This document outlines research on modeling socio-cognitive learning processes in collaborative environments. It discusses:
- The interplay between primary memory (attention control) and secondary memory (long-term memory) during reflection on resources.
- Three studies examining how semantic stabilization evolves through this interplay and affects individual learning. Stabilization was found to support learning by priming memory searches.
- A computational model called CMR that formalizes these memory dynamics and allows modeling how people's reflections lead to intersubjective understandings and semantic stabilization in collaborative tagging systems.
Webinar deck "The great intranets of the Intranet Global Forum" highlighting the best intranet case studies from the Intranet Global Forum in NYC, Oct 22 and 23 2015.
Webinar deck "The great intranets of the Intranet Global Forum" highlighting the best intranet case studies from the Intranet Global Forum in NYC, Oct 22 and 23 2015.
Una explicación sencilla de la Personotecnia, un conjunto de técnicas complejas que permiten un Marketing Directo eficaz.
Esta presentación ha sido elaborada a partir de varias entrevistas con Javier G. Recuenco, experto en el tema, a quien le pedí que me explicara un caso práctico de aplicación de la Personotecnia.
A partir de ese material, he creado esta presentación con el objetivo de transmitir a cualquier persona, incluso a aquellas con pocos conocimientos técnicos relacionados, una visión sencilla de la Personotecnia.
Para profundizar más, recomiendo el libro Personalización, de Javier G. Recuenco y otros autores.
http://www.buscalibros.cl/personalizacion-recuenco-cp_537207.htm
Destacamos la Electro Moly 66. Es un compuesto antigripaje para altas temperaturas con excelentes propiedades hermeticas. Pasta conductora térmica y eléctrica. Evita las fugas, corrosiones internas y soldaduras.
Visite nuestra pagina web para mas informacion, www.brettis.com
fpsyg-08-01454 August 22, 2017 Time 1725 # 1REVIEWpublJeanmarieColbert3
fpsyg-08-01454 August 22, 2017 Time: 17:25 # 1
REVIEW
published: 24 August 2017
doi: 10.3389/fpsyg.2017.01454
Edited by:
Beatrice de Gelder,
Maastricht University, Netherlands
Reviewed by:
Douglas Watt,
Boston University School of Medicine,
United States
Thomas Zoëga Ramsøy,
Neurons Inc. and Singularity
University, Denmark
*Correspondence:
Aamir S. Malik
[email protected]
Specialty section:
This article was submitted to
Emotion Science,
a section of the journal
Frontiers in Psychology
Received: 29 November 2016
Accepted: 10 August 2017
Published: 24 August 2017
Citation:
Tyng CM, Amin HU, Saad MNM and
Malik AS (2017) The Influences
of Emotion on Learning and Memory.
Front. Psychol. 8:1454.
doi: 10.3389/fpsyg.2017.01454
The Influences of Emotion
on Learning and Memory
Chai M. Tyng, Hafeez U. Amin, Mohamad N. M. Saad and Aamir S. Malik*
Centre for Intelligent Signal and Imaging Research (CISIR), Department of Electrical and Electronic Engineering, Universiti
Teknologi Petronas, Seri Iskandar, Malaysia
Emotion has a substantial influence on the cognitive processes in humans, including
perception, attention, learning, memory, reasoning, and problem solving. Emotion has
a particularly strong influence on attention, especially modulating the selectivity of
attention as well as motivating action and behavior. This attentional and executive
control is intimately linked to learning processes, as intrinsically limited attentional
capacities are better focused on relevant information. Emotion also facilitates encoding
and helps retrieval of information efficiently. However, the effects of emotion on learning
and memory are not always univalent, as studies have reported that emotion either
enhances or impairs learning and long-term memory (LTM) retention, depending on
a range of factors. Recent neuroimaging findings have indicated that the amygdala
and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner
that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex
mediating memory encoding and formation; and (iii) the hippocampus for successful
learning and LTM retention. We also review the nested hierarchies of circular emotional
control and cognitive regulation (bottom-up and top-down influences) within the brain to
achieve optimal integration of emotional and cognitive processing. This review highlights
a basic evolutionary approach to emotion to understand the effects of emotion on
learning and memory and the functional roles played by various brain regions and
their mutual interactions in relation to emotional processing. We also summarize the
current state of knowledge on the impact of emotion on memory and map implications
for educational settings. In addition to elucidating the memory-enhancing effects of
emotion, neuroimaging findings extend our understanding of emotional influences on
learning and memory processes; this knowledge may be useful for the design of effectiv ...
