In the picture book Seven Blind Mice (Young, 1992), each mouse investigates a mysterious object that appears by their pond one day. One mouse finds a spear, another a wall, a third a rope. Each mouse returns to the group, convinced they alone understand what lies before them. It is not until the final mouse steps back and sees the whole elephant that the truth becomes clear.
Recently, we hosted a Summer Institute (https://genaiinhistoryeducation.com/summer-institute/) exploring the use of GenAI as part of history instruction, and as we met our participants, it felt a lot like this story. Much like the mice in the story, educators encountering and navigating GenAI find themselves grasping partial truths. Among our workshop participants, Tina had never touched AI but learned, midsession, that her school would mandate its use in the coming academic year. Sierra’s students were already experimenting with it, leaving her scrambling to catch up. Mandy was caught in the crossfire of a staffroom civil war, unsure how to move without offending colleagues. Jacob had gone all in, building custom GPTs, crafting student frameworks, and proudly declaring his technoromantic stance. John arrived certain he already knew it all. Eileen sat somewhere in the pragmatic middle, using GenAI to create lesson plans but unsure about her feelings regarding its use beyond that. After being introduced to the technoskepticism framework, Carl proudly declared that that was how he felt: skeptical — and terrified.
Each of these teacher participants, like each of the seven mice, came with a partial grasp of what GenAI is and what it might mean for teaching history. Some clung tightly to the part they had “touched” — lesson planning, policy mandates, ethical fears, or boundless enthusiasm. Like in the story, no single perspective captured a complete picture of this rapidly evolving tool. Only by listening to a variety of experiences and engaging with the technology in a variety of ways did the whole scene begin to emerge.
But unlike fictional mice, teachers must make decisions in the moment, often with incomplete information, uneven institutional supports, and contradictory messaging around what GenAI is, should be, or could be. Questions, uncertainties, and insights from our teacher participants resonated with how we are trying to consider possibilities and trajectories not yet imagined: the “what ifs?” The way we frame our engagements with Gen AI matters. It is within and through this problem space (Lury, 2021) of uncertainty and possibility that we have begun to develop and articulate a working concept we call technocuriosity.
Technocuriosity is not a fixed stance or a prescriptive model. It is a conceptual and methodological framework that reflects thoughtful, ethically engaged, speculative experimentation with Gen AI. It recognizes the messiness, tensions, and contradictions that come with balancing expectations and uses of emerging technologies in educational contexts. Drawing inspiration from technoskepticism but also from speculative methods, design thinking, and classroom inquiry, technocuriosity invites educators and researchers to explore with care, critique, and openness, (inter)acting with Gen AI without assuming closure. It is a stance rooted in practice, always provisional, always contested, and always in conversation within and across contexts.
The Technocurious Framework
The voices of these teachers were on our minds when we read “Reorienting EdTech: Reclaiming the Civic Purpose of Educational Computing”by Jordan Allison in the Civics of Technology blog on Jun 8, 2025. In it, Dr. Allison suggested that researchers must engage in “foregrounding the lived realities of students and educators who engage with these technologies every day, and recognising that the impacts of educational computing are never just technical, they are also deeply cultural, political, and moral” (para. 2) A technoromantic view doesn’t critically engage with legitimate ethical concerns and risks (mis)shaping historical thinking in subtle ways. Alternatively, technoskepticism provides a framework as an entry point for educators who are thinking about the impact of AI on teaching and learning (Pleasants et al., 2023). However, while technoskepticism offers vital and critical tools, our perception is that it would be difficult to engage with GenAI platforms in the way Dr. Allison suggested is necessary while assuming this disposition.
