scholarly journals Multiple Intelligences in Teaching and Education: Lessons Learned from Neuroscience

2018 ◽  
Vol 6 (3) ◽  
pp. 38 ◽  
Author(s):  
Branton Shearer
Keyword(s):  
Academic Achievement ◽  
Embodied Cognition ◽  
Multiple Intelligences ◽  
Cognitive Neuroscience ◽  
Mixed Method ◽  
Lessons Learned ◽  
Neural Systems ◽  
General Intelligence ◽  
Comprehensive Model

This brief paper summarizes a mixed method review of over 500 neuroscientific reports investigating the proposition that general intelligence (g or IQ) and multiple intelligences (MI) can be integrated based on common and unique neural systems. Extrapolated from this interpretation are five principles that inform teaching and curriculum so that education can be strengths-based and personalized to promote academic achievement. This framework is proposed as a comprehensive model for a system of educational cognitive neuroscience that will serve the fields of neuroscience as well as educators. Five key principles identified are culture matters, every brain is unique—activate strengths, know thyself, embodied cognition/emotional rudder, and make it mean something.

scholarly journals Assessing a Decision Support Tool for SOC Analysts

2021 ◽  
Author(s):  
Jassim Happa ◽  
Ioannis Agrafiotis ◽  
Martin Helmhout ◽  
Thomas Bashford-Rogers ◽  
Michael Goldsmith ◽  
...  
Keyword(s):  
Decision Support ◽  
Mixed Method ◽  
User Study ◽  
Situational Awareness ◽  
Decision Support Tool ◽  
Lessons Learned ◽  
Visualization Tool ◽  
Support Tool ◽  
Response Strategies ◽  
Method Approach

In recent years, many tools have been developed to understand attacks that make use of visualization, but few examples aims to predict real-world consequences. We have developed a visualization tool that aims to improve decision support during attacks. Our tool visualizes propagation of risks from IDS and AV-alert data by relating sensor alerts to Business Process (BP) tasks and machine assets: an important capability gap present in many Security Operation Centres (SOCs) today. In this paper we present a user study in which we evaluate the tool's usability and ability to deliver situational awareness to the analyst. Ten analysts from seven SOCs performed carefully designed tasks related to understanding risks and prioritising recovery decisions. The study was conducted in laboratory conditions, with simulated attacks, and used a mixed-method approach to collect data from questionnaires, eyetracking and voice-recorded interviews. The findings suggest that providing analysts with situational awareness relating to business priorities can help them prioritise response strategies. Finally, we provide an in-depth discussion on the wider questions related to user studies in similar conditions as well as lessons learned from our user study and developing a visualization tool of this type.

Neurofilmology of the Moving Image

2021 ◽  
Author(s):  
Adriano D'Aloia
Keyword(s):  
Embodied Cognition ◽  
Cognitive Neuroscience ◽  
Philosophy Of Mind ◽  
Human Condition ◽  
Moving Image ◽  
Wide Range ◽  
Perceptual Psychology ◽  
Contemporary Cinema

A walk suspended in mid-air, a fall at breakneck speed towards a fatal impact with the ground, an upside-down flip into space, the drift of an astronaut in the void… Analysing a wide range of films, this book brings to light a series of recurrent aesthetic motifs through which contemporary cinema destabilizes and then restores the spectator’s sense of equilibrium. The ‘tensive motifs’ of acrobatics, fall, impact, overturning, and drift reflect our fears and dreams, and offer imaginary forms of transcendence of the limits of our human condition, along with an awareness of their insurmountable nature. Adopting the approach of ‘Neurofilmology’—an interdisciplinary method that puts filmology, perceptual psychology, philosophy of mind, and cognitive neuroscience into dialogue—, this book implements the paradigm of embodied cognition in a new ecological epistemology of the moving-image experience.

scholarly journals Embodied cognition and emotional disorders

2018 ◽  
Vol 9 (3) ◽  
pp. pr.035714 ◽  
Author(s):  
Bergljot Gjelsvik ◽  
Darko Lovric ◽  
J. Mark G. Williams
Keyword(s):  
Motor Cortex ◽  
Embodied Cognition ◽  
Emotional Disorders ◽  
Cognitive Neuroscience ◽  
Semantic Processing ◽  
Low Mood ◽  
Affective Disturbance ◽  
Hub Model ◽  
Important Basis ◽  
Vast Area