The Significance of Social Stimuli in Communication and the Learning Process....Boglarka Bihari
The impact of social context on communication and the learning process. Cooperation on a cognitive level, the reasons for cooperation, and the brain regions associated with social situations.
Journal of Experimental PsychologyLearning, Memory, and CogTatianaMajor22
Journal of Experimental Psychology:
Learning, Memory, and Cognition
Semantic Processes in Preferential Decision Making
Sudeep Bhatia
Online First Publication, July 19, 2018. http://dx.doi.org/10.1037/xlm0000618
CITATION
Bhatia, S. (2018, July 19). Semantic Processes in Preferential Decision Making. Journal of
Experimental Psychology: Learning, Memory, and Cognition. Advance online publication.
http://dx.doi.org/10.1037/xlm0000618
Semantic Processes in Preferential Decision Making
Sudeep Bhatia
University of Pennsylvania
This article examines how semantic memory processes influence the items that are considered by
decision makers in memory-based preferential choice. Experiments 1A through 1C ask participants to list
the choice items that come to their minds while deliberating in a variety of everyday choice settings.
These experiments use semantic space models to quantify the semantic relatedness between pairs of
retrieved items and find that choice item retrieval displays robust semantic clustering effects, with
retrieved items increasing the retrieval probabilities of related items. Semantic clustering can be
disassociated from the effect of item desirability and can lead to inefficiencies such as the consideration
and evaluation of undesirable items early on in the decision. Experiments 2A through 2C use a similar
approach to study the effects of contextual cues on item retrieval and find that decision makers are biased
toward retrieving choice items that are semantically related to the choice context. This effect is usually
strongest early on in deliberation and weakens as additional items are retrieved. Overall, the results
highlight the role of semantic memory processes in guiding the generation of memory-based choice sets,
and illustrate the value of semantic space models for studying preferential decision making.
Keywords: decision making, semantic memory, semantic clustering, preregistration, open science
Preferential decision making involves the selection of a favored
item from a set of feasible choice items. Most experiments on
preferential decision processes explicitly present a choice set to
participants. Correspondingly, psychological theories of decision
making have been concerned primarily with how decision makers
choose between such an exogenously determined set of items, that
is, the decision rules they use to evaluate these items, as well as the
effects of the composition of the choice set, and other related
contextual factors, on their choices (Busemeyer & Rieskamp,
2014; Oppenheimer & Kelso, 2015).
However, many common decision scenarios do not involve a
fixed, exogenous set of choice items. Rather, decision makers must
construct such choice sets by themselves, typically through the use
of memory processes (see Alba & Hutchinson, 1987; Lynch &
Srull, 1982 for early discussions). Consider, for example, the task
of planning what to eat, buying a gift for a friend or family
member, or deciding on a vacation destinati ...
Presentatie die ik samen met Nikki Demandt heb gegeven op 19-12-2011 in het kader van de course Selforganization, cognition and social systems van de Rijksuniversiteit Groningen
Una explicación sencilla de la Personotecnia, un conjunto de técnicas complejas que permiten un Marketing Directo eficaz.
Esta presentación ha sido elaborada a partir de varias entrevistas con Javier G. Recuenco, experto en el tema, a quien le pedí que me explicara un caso práctico de aplicación de la Personotecnia.
A partir de ese material, he creado esta presentación con el objetivo de transmitir a cualquier persona, incluso a aquellas con pocos conocimientos técnicos relacionados, una visión sencilla de la Personotecnia.
Para profundizar más, recomiendo el libro Personalización, de Javier G. Recuenco y otros autores.
http://www.buscalibros.cl/personalizacion-recuenco-cp_537207.htm
Destacamos la Electro Moly 66. Es un compuesto antigripaje para altas temperaturas con excelentes propiedades hermeticas. Pasta conductora térmica y eléctrica. Evita las fugas, corrosiones internas y soldaduras.