As a critical practice, technoskepticism does not preclude engagement; instead, it positions engagement as critique, recognition, and ethical interrogation. Building on the ideas articulated in the technoskeptical framework, we are beginning to explore what it might mean to situate our work along a spectrum of engagement, a fluid space for negotiating nuances relative to specific situations that allows educators to engage with GenAI and other new technologies playfully and fully consider their pitfalls and potentials. We position this practice as being technocurious, a space that invites experimentation, reflection, and ethically aware engagement. Technocuriosity is not a replacement for technoskepticism but an extension of its concerns through a different conceptual and methodological lens. We frame technocuriosity as a form of speculative inquiry that allows the user to inhabit new technologies and offers permission to engage with and in uncertainty, considering the not-yet and the what-if.
We acknowledge that in many ways we are technoskeptics (we are clearly not technoromantics!), but through our research and teaching related to AI, we have found that our dispositions are a little more fluid. While there are many reasons why a technocurious framework is needed, our primary impetus for thinking about and developing this idea further is because we strongly believe that if we (as thoughtful history teachers and researchers) do not think about how GenAI can be applied intentionally and well in the classroom, others who do not have the same level of expertise will, and it may end up being harmful to history instruction.
As mentioned previously, during the workshop, Tina found out her district had purchased a school wide subscription to Google’s Gemini and that the administration would be providing professional development on implementing it in the classroom in the coming semester. As research shows social studies specific professional development is rare (Brugar & Roberts, 2017; Callahan et al., 2016), it seems unlikely that this schoolwide programming would thoughtfully consider best practices for integrating AI with history and social science pedagogies. Beyond this, we heard from many teachers who have found that, even though they try to discourage the use of AI, students are using it. We, ourselves, reported a university student for suspected plagiarism surrounding GenAI use last month. Engaging with GenAI from a technocurious stance may help teachers not only identify GenAI use but also think about ways they can adjust assessments and help students navigate a new technology.
Discussions about technology in education have long oscillated between hesitation and hope. From the early promises of radio and television to the emergence of personal computers and digital platforms, educators have been repeatedly expected to use and take on tools hailed for their transformative promise. Larry Cuban’s (2003) work, however, demonstrated that such technologies often fail to gain traction in teachers’ classrooms as envisaged by developers, not because teachers resist innovation, but because the technologies rarely fit with teachers’ modes of practice and classroom realities.
In contrast, Seymour Papert (1993) envisioned technologies as a catalyst for constructionist learning, stressing experimentation, student engagement, and agency. Meanwhile, cultural critics such as Neil Postman (1985, 1992) and Marshall McLuhan (1967) warned that each new medium/technology reshapes not only what we learn but also how we think. While technocuriosity shifts away from their more cautionary stances, it connects with their insights by taking seriously the symbolic, infrastructural, and cognitive consequences of technology adoption and use.
Technocuriosity takes a posture of thoughtful exploration, not about the interface or novelty of Gen AI but about the deeper issues and complexity it creates in classrooms and education. It is curiosity through and with the technology, asking what becomes possible, thinkable, teachable, or knowable when we treat GenAI as a speculative device or a problem space. We are interested in questions like these: How does it reshape authorship? What epistemic violence and threats does it carry, perpetuate, or mask? Where does it align with disciplinary values within and across discipline, and where does it break from them?
These questions are not born of naïve fascination; they are rooted in situated, speculative critique. Technocuriosity provides a way of working with GenAI tools like ChatGPT that is grounded in pedagogical values and attuned to disciplinary contexts. Technocuriosity builds on Ethan Mollick’s (2024) idea of co-intelligence [a], the notion that AI is not just a tool, but a collaborator that requires human discernment. Yet, like technoskepticism, technocuriosity insists on critical engagement. It does not treat AI as neutral, infallible, or above critique but pays attention to both what it enables and what it displaces, omits, or misrepresents within and through the contexts of its use. This stance is defined by six tenets [b]:
- Situated Liveness: We do not study technologies from a distance, we use them, test them, respond to them in real time. Inquiry happens in media res, in the middle, during the messy moments of engaging with tools like GenAI, even when it fails.
- Speculative Ethics: Rather than just asking, “Does it work?” we also ask, “What could go wrong?” and “What futures are we building when we use this?” We imagine shadow possibilities, unintended effects, and the paths not taken.