Research into embodied cognition (EC) in cognitive neuroscience and psychology has risen exponentially over the last 25 years, covering a vast area of research; from understanding how ability to judge speech sounds depends on an intact motor cortex, to why people perceive hills as steeper when carrying a heavy backpack. Although there are many theories addressing these phenomena, increasing evidence across EC studies suggests simulation (i.e., re-enactment of the motor-sensory aspects of meaning) as an important basis of knowledge. The authors 1) review evidence for the EC paradigm’s claim to simulation effects in cognition, suggesting that simulation exists within a “distributed plus hub” model, 2) discuss the implications of simulation for the understanding of cognitive dysfunctions in emotional disorders, particularly depression, 3) suggest that emotional disorders arises as a result of failed simulation processes, hypothesizing that semantic processing reactivates motor-sensory simulations previously associated with low mood ( enactment/re-enactment networks), and that truncation of such simulation by means of over-use of language-based, abstract processing, motivated by a wish to reduce the affective disturbance associated with episodic, embodied representations, maintains psychopathology, 4) review evidence for effects of truncated simulation on emotional pathology, and 5) discuss the relevance of EC to treatments of emotional pathology.

Vast Topological Learning and Sentient AGI

2021 ◽  
Vol 08 (01) ◽  
pp. 81-111
Author(s):  
Stephen L. Thaler
Keyword(s):  
Human Brain ◽  
Cortical Neurons ◽  
Neural Nets ◽  
Neural Systems ◽  
General Intelligence ◽  
Associative Memories ◽  
Direct Experience ◽  
Environmental Input ◽  
New Concepts ◽  
Random Disturbances

A novel form of neurocomputing allows machines to generate new concepts along with their anticipated consequences, all encoded as chained associative memories. Knowledge is accumulated by the system through direct experience as network chaining topologies form in response to various environmental input patterns. Thereafter, random disturbances to the connections joining these nets promote the formation of alternative chaining topologies representing novel concepts. The resulting ideational chains are then reinforced or weakened as they incorporate nets containing memories of impactful events or things. Such encodings of entities, actions, and relationships as geometric forms composed of artificial neural nets may well suggest how the human brain summarizes and appraises the states of nearly a hundred billion cortical neurons. It may also be the paradigm that allows the scaling of synthetic neural systems to brain-like proportions to achieve sentient artificial general intelligence (SAGI).

Influences of parents' education on their children's educational attainments: the role of parent and child perceptions

2005 ◽  
Author(s):  
Jacquelynne S Eccles
Keyword(s):  
Academic Achievement ◽  
Educational Outcomes ◽  
Family Income ◽  
Family Characteristics ◽  
Parental Influences ◽  
Comprehensive Model ◽  
Educational Attainments ◽  
Residence Location ◽  
Parents Education

This paper is based on a talk given at the conference of the Centre for Research on the Wider Benefits of Learning, September 2004. There is consistent evidence that parents' education predicts children's educational outcomes, alongside other distal family characteristics such as family income, parents' occupations and residence location. A variety of explanations have been offered for these associations. In this paper, we review the most prominent explanations, present a comprehensive model of the influences of parents' education and then summarize some of the research we have done that focuses on the role of parental influences on children's academic achievement.

The Effects of E-learning on African American Males

2010 ◽  
pp. 198-208
Author(s):  
Tammy J. Graham ◽  
Stephenie M. Hewett
Keyword(s):  
Academic Achievement ◽  
African American ◽  
Case Studies ◽  
African American Males ◽  
Educational Experiences ◽  
Lessons Learned ◽  
Learning Program ◽  
Business Professionals ◽  
Electronic Learning ◽  
E Learning

