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This chapter explores the rationale behind, and the importance of understanding, the unique profiles of each child being cared for, across early childhood settings. The purpose of this is to frame ways in which all children can be supported to achieve the best developmental, educational and wellbeing outcomes possible, now and in the future. Drawing on the principles and frameworks discussed in Chapter 1, this chapter will support further understanding of the importance of individualised care and education for every child.
At the heart of effective inclusive education lies a shared understanding among all stakeholders. When early childhood communities develop collective commitment to inclusive philosophies, they establish the essential groundwork for sustainable change. This shared vision recognises that inclusion extends beyond physical placement to encompass full participation, valued contribution and authentic belonging. The It takes a village approach acknowledges that inclusion cannot be the responsibility of individual educators working in isolation; rather, it requires coordinated effort across the entire early childhood community. When staff, families and community co-design inclusive principles together, they develop ownership and commitment that withstands the inevitable challenges of implementation.
Chapter 5 explores computational thinking and how digital tools and processes – such as decomposition, abstraction, and algorithmic thinking – can support students’ mathematical understanding. You will consider how robotics, apps, and modelling can be used to promote logical reasoning and real-world application.
Chapter 9 focuses on how students develop foundational understandings of Measurement and Space in the early years (Foundation to Year 2). It explores how young learners engage with concepts such as length, area, time, and mass through hands-on experiences and everyday contexts. You will consider how to structure learning experiences that build conceptual understanding, support spatial reasoning, and introduce key mathematical vocabulary and thinking processes.
Chapter 10 builds on earlier learning and explores how students extend their understanding of Measurement and Space in the middle and upper primary years (Years 3 to 6). It focuses on the development of key concepts such as units of measure, angles, transformations, and geometric properties. You will investigate strategies for using precise mathematical language, addressing common misconceptions, and applying spatial and measurement thinking to solve purposeful, real-world problems.
This reflection explores the gap between explaining and understanding artificial intelligence’s (AI) outcomes, focusing on the example of AI-driven medical diagnostics. Explainable AI (XAI) is fundamentally rooted in machine learning and probabilistic methods, which is why its relationship to domain-specific contexts, such as medical diagnostics or policymaking, as well as to social concepts, such as trust or accountability, remains ambiguous. This creates a gap between what is technically considered as explaining and what, in turn, constitutes the understanding of a model’s predictions and its concrete, situated implications. In our contribution, we draw on the philosophy of science and its contextual notion of scientific understanding to highlight the need for explainable algorithmic outcomes that enable actors to both explain and intervene in creating, applying or interpreting knowledge. Our reflection highlights the potential tension between XAI as providing insights into an AI model’s technical operations and explainability as part of a situated understanding of how the model works within specific social contexts. We believe that bringing the concept of scientific understanding to empirical AI ethics can help us rethink explainability and contribute to more responsible ways of making sense of and interacting with black-box models, particularly in medical diagnostics.
This chapter reconceptualises environmental competence as a dynamic capability rooted in an interconnected blend of knowledge, skills, attitudes, values, understanding and desire. Drawing on foundational models, it examines the structural components of pro-environmental behaviour and links these to empirical studies emphasising the foundations of ecological action. Building on this, the chapter introduces dynamic frameworks – particularly the sustainability competency models developed by Wiek, Withycombe and Redman and extended by Redman and Wiek – which emphasise collaborative, anticipatory, normative and strategic dimensions of sustainability planning. Through reflective tasks and case-based learning, readers are encouraged to recognise and cultivate transformative competencies, such as intercultural mediation and intra-personal awareness, essential for navigating global environmental challenges. The chapter also highlights concepts like Kickwa alli kawsay and Japanese kizuna as culturally embedded pathways towards sustainable living, reinforcing the argument that environmental competence must be pluralistic, inclusive and action-oriented. Ultimately, the text advocates for a holistic shift from static notions of competence to adaptive, integrative models that empower individuals and communities to enact meaningful change within diverse societal contexts.
