The Transformative Learner

Death-Rebirth, Curiosity, and Identity

Shadow Rebbe/Benjamin Gabbai is a fellow at the Open Research Institute, focusing on the intersection of education, epistemics, and childrearing.

Abstract

Most models of learning use some version of the storehouse metaphor: learning is understood primarily as accumulation. That model breaks down when learning requires not addition, but the ‘death’ of an old frame and the emergence of a better one. Drawing on Cognitive Transformation Theory, I examine two obstacles to such learning: knowledge shields and frame blindness. I argue that the real question is not how to induce transformation in favorable conditions, but how to form a learner who can increasingly undergo transformative learning without them. That argument leads to a portrait of the transformative learner, whose revolutionary curiosity is stabilized by identity into character. Everything said up to this point forces a corresponding educational conclusion: foundational education should be judged by the learner’s future capacity for transformative learning.

The Storehouse Model

The typical model used to think about learning is described by Klein and Baxter (2009) as the storehouse model. In their words:

“It assumes that the learner is missing some critical form of knowledge—factual information or procedures. The learner or the instructor defines what knowledge is missing. Together, they add this knowledge via a course, a practice regimen, or through simple study. Instructors provide feedback to the learner. Then, they test whether the new knowledge was successfully added to the storehouse.”

A richer version of the storehouse metaphor¹ includes not only stored contents, but also the mind’s operations on those contents: memory, recall speed, procedural fluency, and other forms of processing power. Learning, in this view, is both accumulation and the strengthening of the mind’s capacity to handle what it knows. This is a highly intuitive picture of how minds improve.

This commonsensical metaphor of the storehouse fits with many learning experiences we encounter in life, and in those cases is adequate. As Klein and Baxter themselves draw an analogy to Kuhn’s model of science. And you can compare learning with the storehouse model roughly to the work inside a paradigm that Kuhn (1970) describes ‘normal science’ to be.

But the storehouse metaphor is deeply inadequate in describing many types of learning, including the most significant ones. This is because the model does not include many important affordances.

• Interactivity of knowledge: The storehouse metaphor leads the mind to consider units of knowledge to be discrete. It does not make salient the relationality between different patterns of thought, especially how the arrangement of concepts within a conceptual network can determine radically different outcomes in understanding and receptivity to new information.

• Subtractive knowledge: The storehouse model makes it seem like abandoning knowledge, or unlearning, has a maximal utility of negating a mistake, and does not acknowledge that negating knowledge can lead to positive gains in understanding, and certainly does not recognize the possibility of transformative effects.

• Abstraction and Deconstruction: The storehouse model lacks the capacity to express how many pieces of information can be condensed into one abstraction, nor how an abstraction can be deconstructed into smaller pieces.

• Perceptual Growth: The storehouse model does not invite the mind to consider how pieces of knowledge can alter the capacity for the assimilation of future knowledge.

• Environment: The storehouse model also fails to capture the dynamic relation between learner and environment. As the learner changes, both the quantity of what can be learned and the kinds of things that can become intelligible or extractable from the environment change as well.

These considerations are not impossible within this model, but they involve serious friction.

An Alternative to the Scientist Metaphor

Cognitive Transformation Theory, as presented by Klein and Baxter, therefore rejects the storehouse model in order to emphasize the revision aspect of conceptual networks² and suggests using a “scientist” metaphor. Klein and Baxter (2009) write:

“Cognitive learning is not simply a matter of adding additional beliefs into the existing mental models. Rather, we have to revise our belief systems and our mental models as experience shows the inadequacy of our current ways of thinking. We discover ways to extend or even reject our existing beliefs in favor of more sophisticated beliefs. The scientist metaphor is much more suited to cognitive learning. This metaphor views a learner as a scientist engaged in making discoveries, wrestling with anomalies, and finding ways to restructure beliefs and mental models…”

I have a few objections to using the scientist metaphor. First of all, consider a person with a storehouse model of learning. By implication this person understands the mind, knowledge and learning to fit that model. For them, a scientist is merely a container of a specialized set of knowledge. Which is to say, for those who do not understand the problematics of the storehouse model, the ‘scientist’ metaphor is uninformative. Hence it fails in the pedagogical task that the metaphor aims to accomplish.

