52,493 research outputs found
Apperceptive patterning: Artefaction, extensional beliefs and cognitive scaffolding
In âPsychopower and Ordinary Madnessâ my ambition, as it relates to Bernard Stieglerâs recent literature, was twofold: 1) critiquing Stieglerâs work on exosomatization and artefactual posthumanismâor, more specifically, nonhumanismâto problematize approaches to media archaeology that rely upon technical exteriorization; 2) challenging how Stiegler engages with Giuseppe Longo and Francis Baillyâs conception of negative entropy. These efforts were directed by a prevalent techno-cultural qualifier: the rise of Synthetic Intelligence (including neural nets, deep learning, predictive processing and Bayesian models of cognition). This paper continues this project but first directs a critical analytic lens at the Derridean practice of the ontologization of grammatization from which Stiegler emerges while also distinguishing how metalanguages operate in relation to object-oriented environmental interaction by way of inferentialism. Stalking continental (Kapp, Simondon, Leroi-Gourhan, etc.) and analytic traditions (e.g., Carnap, Chalmers, Clark, Sutton, Novaes, etc.), we move from artefacts to AI and Predictive Processing so as to link theories related to technicity with philosophy of mind. Simultaneously drawing forth Robert Brandomâs conceptualization of the roles that commitments play in retrospectively reconstructing the social experiences that lead to our endorsement(s) of norms, we compliment this account with Reza Negarestaniâs deprivatized account of intelligence while analyzing the equipollent role between language and media (both digital and analog)
The Potency Of Metacognitive Learning To Foster Mathematical Logical Thinking
The ability of thinking logically needs to be developed due to the fact that it is an essential basic skill. Logical thinking affects that giving reason must be true, and that a sequence of assumptions is based on the high truth value. Mathematics is a subject that functions to train students to think logically. The understanding of logic will help students to arrange the proof that support through process to finally arrive at a conclusion. Currently, metacognition is viewed as an essential element of learning. It refers to someone knowledge of processes and the result itself or of that connected to the process. Metacognition is needed when student solves the task that needs argumentation and logical understanding. In order to help student to skillful think logically, mathematics learning must be designed as such so that the condition will raise the skill of metacognitive acts.
Key words: metacognitive learning, mathematical logical thinkin
Using fMRI in experimental philosophy: Exploring the prospects
This chapter analyses the prospects of using neuroimaging methods, in particular functional magnetic resonance imaging (fMRI), for philosophical purposes. To do so, it will use two case studies from the field of emotion research: Greene et al. (2001) used fMRI to uncover the mental processes underlying moral intuitions, while Lindquist et al. (2012) used fMRI to inform the debate around the nature of a specific mental process, namely, emotion. These studies illustrate two main approaches in cognitive neuroscience: Reverse inference and ontology testing, respectively. With regards to Greene et al.âs study, the use of Neurosynth (Yarkoni 2011) will show that the available formulations of reverse inference, although viable a priori, seem to be of limited use in practice. On the other hand, the discussion of Lindquist et al.âs study will present the so far neglected potential of ontology-testing approaches to inform philosophical questions
Learning strategies in interpreting text: From comprehension to illustration
Learning strategies can be described as behaviours and thoughts a learner engages in during learning that are aimed at gaining knowledge. Learners are, to use Mayerâs (1996) constructivist definition, âsense makersâ. We can therefore position this to mean that, if learners are sense makers, then learning strategies are essentially cognitive processes used when learners are striving to make sense out of newly presented material. This paper intends to demonstrate that such thoughts and behaviours can be made explicit and that students can co-ordinate the basic cognitive processes of selecting, organising and integrating. I will discuss two learning strategies which were developed during three cycles of an action research enquiry with a group of illustration students. While each cycle had its own particular structure and aims, the main task, that of illustrating a passage of expository text into an illustration was a constant factor. The first learning strategy involved assisting students develop âmacropropositionsââpersonal understandings of the gist or essence of a text (Louwerse and Graesser, 2006; Armbruster, Anderson and Ostertag, 1987; Van Dijk & Kintsch, 1983). The second learning strategy used a form of induction categorised as analogical reasoning (Holyoak, 2005; Sloman and Lagnado, 2005). Both strategies were combined to illustrate the expository text extract. The data suggests that design students benefit from a structured approach to learning, where thinking processes and approaches can be identified and accessible for other learning situations. The research methodology is based on semi-structured interviews, questionnaires, developmental design (including student notes) and final design output. All student names used are pseudonyms. The text extract from âThrough the Magic Doorâ an essay Sir Arthur Conan Doyle, (1907) has been included as it provides context to analysis outcomes, student comments and design outputs.
Keywords:
Action Research; Illustration; Macrostructures; Analogical Reasoning; Learning Strategies</p
Development of intuitive rules: Evaluating the application of the dual-system framework to understanding children's intuitive reasoning
This is an author-created version of this article. The original source of publication is Psychon Bull Rev. 2006 Dec;13(6):935-53
The final publication is available at www.springerlink.com
Published version: http://dx.doi.org/10.3758/BF0321390
Helmholtzâs Physiological Psychology
Hermann von Helmholtz (1821-1894) established results both controversial and enduring: analysis of mixed colors and of combination tones, arguments against nativism, and the analysis of sensation and perception using the techniques of natural science. The paper focuses on Helmholtzâs account of sensation, perception, and representation via âphysiological psychologyâ. Helmholtz emphasized that external stimuli of sensations are causes, and sensations are their effects, and he had a practical and naturalist orientation toward the analysis of phenomenal experience. However, he argued as well that sensation must be interpreted to yield representation, and that representation is geared toward objective representation (the central thesis of contemporary intentionalism). The interpretation of sensation is based on âfactsâ revealed in experiment, but extends to the analysis of the quantitative, causal relationships between stimuli and responses. A key question for Helmholtzâs theory is the extent to which mental operations are to be ascribed a role in interpreting sensation
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Theory of deferred action: Agent-based simulation model for designing complex adaptive systems
Deferred action is the axiom that agents act in emergent organisation to achieve predetermined goals. Enabling deferred action in designed artificial complex adaptive systems like business organisations and IS is problematical. Emergence is an intractable problem for designers because it cannot be predicted. We develop proof-of-concept, conceptual proto-agent model, of emergent organisation and emergent IS to understand better design principles to enable deferred action as a mechanism for coping with emergence in artefacts. We focus on understanding the effect of emergence when designing artificial complex adaptive systems by developing an exploratory proto-agent model and evaluate its suitability for implementation as agent-based simulation
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