Visite nuestra pagina web para mas informacion, www.brettis.com
fpsyg-08-01454 August 22, 2017 Time 1725 # 1REVIEWpublJeanmarieColbert3
fpsyg-08-01454 August 22, 2017 Time: 17:25 # 1
REVIEW
published: 24 August 2017
doi: 10.3389/fpsyg.2017.01454
Edited by:
Beatrice de Gelder,
Maastricht University, Netherlands
Reviewed by:
Douglas Watt,
Boston University School of Medicine,
United States
Thomas Zoëga Ramsøy,
Neurons Inc. and Singularity
University, Denmark
*Correspondence:
Aamir S. Malik
[email protected]
Specialty section:
This article was submitted to
Emotion Science,
a section of the journal
Frontiers in Psychology
Received: 29 November 2016
Accepted: 10 August 2017
Published: 24 August 2017
Citation:
Tyng CM, Amin HU, Saad MNM and
Malik AS (2017) The Influences
of Emotion on Learning and Memory.
Front. Psychol. 8:1454.
doi: 10.3389/fpsyg.2017.01454
The Influences of Emotion
on Learning and Memory
Chai M. Tyng, Hafeez U. Amin, Mohamad N. M. Saad and Aamir S. Malik*
Centre for Intelligent Signal and Imaging Research (CISIR), Department of Electrical and Electronic Engineering, Universiti
Teknologi Petronas, Seri Iskandar, Malaysia
Emotion has a substantial influence on the cognitive processes in humans, including
perception, attention, learning, memory, reasoning, and problem solving. Emotion has
a particularly strong influence on attention, especially modulating the selectivity of
attention as well as motivating action and behavior. This attentional and executive
control is intimately linked to learning processes, as intrinsically limited attentional
capacities are better focused on relevant information. Emotion also facilitates encoding
and helps retrieval of information efficiently. However, the effects of emotion on learning
and memory are not always univalent, as studies have reported that emotion either
enhances or impairs learning and long-term memory (LTM) retention, depending on
a range of factors. Recent neuroimaging findings have indicated that the amygdala
and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner
that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex
mediating memory encoding and formation; and (iii) the hippocampus for successful
learning and LTM retention. We also review the nested hierarchies of circular emotional
control and cognitive regulation (bottom-up and top-down influences) within the brain to
achieve optimal integration of emotional and cognitive processing. This review highlights
a basic evolutionary approach to emotion to understand the effects of emotion on
learning and memory and the functional roles played by various brain regions and
their mutual interactions in relation to emotional processing. We also summarize the
current state of knowledge on the impact of emotion on memory and map implications
for educational settings. In addition to elucidating the memory-enhancing effects of
emotion, neuroimaging findings extend our understanding of emotional influences on
learning and memory processes; this knowledge may be useful for the design of effectiv ...
The Significance of Social Stimuli in Communication and the Learning Process....Boglarka Bihari
The impact of social context on communication and the learning process. Cooperation on a cognitive level, the reasons for cooperation, and the brain regions associated with social situations.
Journal of Experimental PsychologyLearning, Memory, and CogTatianaMajor22
Journal of Experimental Psychology:
Learning, Memory, and Cognition
Semantic Processes in Preferential Decision Making
Sudeep Bhatia
Online First Publication, July 19, 2018. http://dx.doi.org/10.1037/xlm0000618
CITATION
Bhatia, S. (2018, July 19). Semantic Processes in Preferential Decision Making. Journal of
Experimental Psychology: Learning, Memory, and Cognition. Advance online publication.
http://dx.doi.org/10.1037/xlm0000618
Semantic Processes in Preferential Decision Making
Sudeep Bhatia
University of Pennsylvania
This article examines how semantic memory processes influence the items that are considered by
decision makers in memory-based preferential choice. Experiments 1A through 1C ask participants to list
the choice items that come to their minds while deliberating in a variety of everyday choice settings.
These experiments use semantic space models to quantify the semantic relatedness between pairs of
retrieved items and find that choice item retrieval displays robust semantic clustering effects, with
retrieved items increasing the retrieval probabilities of related items. Semantic clustering can be
disassociated from the effect of item desirability and can lead to inefficiencies such as the consideration
and evaluation of undesirable items early on in the decision. Experiments 2A through 2C use a similar
approach to study the effects of contextual cues on item retrieval and find that decision makers are biased
toward retrieving choice items that are semantically related to the choice context. This effect is usually
strongest early on in deliberation and weakens as additional items are retrieved. Overall, the results
highlight the role of semantic memory processes in guiding the generation of memory-based choice sets,
and illustrate the value of semantic space models for studying preferential decision making.