- Relational Configuration: Technology does not exist in a vacuum. It exists in schools, systems, and relationships. Technologies are always shaped by and shaping the sociomaterial systems they enter. Researchers map and engage these entanglements, including what things GenAI gets wrong.
- Figural Thinking: We treat technology not just as a tool, but as a figure, something with symbolic weight that both stabilizes and mutates meaning over time. It carries stories about the future, about knowledge, and about what counts as “good” learning. We ask “What do tools like GenAI mean in our classrooms, and how might those meanings shift?”
- Methodological Invention: Methods should be designed responsively to problems and may need to be improvised, hybridized, or invented anew. Technocurious teachers try, adapt, reflect, and sometimes invent new ways of working.
- Reflexive Cocreation: Researchers and educators are not outside observers but coconstructors of the role of technology in education. Technocuriosity is dialogic, recursive, and self-implicating, and the teacher is a critical piece of the equation.
Curiosity With Constraints and Moral Duplicity: Access and Responsibility
While technocuriosity stresses speculative experimentation and exploration, we recognize that not all educators or students have equal access, time, or support to systematically engage in sustained inquiries and interactions. We saw this for ourselves at the Summer Institute, where participants using the free version of Chat GPT lost access due to memory and token limits or were unable to upload files. We also saw how some teachers had access to division-provided subscriptions, while others were engaging with the technology for the first time with no division support. Technocuriosity cannot ignore these disparities and systematic inequities facing students, their families, and teachers.
A technocurious stance must also recognize the broader material consequences of our engagement with Gen AI. Specifically, technocurious educators and researchers must consider the environmental costs in terms of energy consumption, water age, and carbon emissions. These considerations give way to the struggle of weighing the pedagogical and civic possibilities of Gen AI against its planetary cost. In a recent article, Ezra Klein (2025) detailed his own increased use of GenAI while also recognizing the ecological impacts of this use. We share this discomfort and moral duplicity. Within a technocurious framework, we know we cannot resolve this tension/contradiction, but live with it while continuing to experiment, staying alert, and recognizing its consequences as the terrain shifts around us.
Similarities and Differences Between Technoskepticism and Technocuriosity
While technoskepticism and technocuriosity might seem like contrasting dispositions, they share key commitments that anchor thoughtful engagement with emerging technologies. In truth, technocuriosity cannot exist without the foundation laid by technoskepticism. Both frameworks reject the idea of neutrality. Technoskepticism foregrounds the power-laden nature of tech systems, while technocuriosity builds on this insight by insisting that technologies are not only configured by humans but also act as cocreators of possible worlds. Each stance calls for critical engagement: technoskepticism advocates for interrogating power structures and systemic inequities, and technocuriosity encourages sustained inquiry into the infrastructures, imaginaries, and embedded biases of AI tools.
Civic agency remains central to both, though technocuriosity leans toward situated experimentation, encouraging educators to engage in iterative processes and cocreation with the tools under evaluation. Both also take seriously the temporal dimensions of technological change: technoskepticism asks us to remember, to draw historical lines; technocuriosity asks us to imagine interactional potentials and shadow futures that technologies might invite or foreclose.
However, these two frameworks diverge in tone, intent, and future practice. In our view, technoskepticism is reflective and cautionary. It focuses on the harms technologies can cause and the ways they centralize power, perpetuate bias, or erode civic trust and is anchored in rhetorical critique. Ultimately, it urges educators to question and resist technologies that conflict with ethical or educational values. Technoskepticism is vital and powerful in reminding educators and others that saying “no” is a valid and appropriate pedagogical act. In contrast, technocuriosity pairs the same critique with speculation, wondering what might become. It draws from media studies, speculative design, science and technology studies, and even amphibious sociology to imagine new roles and relationships between humans and machines, asking what might happen if we explore technologies from within.