Moreover, while the scientist metaphor saliently captures the idea of experimenting, it drastically fails to evoke the aversive dimension of transformation. Subtractive knowledge, reorganization, and the development of new awareness are all experiences that most people shy from, and for a person with a storehouse model, they seem especially threatening; they appear as a loss of wisdom, a growth in ignorance at worst, and as meaningless at best.

Because of these considerations, I suggest using a death-rebirth metaphor; it better fits the lived structure of the experience. It cannot be subsumed in the storehouse model, the way the scientist metaphor can. Hence, while it may not be immediately understandable for a person who is locked into the storehouse model, at the very least it defends itself from being misinterpreted.

Transformative learning is never a simple swap out of one proposition for another; it is a radical reorganization of the network of concepts that form the mind in a domain. A way of organizing attention, meaning, and expectation breaks down so that a better one can emerge. It is not an overstatement to say that part of the mind has died and is reborn anew. We can label the competing learning metaphors or models storehouse vs. transformative, while using death-rebirth as the metaphor for the lived structure of transformation.

The dramatic aggression of the term is not a mistake either. The threat of transformation, that is, the death-rebirth moment, is typically frightening. Feltovich, Coulson, and Spiro (2001), report the reactions of medical students to the educational procedures aimed at transformative learning:

“A testimony to the degree of discomfort the challenges caused the students was the amount of anger and frustration that was elicited within the experimental procedures.”

But beyond the fear and anger that transformative learning brings, it is also experienced as disorienting and rejuvenating in relation to the importance of the domain to the learner and their inexperience. The joy of the ‘aha!’ is powerful and readers can surely recall moments of ecstasy in which confusion was reconstructed into a comprehensible pattern.

Knowledge Shields

When discordant information that challenges a current frame or conceptual network enters awareness, typical responses that protect the incumbent from threat are invoked. These epistemological responses are analogous to the colloquial psychoanalytical “defense mechanisms”. To avoid destabilization, the mind protects itself by deploying what Feltovich et al. (1994) call knowledge shields. In the appendix to ‘Learners’ (Mis)Understanding...,’ Feltovich, Coulson, and Spiro (2001) list 23 such shields. Among them are (paraphrased):

• Illegitimate subsumption: this anomaly is a special case of what I already know; I can account for it with my current model. The new concept I am encountering behaves just like the ones I am already familiar with.

• Argument from authority: This new data is simply wrong because authority X has informed me otherwise.

• Impertinent Complexification: I will be able accommodate the new material, because there is more to it than what is present. With more data, it will fit my current model. We just won’t go into the details right now.

They also explain why knowledge shields are so problematic:

“If the application of Knowledge Shields is catch-as-catch can, as our results suggest, then conceptual change should be especially difficult for concepts of the kind we have examined. This is because in this kind of structure there are so many places to hide the effects of discrepant information. For example, there can be no such thing as a critical challenge to some key part of the network because of the multiplicity of influences on belief. This kind of conceptual network provides so many sources of resiliency, that some way can be found by the learner to accommodate the implications of a challenge to credibility. Changing belief probably requires a multi faceted, systematic affront, a process of dismantling and reconstructing a large part of a belief system.”

In other words, trying to dismantle a structure of a person’s conceptual network is very difficult because each concept of the learner is reinforced by others, and any attempt to reshuffle the conceptual network is defended by knowledge shields, which are deployed willy-nilly—anything to keep the structure safe.

Frame Blindness

Even if the problem of knowledge shields were bypassed with instructional design, which would be an exceptional feat, this still only deals with conscious and surfaced resistances to the death and rebirth of the mind that is constitutive of transformative learning. Another, perhaps more severe problem is that the salience landscape, or frame, of the mind shapes what becomes visible in the first place.