The chapter examines the experiences of three African American males who were placed in an electronic learning (e-learning) classroom in a rural secondary school. The three case studies provide detailed descriptions of the young men’s backgrounds, educational experiences, and academic achievement results before the implementation of e-learning. Furthermore, the case studies detail their academic achievement results and dispositions during the e-learning process, pitfalls of their e-learning program, and lessons learned from the implementation of the program. It is the authors’ hope that educators and business professionals will utilize the information and lessons learned in this chapter when planning and implementing e-learning classes and trainings in order to enhance e-learning experiences for African American males.

scholarly journals DNNBrain: A Unifying Toolbox for Mapping Deep Neural Networks and Brains

2020 ◽  
Vol 14 ◽  
Author(s):  
Xiayu Chen ◽  
Ming Zhou ◽  
Zhengxin Gong ◽  
Wei Xu ◽  
Xingyu Liu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Cognitive Neuroscience ◽  
Deep Neural Networks ◽  
Learning Strategy ◽  
Neural Systems ◽  
Levels Of Abstraction ◽  
Internal Representations ◽  
Internal Operations ◽  
High Level

Deep neural networks (DNNs) have attained human-level performance on dozens of challenging tasks via an end-to-end deep learning strategy. Deep learning allows data representations that have multiple levels of abstraction; however, it does not explicitly provide any insights into the internal operations of DNNs. Deep learning's success is appealing to neuroscientists not only as a method for applying DNNs to model biological neural systems but also as a means of adopting concepts and methods from cognitive neuroscience to understand the internal representations of DNNs. Although general deep learning frameworks, such as PyTorch and TensorFlow, could be used to allow such cross-disciplinary investigations, the use of these frameworks typically requires high-level programming expertise and comprehensive mathematical knowledge. A toolbox specifically designed as a mechanism for cognitive neuroscientists to map both DNNs and brains is urgently needed. Here, we present DNNBrain, a Python-based toolbox designed for exploring the internal representations of DNNs as well as brains. Through the integration of DNN software packages and well-established brain imaging tools, DNNBrain provides application programming and command line interfaces for a variety of research scenarios. These include extracting DNN activation, probing and visualizing DNN representations, and mapping DNN representations onto the brain. We expect that our toolbox will accelerate scientific research by both applying DNNs to model biological neural systems and utilizing paradigms of cognitive neuroscience to unveil the black box of DNNs.

scholarly journals Disembodying cognition

2010 ◽  
Vol 2 (1) ◽  
pp. 79-116 ◽  
Author(s):  
Anjan Chatterjee
Keyword(s):  
Embodied Cognition ◽  
Recent Work ◽  
Cognitive Neuroscience ◽  
Real World ◽  
Grounded Cognition ◽  
Perceptual Information ◽  
Knowing How ◽  
Neuronal Ensembles ◽  
Sensory Motor ◽  
Motor Information

AbstractThe idea that concepts are embodied by our motor and sensory systems is popular in current theorizing about cognition. Embodied cognition accounts come in different versions and are often contrasted with a purely symbolic amodal view of cognition. Simulation, or the hypothesis that concepts simulate the sensory and motor experience of real world encounters with instances of those concepts, has been prominent in psychology and cognitive neuroscience. Here, with a focus on spatial thought and language, I review some of the evidence cited in support of simulation versions of embodied cognition accounts. While these data are extremely interesting and many of the experiments are elegant, knowing how to best interpret the results is often far from clear. I point out that a quick acceptance of embodied accounts runs the danger of ignoring alternate hypotheses and not scrutinizing neuroscience data critically. I also review recent work from my lab that raises questions about the nature of sensory motor grounding in spatial thought and language. In my view, the question of whether or not cognition is grounded is more fruitfully replaced by questions about gradations in this grounding. A focus on disembodying cognition, or on graded grounding, opens the way to think about how humans abstract. Within neuroscience, I propose that three functional anatomic axes help frame questions about the graded nature of grounded cognition. First, are questions of laterality differences. Do association cortices in both hemispheres instantiate the same kind of sensory or motor information? Second, are questions about ventral dorsal axes. Do neuronal ensembles along this axis shift from conceptual representations of objects to the relationships between objects? Third, are questions about gradients centripetally from sensory and motor cortices towards and within perisylvian cortices. How does sensory and perceptual information become more language-like and then get transformed into language proper?

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