Within this exploration, it does not encourage the user to accept technologies such as GenAI as they currently exist, but to press, prototype, and reimagine their uses and affordances (good and bad). In this sense, technocuriosity is a methodological practice rooted in iteration, improvisation, and situated experimentation that insists that we must inhabit technologies — tinker, play, and cocreate — to understand them. Where technoskepticism can serve as a brake to help slow us down and notice power, technocuriosity can steer us toward what might be possible when those powers are contested, redirected, or repurposed.
A key strength of the technoskepticism framework is its emphasis on critical questioning. These questions are designed to be deployed in ways that help illuminate particular values and power structures. We agree with this stance and see technocuriosity as building on it. Where technoskepticism often illuminates resistance and refusal, technocuriosity invites exploration and examination with caution and creativity. We developed a set of questions that are parallel to the technoskeptical questions (Figure 1); these questions are still critical but also designed to create a space for situated use, speculative thinking, and experimentation. These technocurious questions are not intended to replace technoskepticism and, in many cases, could still be seen as technoskeptic operationalized differently. In these additional questions, we sought to expand the possibilities for ways educators and educational researchers might work with Gen AI in real time, generating opportunities to take a different path and utilize different methods of engagement. They serve as potential prompts across a variety of contexts. In our presentation of these questions, our goal is not to suggest a single best path forward but to offer new perspectives — a dual lens — through which educators can both interrogate and engage with Gen AI.
Figure 1
Technoskeptical and Technocurious Questions
Conclusion: Holding Possibility and Complexity Together
Ultimately, the technocurious framework presented here is a call to move beyond a dichotomy. For example, instead of choosing between being all-in or all-out on GenAI, it invites consideration of a spectrum with space for questions, contradictions, creative risks, and ethical reflection. It is a space where both caution and imagination are welcome; where we can hold concerns about bias and misinformation alongside excitement about new ways to support historical inquiry and student learning; where we can be both critical and cautious.
And that brings us back to the mice.
The teachers who joined our Summer Institute did not come because they had it all figured out. They came, like the mice in the story, because something unfamiliar had appeared on the edge of their professional pond, and they were curious. Some arrived cautious while others were conflicted. Some brought enthusiasm and others brought skepticism, but underneath all of that was a shared willingness to explore, ask questions, and learn in community.
Like the final mouse who stepped back and saw the whole elephant, our participants began to realize that understanding the potentials and pitfalls of GenAI in education is not possible through one perspective. It requires blending together a multitude of viewpoints while testing boundaries and creating new knowledge together. That is what technocuriosity makes possible: openness to possibility and a way of seeing the whole.
We view technocuriosity not as a destination but as a beginning: an invitation to think and teach with nuance, to remain open to surprise, and to resist both hype and fear. This framework will continue to evolve as we play with it, stress test it in classrooms, refine its conceptual groundings, and remain in dialogue with educators, researchers, and students who are navigating and mapping GenAI in real time. We share these early reflections and ideas, not as a definitive answer, but as a provocation and an initiating point for generative discussion around research and pedagogy related to GenAI. Like the teachers in our Summer Institute, we are still in the process of figuring out both the framework and GenAI by asking questions, adapting our thinking, playing and speculating, all while seeking to build networks and communities around uncertainty. Though our work is still unfolding, we believe that a technocurious approach of curiosity that is critical, careful, and collective holds potential for educators seeking to navigate rapidly evolving technologies.
End Notes
[a] We acknowledge Ethan Mollick’s (2024) work often stresses co-creation and optimism and many may see him as a technoromantic. Our decision to cite him here emerges from his concept of co-intelligence, the centaur model, and the importance of human discernment as key instantiations of the broader problem space we are navigating and exploring.
[b] These six tenets are “poached” or “borrowed” then reimagined (de Certeau, 1984) from the field of sociology, drawing in particular on the work of Celia Lury as it relates to Inventive Methods (Lury & Wakefield, 2012), Amphibious Sociology (Lury, 2012), and Figures (Lury et al., 2022).
References
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