A mind’s frame, constructed by the learner via their conceptual network³, makes some aspects of reality salient and others negligible. Transformative learning, as I am using the term, is the pursuit of better frames and the abandonment of poorer ones. It is well-structured attention that is the object of education and learning. The implication of the fact that we are always embodying a frame means that certain features of reality never present themselves, and it is particularly the features that would instigate a call for revision that are typically left in the dark.

Hence, before knowledge shields can even be deployed, there needs to be a way for the anomalous information to surface past the frame blindness⁴.

In the examples discussed by Klein and Baxter (2009) and Feltovich, Coulson, and Spiro (2001), frame blindness is largely a non-problem; the context evaluated is a learner who is being actively taught by an expert. The teacher is able to force the anomaly down the throat of the learner, which evokes the gag of knowledge shields. But the ability to simply ignore the incongruent data is not an option that needs to be addressed.

For various reasons, the assumption of learning involving an active teacher is inadequate in thinking about transformative learning for the present and future state of our contemporary world. For starters, many people today are autodidacts in several domains of their lives. Mediums like YouTube, Substack and various AI bots are used to learn and all of these systems are opt-in; hence incongruent data can be ignored or deflected with knowledge shields. Incongruent data can be avoided by shaping one’s own curriculum in a way to avoid the toil of transformative learning.

Moreover, there are many domains where transformation is highly valuable, but does not even have clear accessible lineages—learning is autodidactic by nature, and authorities that can press do not exist. Finally, and perhaps most importantly, as the scientist metaphor suggested by Klein and Baxter implies, an inquirer into novel fields is a learner, but has no authority to rely on. Hence, any resolution to the problems of transformative learning needs to take into account the challenge of both knowledge shields and frame blindness, and contextualize them in a world where autodidactic learning is the norm.

Institutional Supports for Transformative Learning

Because it is so hard for learners to engage in transformative learning successfully, it is often only done at scale in expert institutions that are specifically designed to accommodate this. Consider the immense effort invested in medical students, or Buddhist monks. While we can be assured that much transformative learning (and perhaps even most of it) happens in the wild, these cases are too diverse and unpredictable to be documented.

These teaching institutions assume learner motivation to progress in their practice, whatever it may be. In addition, they typically filter out any student who is not thought capable of acquiring expertise. So these institutions select for highly motivated and already intelligent students.

Within the motivation to learn generally, the motivation for transformative learning is subsumed. Hence there is no need to inquire what the students’ motivation is to engage death and rebirth. In order to facilitate this difficult learning, instructional design of these institutions scaffold the learning in various ways that are assumed in Cognitive Transformation Theory research typically.

• Identity is retained through transformation and is explicitly not threatened. (You will not lose any sense of identity by engaging in this paradigm shift)

• Peers that have already gone through the process show that what you are learning is both learnable/comprehensible. (This assumes a standardization of the education, which is usually granted.)

• Experts allow one to keep a critical identity frame—trust in authority is legitimate. New authorities do not need to be recognized, nor does the concept of trust need to be reevaluated. (Consider the pedagogy of going through Freudian analysis.)

The research on conceptual change and knowledge shields studies people under relatively favorable conditions: the students want proficiency and have teachers who are trying to transfer their expertise, they have a definite end they know to be accessible, and they trust the relevant experts enough to let themselves be corrected.
But the autodidactic reality lacks all of these things.

Curriculum vs. Character

Even with all of these supports, CTT expresses constant laments at the difficulty of transformative learning. I would like to suggest that an underdiagnosed aspect of their problem lies in the capacity of the learners. This is natural, given that CTT focuses on creating domain specific learning environments. We already recognize a variance amongst learners’ capacity for transformative learning; it is only natural to ask what might contribute to this variance. If this capacity is impacted by experience and history, we can then begin inquiring how to cultivate such a capacity in learners and stabilize it as a character.

So instead of asking how to create an environment where knowledge shields can be bypassed for highly motivated learners, we can ask what the character of a learner proficient at transformative learning looks like and how to cultivate one⁵.