This brief chapter considers what we mean by knowledge, explanation and understanding, aspects that have and remain areas of debate in the philosophy of science. Despite scientists referring to these aspects routinely in ways that suggest their meaning is clear, examples are given that suggest the terms can actually be used in various ways by different people. It is important to consider what is being claimed and why in a claimed explanation or a claim to understanding, because the terms carry different weights and subjectively mean different things. This can lead to confusion and errors of reasoning that can constrain a field.
This chapter looks at claims to understanding. It begins by looking at the system I have worked on, the lamprey spinal cord locomotor circuit, and claims that circuit function and behaviour can be understood in terms of the interactions of spinal cord nerve cells. I highlight that the claims to experimental confirmation actually reflect various assumptions and extrapolations and that the claimed understanding is lacking. I then look at the Nobel Prize winning work on the Aplysia gill withdrawal reflex, making the same conclusion as the lamprey, various assumptions and extrapolations are used to claim causal links, and in doing this commit various logical fallacies, including confusing correlation for causation and begging the question. I finish by looking at hippocampal long-term potentiation and claims it is the cellular basis of memory, again highlighting that the claimed links have not been made.
Stephen Engstrom argues that judgments that amount to knowledge constitute the end of the faculty of understanding. This implies that true judgments and false judgments are not on par in relation to the attainment of this end. False judgments are incomplete realizations of the understanding whose explanation requires reference to a factor that prevents it from attaining its end. Engstrom takes this to show that truth is essential to judgment (and belongs to its form) whereas falsity is not. This is reflected in our original, a priori understanding of judgment, according to which the capacity to judge is the capacity to know (rather than the capacity, say, to judge either truly or falsely). In an appendix, Engstrom relates this account to the notion of objective validity.
Janum Sethi investigates Kant’s application of hylomorphism to the theory of self-consciousness, as evident in the distinction he draws between transcendental and empirical apperception. According to Sethi, the standard reading of this distinction overlooks that it is drawn in terms of a distinction between transcendental and empirical unity of apperception, which can be traced to the distinct natures of the two faculties that produce these unities: whereas the former is brought about according to the rational laws of the understanding, the latter is a result of the psychological laws of the imagination. In light of this, Sethi argues that the two types of apperception amount to a subject’s awareness of two cognitively essential aspects of herself: namely, her spontaneity and her receptivity – that is, of her capacity to receive the material for cognition through the senses and of her capacity to impart a certain form to this material through the use of the understanding.
David Hume's A Treatise of Human Nature, published anonymously in 1739–40, was his first major work of philosophy, and his only systematic, scientific analysis of human nature. It is now regarded as a classic text in the history of Western thought and a key text in philosophical empiricism, scepticism, and naturalism. This Critical Guide offers fourteen new essays on the work by established and emerging Hume scholars, ranging over Hume's epistemology and philosophy of mind, the passions and ethics, and the early reception of the Treatise. Topics include the significance of Hume's treatment of the passion of curiosity, the critical responses to Hume's account of how we acquire belief in external objects, and Hume's depiction of the human tendency to view the world in inegalitarian ways and its impact on our view of virtue. The volume will be valuable for scholars and students of Hume studies and in eighteenth-century philosophy more generally.
This chapter contrasts the theory of singular compositional abduction with Peter Lipton’s picture of inference to the best explanation. Where Lipton does intend his theory to apply to the scientific interpretation of experimental results, his approach does not involve extensive close reading of scientific experimental work. Moreover, where Lipton relies heavily on early work on contrastive explanation, this chapter argues that that account has limited applicability. It also indicates how his brief account of explanatory virtues have little to offer when it comes to abductive inferences from individual experimental results.
This chapter explains why cognition (Erkenntnis) is its own kind of cognitive good, apart from questions of justification. I argue against reducing the work of thought experiments to their epistemological results, such as their potential to provide prima facie justification. As an apparatus for cognition, a thought experiment enacts the three core elements of Ørsted’s Kantian account: (1) it is a tool for variation; (2) it proceeds from concepts, and (3) its goal is the genuine activation or reactivation of mental processes. Cognition has two components: givenness and thought. I will show in this chapter how givenness and thought are both achieved through thought experiments.
