He works at the intersection of philosophy, cognitive
science, and machine learning, integrating ideas, methods, and frameworks from each to advance our
understanding of complex, cross-disciplinary problems. (...) His earlier work on computational cognitive science resulted in his
book, Unifying the Mind: Cognitive Representations as Graphical Models, which developed an
integrated cognitive model of complex human cognition.
Language:English
Score: 951012.4
-
https://www.unidir.org/sites/d...pdfs/description-eng-0-740.pdf
Data Source: un
Sensory pathways like those for basic vision and hearing are the first to develop, followed by early language skills and higher cognitive functions. Connections proliferate and prune in a prescribed order, with later, more complex brain circuits built upon earlier, simpler circuits.
2 The interactive influ-ences of genes and experience shape the developing brain. (...) Early plasticity means it’s easier and more effective to influence a baby’s developing brain architecture than to rewire parts of its circuitry in the adult years.
4 Cognitive, emotional, and social capacities are inextricably intertwined throughout the life course. (...) Emotional well-being and social compe- tence provide a strong foundation for emerging cognitive abilities, and together they are the bricks and mortar that comprise the foundation of human development.
Language:English
Score: 951012.4
-
https://violenceagainstchildre...ard_brian_science_briefing.pdf
Data Source: un
DISABILITY STATISTICS : REPORT OF THE SECRETARY-GENERAL AND THE WASHINGTON GROUP
A separate section focuses on the
reasons for which a child might be out of school. Cognitive testing began in the
United States in 2015 and will continue in other international locations in 2016.
(...) The Question
Design Research Laboratory at the National Center for Health Statistics is scheduled
to conduct cognitive testing of the module in the United States in 2016. Revisions
will be made based on the cognitive test results, followed by cognitive and field
testing in additional countries.
Language:English
Score: 949608.2
-
https://daccess-ods.un.org/acc...?open&DS=E/CN.3/2016/22&Lang=E
Data Source: ods
Better cognition in later life has been associated with higher levels of education.29,30 Our urban sample had much more formal education than the rural sample, which may explain the higher levels of cognitive functioning among the urban older adults. (...) Residential mobility and cognitive function among middle-aged and older adults in China. (...) Rural-urban differences in the prevalence of cognitive impairment in independent community-dwelling elderly residents of Ojiya city, Niigata
Prefecture, Japan.
Language:English
Score: 944447.6
-
https://www.un.org/en/developm...M_26Feb2019_S5_KarlPeltzer.pdf
Data Source: un
PowerPoint Presentation
UNESCO EDUCATION SECTOR
Education for Sustainable Development Goals
Learning objectives
UNESCO EDUCATION SECTOR 2
Publication developed by UNESCO together with a research team at the University of Vechta, Germany to provide guidance on how to address each of the 17 SDGs through Education
Peer-reviewed by experts on ESD and on each of the SDGs from around the world
Launched at the UNESCO Week for Peace and Sustainable Development in Ottawa, Canada in March 2017
So far available in 4 languages (English, French, Spanish, Portuguese); translation into other languages (Arabic, Russian, Chinese, Serbian…) ongoing
Background
UNESCO EDUCATION SECTOR 3
Provide orientation on how to use ESD for learning for the SDGs
Outline indicative learning objectives as well as suggestions and examples for topics and learning activities for each SDG
Describe implementation on different levels from course design to national strategies
Support education officials, policy makers, educators, curriculum developers and others in designing strategies, curricula and lesson plans
Contribute to developing all learners’ capacity to contribute to the achievement of the SDGs within their timeframe until 2030
Aims of the Publication
UNESCO EDUCATION SECTOR 4
Structure of the Publication
Part I Introduction to the SDGs, ESD, and the possible contribution of ESD to achieving the SDGs;
Part II Recommendations for cognitive, socio- emotional and behavioural learning objectives, topics and pedagogical approaches for each of the 17 SDGs;
Part III Recommendations and examples of strategies for how ESD can be implemented at different educational levels and in different settings.
(...) UNESCO EDUCATION SECTOR 6
cognitive domain: comprises knowledge and thinking skills necessary to better understand the specific SDG and the challenges in achieving it
socio-emotional domain: includes social skills that enable learners to collaborate, negotiate and communicate to promote the SDGs as well as self-reflection skills, values, attitudes and motivations that enable learners to develop themselves
behavioural domain: describes action competencies
Recommendations for SDG learning topics and approaches
UNESCO EDUCATION SECTOR 7
Example: No poverty (SDG 1) – Learning Objectives
Cognitive
learning
objectives
The learner understands…
• the concepts of extreme and relative poverty and is able to critically reflect on their underlying cultural and normative assumptions and practices.
• how extremes of poverty and extremes of wealth affect basic human rights and needs.