These questions of curriculum design for a domain and cultivation of a character overlap, but diverge in important ways. The answer for character formation cannot be limited to domain-specific curriculum design; it must involve the cultivation of a more general and stable capacity. This cultivation may be actualized via a curriculum, but it cannot be one aimed merely at the delivery of content. It would be a curriculum for the formation of character, with the learner themselves as the object of inquiry. This is analogous to the difference between trying to explain to a student how to solve a specific mathematical procedure versus giving them a general understanding that would allow them to solve all such questions in the set, or better yet, how to approach new domains in mathematics.

Conservative and Revolutionary Curiosity

Highly structured environments for transformative learning support revision externally by surfacing anomaly, sustaining attention, providing sequencing, reducing the cost of destabilization, and legitimizing the new frame. But if the educational aim is not better environmental design for learners who generally struggle with transformative learning, but the formation of a character who can increasingly internalize revision, then some scaffolding that these environments provide need to be located in the learner’s history, rather than in the present environment. In other words, the learner needs to have internalized mechanisms that drive to transformative learning; the learner needs to be actively seeking the death-rebirth of transformative learning. Below I sketch some of what I think to be the most important parts of the character of a transformative learner.

Curiosity is defined as “a pleasant motivational state involving the tendency to recognize and seek out novel and challenging information and experiences” (Kashdan, Steger, and Breen 2007). Both additive learners and transformative learners can be curious. However, because of the different frames between these two camps of learners, curiosity manifests itself in different ways.

For the storehouse learners, curiosity drives one to seek additive concepts that do NOT require any significant reformation of the mind⁶. Most school learning fits this category. This curiosity seeks addition, extension, clarification, enrichment, or stimulation without threatening the basic frame. We can call this, additive or conservative curiosity.

However, transformative learners are driven by a different kind of curiosity. They seek information that destabilizes and offers better conceptual networks. This second type of curiosity, at the very least, seeks data to subtract errors from itself and be less wrong; in more sophisticated and fuller versions, this curiosity is driven by the motivation for a radical reshaping of the mind, and strives for novel frames that unearth new affordances from old territories. It is more than willing to endure the negative moment in which an old frame becomes unstable, inadequate, obsolete and incoherent; it is precisely a quest for such experiences. We can call this, transformative or revolutionary curiosity.

Revolutionary curiosity serves to resolve many problems that the educational environments researched by CTT resolve implicitly, as well as obsolete some of the problems they seek to resolve in these spaces.

As explained above, in highly scaffolded settings, the learner does not need to generate the full motive force for transformation from within. But a learner in a state of revolutionary curiosity has the internal motivation that can drive transformational learning.

Earlier, we noted a list of structural features that make transformative learning easier in the institutions researched by Cognitive Transformation theorists:

• Motivation

• Credible end-goal/standardization

• Structure of information

• Identity protection

• Peer normalization

• Trustworthy authority

• Coercive mechanisms for overcoming shields and blindness

Revolutionary curiosity makes motivation for transformative learning endogenous. Because confrontation with anomaly is itself experienced as valuable, it does not need the external motivations of the institution to undergo transformative learning. Similarly, it weakens, or even completely dissolves, the need for a fixed endpoint; the learner who embraces and pursues the death-rebirth cycle of learning does not need the endpoint to be clear in order to seek the information that can trigger such an experience.

Institutions use authority, carrots, and sticks, amongst a variety of tools to make learners confront information that catalyzes transformative challenges. Revolutionary curiosity is a motivational state that seeks out, remains with, and even invites disturbing data rather than flee toward simpler explanations. In that sense it substitutes for forced exposure to anomaly, containment from escape to distractions, and some of the struggle against knowledge shields.

When considering frame blindness and shields, the sophistication of the learner in a state of revolutionary curiosity comes into play in interesting ways. For some individuals, information with transformative potential will still be actively sought. In a sense, an excellent transformative learner will be able to successfully identify and consider alternative frames that emerge from data. While this cannot possibly resolve the problem of frame blindness completely, it is clearly valuable.

As for knowledge shields, a learner in a state of revolutionary curiosity treats them with suspicion. While every knowledge shield is possibly functioning to protect one from degenerating into a worse frame, it is also potentially a barrier to forward evolution.