This chapter looks at Kant’s understanding of the relationship between laws of nature and those of freedom in order to further explain Kant’s grounding argument at 4:453. The two sets of laws constitute two systems, the first governing phenomenal nature and the second the intelligible world, that is, the systematic interrelation of rational wills. How the two sets of laws relate reveal one fundamental philosophical system that can be grasped correctly only from the standpoint of practical reason, namely, that of the agent making use of its intelligence in its practical activity. It is the same understanding and the very same transcendental subject who gives the law to nature, who also gives the law to itself, using the same set of concepts, only differently applied. Our law-giving function in both worlds grounds the primacy of our membership in the intelligible world. Different criteria of application of these concepts to noumenal and phenomenal worlds are discussed, and I show how Kant avoids objections to the idea of timeless agency. Kant espouses a modified Leibizianism through which the intelligible and sensible worlds are harmonized indirectly by the author of nature, who harmonizes the functions in us through which the two are constituted.
Kant ascribes two radically different kinds of language—symbolic or pictorial (qua intuitive) and discursive languages—to the ‘Oriental’ and ‘Occidental’ peoples, respectively. By his analysis, having a merely symbolic language suggests that the Orientals lack understanding – and hence the ability to form concepts and think in abstracto – as well as genius and spirit. Meanwhile, he establishes discursive language as a sine qua non of the continued progress of humanity. These points add up to an exclusionary view of progress according to which the Occidental whites alone are equipped with the requisite discursive skills and other talents (including genius and spirit) to accomplish advanced culture and pursue humanity’s (moral) destiny. The Orient, with its supposedly “childish language,” is consigned to the childhood of humanity. In holding this view, Kant has departed from some of his predecessors – such as Leibniz, whose vision of the future of humanity includes an East-West harmony facilitated by a “universal symbolism,” and Rousseau, who exalts a livelier connection with the world mediated by a pictorial language.
In this article I question a long-established, common-sense belief. Namely, that words contain meanings. This belief is the absolute presupposition underpinning the familiar question: ‘What does that word mean? Backed by John Locke, I argue that words don’t mean. Or as Locke puts it: ‘Words are an insignificant noise.’ Words become significant, meaningful, once we have each processed them through our own minds. In short, we subjectively make our own meanings. The role of words is to trigger the meanings we have made for ourselves. This is where the inescapable roots of misunderstanding lie. The words that do the triggering are public. The meanings we create for those words are unavoidably private and mobile. The bulk of the rest of the article addresses the question: ‘How far can we curb misunderstanding?’
Planning for learning is essential for creating environments conducive to deep learning and to developing student understandings. Standard 3 of the Australian Professional Standards for Teachers (APST) specifies the need for all graduate teachers to be able to ‘plan for and implement effective teaching and learning’. Quality planning involves the systematic use of feedback data to design activities that encourage the assimilation and synthesis of information, leading to the creation of new understandings. Student learning should always be the goal.
The sense of duty is a virtue of caring, not directly about the good, or even about justice, but about doing one’s duty. Insofar as doing what one takes to be one’s duty is in fact to do what is good, the sense of duty functions as a backup for the more direct virtues of caring – generosity, compassion, and truthfulness, as well as justice. Being a virtue of caring, the sense of duty can be expressed in emotions: a feeling of satisfaction in having done one’s duties or feelings of guilt or shame at having neglected them. The sense of duty can vary, emotionally, according to how one conceives the authoritative source of duty, on a spectrum from reverence, through respect, to resentful acceptance. Example of the extremes beyond the spectrum are some Hebrew psalmists’ delight in the law of God and the contempt of the utter moral cynic.
‘Truth’ refers to reality – what is, was, will be, and should be – and its aspects, in the context of representations thereof. A true something is the real thing, and a true proposition, belief, hypothesis, exemplar, and so forth is a successful representation of truth in the first sense. The virtue of truthfulness is the judicious love of truth in both senses. From love of reality and correct representations of it, the truthful person tends to tell others the truth as she sees it, but is not fanatical about telling it, because virtues like justice, compassion, and gentleness, which themselves are a kind of truth, can enjoin the withholding or even distortion of truths. Truths can be horrible, and it can take courage and humility to admit them.