for human work vs an augmentation or assistant for humans, in times of crisis humans tend to make decisions that address the acute need, but which may be less strategically sound. In effect, their decisions may ‘eat the future’ (Usher, 2024). There are emerging examples of AI agents replacing human functions in clerical and support tasks across HE, as there are for other industries, but also in teaching as budgets for part-time instructors and teaching assistants disappear, and research as governments demand more return on research investments (e.g. Bates et al., 2020).

It is possible that the critical and thoughtful embedding of AI across our work may lead to better outcomes for students and staff in the medium to long term. However, when survival is the core driver of decisions and normal checks and balances are suspended, the long-term implications may not be weighed as carefully as they should, and the potential for the further enshittification of higher education seems high (Doctorow, 2022).

This session will discuss the implications of seeing AI as a potential saviour of higher education systems in distress, and the need for balancing short-term gains and longer-term system change to achieve a new form of sustainability.

References:

Bates, T., Cobo, C., Marino, O., and Wheeler, S. (2020). Can artificial intelligence transform higher education? International Journal of Educational Technology in Higher Education. 17(42). https://doi.org/10.1186/s41239-020-00218-x

Blackburn, S., LaBerge, L., O’Toole, C., and Schneider, J. (2020). Digital Strategy in a Time of Crisis: Now is the time for bold learning at scale. McKinsey Digital. Online: https://kolnegar.ir/wp-content/uploads/2020/07/Digital-strategy-in-a-time-of-crisis.pdf Accessed: 27 November, 2024.

Doctorow, C. (2022). Social Quitting. Online: https://doctorow.medium.com/social-quitting-1ce85b67b456 Accessed: 28 November 2024.

Hale, J.E., Hale, D.P., and Dulek, R.E. (2006). Decision processes during crisis response: An exploratory investigation. Journal of Managerial Issues, 18(3): 301-320. https://www.jstor.org/stable/40604542

Rof, A., Bikfalvi, A., and Marques, P. (2020). Digital Transformation for Business Model Innovation in Higher Education: Overcoming the Tensions. Sustainability. 12(12), 4980. https://doi.org/10.3390/su12124980

Usher, A. (2024). Eating the future. Higher Education Strategy Associates Blog, 9 September, 2024. Online: https://higheredstrategy.com/eating-the-future/ Accessed: 27 November, 2024.