What it does not replace are the supports tied to structure, peers, and authority. Curiosity does not itself sequence information well, normalize the process socially, or solve the problem of identifying trustworthy guides. It may reduce dependence on these things, but it does not make them unnecessary. Revolutionary curiosity is therefore not a substitute for the whole scaffold of transformative learning.

More importantly, revolutionary curiosity is an unstable motivational state. It must be stabilized as a character trait in order to replace the institutional scaffolding in a reliable way.

Identity and Stabilization of Revolutionary Curiosity

I suggest considering identity as a stabilizer of revolutionary curiosity. Borrowing from Sfard and Prusak (2005), identity may be understood as a set of significant, reifying, endorsable stories about who a person is and who that person is becoming. In the terms of this essay, the transformative learner comes to understand themself through stories in which being revised is not a humiliation or a threat to selfhood, but an integral part of learning well. These stories form part of the learner’s frame and pattern of interpretation of their own experiences. When revolutionary curiosity becomes part of the learner’s self-understanding, anomaly, disorientation, and the possibility of frame change are actively pursued. In this sense, identity is one of the means by which revolutionary curiosity becomes durable enough to begin taking the form of character.

Identity is not merely adjacent to learning; it is a powerful part of the learner’s frame itself, and thus shapes the learning process dynamically. It affects what the learner notices in the information landscape, how they interpret data, and their emotional responses to threats to their current conceptual network. Recognizing oneself as a transformative learner animated by revolutionary curiosity is a game changer; it reorganizes not only motivation, but the learner’s attention and their whole stance towards revision.

Character of the Transformative Learner

We are now ready to define the Transformative Learner:

The transformative learner is a person for whom revolutionary curiosity has been stabilized by identity into character, and who can reliably sustain revision toward better frames.

The transformative learner matters both inside expert educational institutions and outside them. Such learners reduce some of the burdens institutions typically carry because they do not depend on coercion, externally forced anomaly, and heavy motivational support. A population of transformative learners will ease the job of curriculum designers and teachers. Such a population would also make possible more radical visions of what expert educational institutions can be. Institutional scaffolds will still play a large role in the learning of transformative learners. But if such a character were more common, institutions could spend less effort overcoming basic resistance to transformation and focus instead on other pedagogical functions in order to better leverage resources.

As noted earlier, autodidactic learning is increasingly becoming the rule rather than the exception. In autodidactic conditions, frame blindness and knowledge shields are harder to overcome because there is no expert forcing anomaly to the surface. The transformative learner is better able to seek, notice, and remain with threatening information without institutional support.

It is important to discriminate between a genuine transformative learner and its confused imitators. The transformative learner is not merely open to revising their conceptual network willy-nilly; such a character would be easily manipulated or unstable. Novelty addiction is another misleading vice. While it is a close look-alike to revolutionary curiosity, it lacks the discretion to care whether the new frame is not simply shiny, but also better. Another failure mode is a tendency toward skepticism that paralyzes judgment and cultivates disengagement.

Like any virtue, this character suffers from the Gorgias Problem: it is easier to appear to be a transformative learner than it is to be one. Varieties of performative anti-dogmatism or heterodoxy are real temptations that must be recognized as false presentations of the transformative learner.

The portrait of this kind of person raises a new question: how should we judge an education?

A New Standard for Foundational Education

Educational institutions are typically judged by the storehouse model. In that sense, a successful program ends with a learner in command of the relevant stock of knowledge. The transformative learning model and the introduced character of the transformative learner unveil a more sensible criterion: how driven and capable is the graduate at transformative learning?

Cognitive Transformation Theory leads us to judge an educational institution or program by its capacity to successfully induce transformative episodes in a specific domain. Our account here takes it one step forward and asks us to judge the success of foundational education by looking at the graduate’s capacity for future transformative learning, inside and outside of official educational institutions.

Education typically aims to internalize in the learner some knowledge that is currently outside. This can be seen in domains as varied as spelling tests, calculus and philosophy. The description of the transformative learner described here invites us to see the general capacity for transformative learning as a foundational proficiency to be internalized.