(...) Suggested learning approaches and methods:
UNESCO EDUCATION SECTOR 9
Example: Affordable and clean energy (SDG 7)
Cognitive
learning
objectives
The learner knows about/understands…
• different energy resources – renewable and non-renewable – and their respective advantages and disadvantages
• how policies can influence the development of energy production, supply, demand and usage
Socio-
emotional
learning
objectives
The learner is able to:
• assess and understand the need for affordable, reliable, sustainable and clean energy of other people/other regions
• clarify personal norms and values related to energy production and usage as well as to reflect and evaluate their own energy usage in terms of efficiency and sufficiency
Behavioural
learning
objectives
The learner is able to:
• apply basic principles to determine the most appropriate renewable energy strategy in a given situation
• influence public policies related to energy production, supply and usage
UNESCO EDUCATION SECTOR 10
Ex: Responsible Consumption and Production (SDG 12)
Cognitive
learning
objectives
The learner understands…
• how individual lifestyle choices influence social, economic and environmental development
• dilemmas/trade-offs related to and system changes necessary for achieving sustainable consumption and production
Socio-
emotional
learning
objectives
The learner is able to:
• differentiate between needs and wants, and to reflect on their own individual consumer behaviour in light of the needs of nature, other people, cultures, countries and future generations
• feel responsible for the environmental and social impacts of their own individual behaviour as a producer or consumer.
Language:English
Score: 942255.1
-
https://unece.org/fileadmin/DA...objectives_EN_long_version.pdf
Data Source: un
TRADITIONAL KNOWLEDGE : NOTE / BY THE SECRETARIAT
PURPOSES OF THE PROJECT
Project proposal aims at both cognitive purposes and operative actions.
Cognitive purposes are:
1. (...) WORK PROGRAMME
First year
Goals
Cognitive goal: to continue the drawing up of the inventory on TK and their innovative use.
(...) Second year
Goals
Cognitive purpose: Database dissemination
Organizational purpose: Network implementation
Activities
1.
Language:English
Score: 939802.5
-
daccess-ods.un.org/acce...en&DS=ICCD/COP(6)/CST/4&Lang=E
Data Source: ods
The approach of integrating different (e.g. behavioral and neurobiological) measures of a comprehensive set of cognitive domains has become increasingly influential in the field of psychiatry. (...) In addition, demographic information as well as extensive cognitive and behavioral measures will be permitted to derive predictive models. (...) In addition, clinical institutions could potentially provide additional (undisclosed) data, such as cognitive, behaviourally, neurophysiological data and clinical diagnosis.
Language:English
Score: 937543.9
-
https://www.itu.int/en/ITU-T/f...ents/all/FGAI4H-H-019-A02.docx
Data Source: un
The approach of integrating different (e.g. behavioral and neurobiological) measures of a comprehensive set of cognitive domains has become increasingly influential in the field of psychiatry. (...) In addition, demographic information as well as extensive cognitive and behavioral measures will be permitted to derive predictive models. (...) In addition, clinical institutions could potentially provide additional (undisclosed) data, such as cognitive, behaviourally, neurophysiological data and clinical diagnosis.
Language:English
Score: 937543.9
-
https://www.itu.int/en/ITU-T/f...ents/all/FGAI4H-G-005-A08.docx
Data Source: un
Dementia is a syndrome – usually of a chronic or progressive nature – that leads to deterioration in cognitive function (i.e. the ability to process thought) beyond what might be expected from the usual consequences of biological ageing. (...) Consciousness is not affected. The impairment in cognitive function is commonly accompanied, and occasionally preceded, by changes in mood, emotional control, behaviour, or motivation.
(...) Signs and symptoms
Dementia affects each person in a different way, depending upon the underlying causes, other health conditions and the person’s cognitive functioning before becoming ill. The signs and symptoms linked to dementia can be understood in three stages.
Language:English
Score: 937543.9
-
https://www.who.int/news-room/fact-sheets/detail/dementia
Data Source: un
TDD Update: TG-Cogni (Neuro-cognitive diseases) [Same as Meeting F]
- 15 -
FG-AI4H-G-007
INTERNATIONAL TELECOMMUNICATION UNION
TELECOMMUNICATION STANDARDIZATION SECTOR
STUDY PERIOD 2017-2020
FG-AI4H-G-007
ITU-T Focus Group on AI for Health
Original: English
WG(s):
Plenary
New Delhi, 13-15 November 2019
DOCUMENT
Source:
TG-Cogni topic driver
Title:
TDD Update: TG-Cogni (Neuro-cognitive diseases) [Same as Meeting F]
Purpose:
Discussion
Contact:
Marc Lecoultre MLLab.ai Switzerland
Tel: +41 79 321 09 29 Fax: +41 22 364 30 69 Email: ml@mllab.ai
Contact:
Kherif Ferah, vice-director LREN, CHUV Switzerland
Tel: +41 79 556 11 06 Email: Ferath.kherif@chuv.ch
Abstract:
This document is the Topic Description Document (TDD) containing the standardized benchmarking approach for the use of AI for Neuro-Cognitive diseases. (...) This document is the TDD for the Topic Group on “AI against neuro-cognitive diseases” (TG-Cogni) The document will be developed cooperatively over several FG-AI4H meetings starting from meeting D in Shanghai. (...) The data will include clinical scores, diagnostic, cognitive measures and biological measures (PET, MRI, fMRI, lab results).
Language:English
Score: 934207.6
-
https://www.itu.int/en/ITU-T/f...ocuments/all/FGAI4H-G-007.docx
Data Source: un