We should therefore judge a foundational education not by what knowledge it transmits, nor by what transformations it induces under scaffolded conditions. Instead we should examine whether it graduates a learner capable of meaningful self-revision. The deepest educational question is not what the learner merely knows, but what kind of learner the education has made.

Fate of the Animals — Franz Marc

Open questions

Open empirical and conceptual questions obviously remain to be explored. Below, I list only a few for the consideration of future research.

• What are the domain limits of transformative learning? Can one be a generalized transformative learner, or is one limited to bounded domains? How are these domains best constructed and understood?

• What observable behaviors, conversational patterns, or learning trajectories would distinguish a genuine transformative learner from a merely performative one?

• What kinds of educational experiences most reliably increase a learner’s future capacity for transformative learning, rather than merely inducing isolated transformative episodes?

• What can help autodidactic learners reliably surface anomaly in the absence of expert guidance, especially under conditions of frame blindness and opt-in information environments?

• To what extent can revolutionary curiosity be a vice and not a virtue?

Thank you to Shoshana Gabbai and David Campbell for comments on an earlier draft.

Thank you to my peers at ORI for cultivating an environment that makes me excited to write.

Thank you to Joe Edelman—a constant source of my transformative learning.

Glossary

𝗔𝗱𝗱𝗶𝘁𝗶𝘃𝗲 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆: See 𝗰𝗼𝗻𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝘃𝗲 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆.

𝗔𝗱𝗱𝗶𝘁𝗶𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Learning that adds information, procedures, or fluency without major reorganization of a learner’s 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘂𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 or 𝗳𝗿𝗮𝗺𝗲.

𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘂𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸: The dynamically activated organization of concepts, expectations, and relations through which a learner understands a domain. It helps structure the learner’s 𝗳𝗿𝗮𝗺𝗲, and when threatened by anomaly it is often defended by 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝘀𝗵𝗶𝗲𝗹𝗱𝘀.

𝗖𝗼𝗻𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝘃𝗲 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆: Curiosity that seeks addition, clarification, enrichment, or stimulation without threatening the learner’s basic 𝗳𝗿𝗮𝗺𝗲.

𝗗𝗲𝗮𝘁𝗵-𝗥𝗲𝗯𝗶𝗿𝘁𝗵 𝗺𝗼𝗱𝗲𝗹 / 𝗺𝗲𝘁𝗮𝗽𝗵𝗼𝗿: A metaphor for the lived structure of 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴, in which an old 𝗳𝗿𝗮𝗺𝗲 breaks down so that a better one can emerge.

𝗙𝗿𝗮𝗺𝗲: The organization of salience, expectation, and interpretation that shapes what a learner notices, ignores, and treats as significant. A 𝗳𝗿𝗮𝗺𝗲 is partly structured by the learner’s 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘂𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸, and 𝗳𝗿𝗮𝗺𝗲 𝗯𝗹𝗶𝗻𝗱𝗻𝗲𝘀𝘀 occurs when it prevents relevant anomaly from appearing as significant at all.

𝗙𝗿𝗮𝗺𝗲 𝗯𝗹𝗶𝗻𝗱𝗻𝗲𝘀𝘀: The condition in which a learner’s existing 𝗳𝗿𝗮𝗺𝗲 prevents relevant anomaly from appearing as significant in the first place.

𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆: A set of significant, reifying, endorsable stories about who a person is and who that person is becoming, helping stabilize 𝗿𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗮𝗿𝘆 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆 into character.

𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝘀𝗵𝗶𝗲𝗹𝗱𝘀: Defensive maneuvers by which a learner protects an incumbent 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘂𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 from threatening anomaly once it has surfaced within the learner’s 𝗳𝗿𝗮𝗺𝗲.

𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗮𝗿𝘆 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆: Curiosity that seeks information with the potential to revise the current 𝗳𝗿𝗮𝗺𝗲 or 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘂𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 toward a better one.

𝗦𝘁𝗼𝗿𝗲𝗵𝗼𝘂𝘀𝗲 𝗺𝗼𝗱𝗲𝗹 / 𝗺𝗲𝘁𝗮𝗽𝗵𝗼𝗿: A model of learning in which the mind improves primarily through 𝗮𝗱𝗱𝗶𝘁𝗶𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴: the accumulation of contents, procedures, and fluencies, along with growing skill in handling and applying them. It is therefore linked to 𝗰𝗼𝗻𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝘃𝗲 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆, which seeks extension, clarification, and enrichment without demanding major reorganization of the learner’s 𝗳𝗿𝗮𝗺𝗲 or 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘂𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸.

𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆: See 𝗿𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗮𝗿𝘆 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆.

𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗿: A person for whom 𝗿𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗮𝗿𝘆 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆 has been stabilized by 𝗶𝗱𝗲𝗻𝘁𝗶𝘁𝘆 into character, and who can reliably sustain revision toward better 𝗳𝗿𝗮𝗺𝗲𝘀.

𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Learning that revises or reorganizes a learner’s 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘂𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 and 𝗳𝗿𝗮𝗺𝗲, rather than merely adding new content.

Bibliography

Adler, Mortimer J., and Charles Van Doren. How to Read a Book: The Classic Guide to Intelligent Reading. New York: Simon & Schuster, 1972.

Feltovich, Paul J., Richard L. Coulson, and Rand J. Spiro. “Learners’ (Mis)Understanding of Important and Difficult Concepts: A Challenge to Smart Machines in Education.” In Smart Machines in Education: The Coming Revolution in Educational Technology, 349–375. Menlo Park, CA: AAAI/MIT Press, 2001.

Feltovich, Paul J., Rand J. Spiro, Richard L. Coulson, and Jans F. Adami. Conceptual Understanding and Stability, and Knowledge Shields for Fending Off Conceptual Change. Technical Report No. 7. Springfield, IL: Southern Illinois University School of Medicine, 1994.

Kashdan, Todd B., Michael F. Steger, and William E. Breen. “Curiosity.” In Encyclopedia of Social Psychology, edited by Roy F. Baumeister and Kathleen D. Vohs. Thousand Oaks, CA: SAGE, 2007.

Klein, Gary, and Holly C. Baxter. “Cognitive Transformation Theory: Contrasting Cognitive and Behavioral Learning.” In The PSI Handbook of Virtual Environments for Training and Education, Vol. 1, Learning, Requirements, and Metrics, edited by Jack J. Cohn, Daniel Schmorrow, and David Nicholson, 50–65. Westport, CT: Praeger Security International, 2009.

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Sfard, Anna, and Anna Prusak. “Telling Identities: In Search of an Analytic Tool for Investigating Learning as a Culturally Shaped Activity.” Educational Researcher 34, no. 4 (2005): 14–22.

1. I alternate freely here between the use of the words model and metaphor.

2. Adler and Van Doren’s (1972) distinction between “reading for information” and “reading for understanding” parallels the contrast developed here. The former treats reading as adding information to their storehouse; the latter requires the reader to transform their conceptual perception. The account helps point at pedagogical opportunities in reading for transformative learning.

3. By “conceptual network,” I do not mean a static set of interrelated concepts, but a dynamically activated organization that responds to incoming stimuli and helps regulate what the learner notices, assimilates, resists, or treats as salient. In this respect, it is more helpful to think of the mind as an ongoing regulatory system than as a static set of interrelated concepts

4. There are a variety of interesting descriptions of this same concept from different angles; Pixie refers to it as epistemic firewalls, and Defender discriminates between epistemic firewalls and fences. While they are more focused on broader communication issues and not education, the implications of this paper for their concerns are evident.

5. This argument does not reject additive learning. A learner who becomes better at transformative learning will be able to augment themselves at additive learning whenever the task calls for accumulation, fluency, or retention.

6. Regardless of the model, every piece of additive information has some ecological effect on the conceptual network in the mind, and hence, regardless of how the learner models themselves, there will be some small-scale transformation. However, at miniscule scales, the experience is aligned with the storehouse model and is explained satisfactorily.