Keywords: decision making, semantic memory, semantic clustering, preregistration, open science
Preferential decision making involves the selection of a favored
item from a set of feasible choice items. Most experiments on
preferential decision processes explicitly present a choice set to
participants. Correspondingly, psychological theories of decision
making have been concerned primarily with how decision makers
choose between such an exogenously determined set of items, that
is, the decision rules they use to evaluate these items, as well as the
effects of the composition of the choice set, and other related
contextual factors, on their choices (Busemeyer & Rieskamp,
2014; Oppenheimer & Kelso, 2015).
However, many common decision scenarios do not involve a
fixed, exogenous set of choice items. Rather, decision makers must
construct such choice sets by themselves, typically through the use
of memory processes (see Alba & Hutchinson, 1987; Lynch &
Srull, 1982 for early discussions). Consider, for example, the task
of planning what to eat, buying a gift for a friend or family
member, or deciding on a vacation destinati ...
Presentatie die ik samen met Nikki Demandt heb gegeven op 19-12-2011 in het kader van de course Selforganization, cognition and social systems van de Rijksuniversiteit Groningen
This is a talk about activity systems analysis and its application for design research. This talk was prepared for students and faculty at Florida State University.
Chapter 8
Cognitive Rehabilitation: An Integrative Neuropsychological Approach 2nd Edition .McKay Moore Sohlberg
ارایه شده در توسط لیلا بخشعلی زاده در کلاس توانبخشی شناختی دکتر آناهیتا خرمی بنارکی - پژوهشکده علوم شناختی
Reflection (1)This chapter explains learning and memories base.docxdebishakespeare
Reflection (1)
This chapter explains learning and memories based on the biology. Driscoll shows some theories that human’s learning is related to the genetic inheritance and brain physiology in Biology. There are two kinds of causes to explain human’s behavior: proximate cause and ultimate cause. Ultimate cause is kind of instinctive desires our ancestors have had been formed to survive for a long time and inherited, the other one, proximate desire is related to the expression of genes or presence of certain behaviors. Ultimate cause interacted with environment leads evolution effects on conditions and cognition. Proximate cause drags on the interest of neurophysiologists, which is studied in the area of the brain with attention, learning and memory, and cognitive development.
This chapter shows that implication of evolution psychology for learning and instruction. First, human may be predisposed to certain fear but it is possible to overcome it with appropriate instructions. Second, it is very difficult to establish if behaviors are not predisposed to learn, but it also can be established using certain instructions. Third, previously adapted behaviors and “actions associated with decreased fitness in ancestral population may be difficult to overcome and establish, respectively, but if we give proper instructions to overcome and establish, it is possible.
In addition, Driscoll shows implication of neurophysiology for learning and instruction. Cognitive functions play different roles in learning and human development, the brain has plasticity naturally, the learning of language may be biologically pre-programmed and disabilities with learning may be related to neurological basis. Yet we don’t know still how the brain works to store memory and information, and what roles the brain play in learning. Many researches are ongoing to find out how we improve our faculties in learning and developing.
Reflection (2)
This chapter of Driscoll’s Psychology of Learning for Instruction evaluates the effects of biology in memory and learning. This affects are divided into two parts: evolution and neurophysiology. Evolution has an effect on cognition and conditioning. It is considered the main cause or ultimate of learning and memory. Neurophysiology is the direct cause of learning and memory. The indirect causes of neurophysiology’s effect on learning and memory are the brain and attention. Evolution and conditioning refer to the age old psychology argument nature vs. nurture. It is between what we are born knowing and what the environment gives (teaches ) us. According to Driscoll (2005), there is evidence to recommend that operant and classical conditions are subject to biological influences. The reason for that is based on the study pointed by Garcia and Koelling. They made a research on taste aversion focus on how rats regarded illness and pain.
The chapter also claims that our evolutionary heritage and genetic require specific constrain ...
Cognitive Load Persuade Attribute for Special Need Education System Using Dat...ijdmtaiir
Human learning system is highly sensitive to
responsive system according the processing, mapping, motion,
auditory and visualization system. Special education system is
implemented to overcome the demanded sense of the human
special care sensitive signals. This responsive system is
balanced and effectively instrumented with modern
technological learning pedagogy to bring the special need
learners into the normal learning system. In the learning
process, cognitive human sensors directly influence the
learning effectiveness. This paper attempted to observe the
cognitive load such as mental , physical , temporal
,performance , effort and frustration in the long term , short
term, working , instant , responsive, process, recollect ,
reference , instruction and action memory and classify the
observed values as per the generalized and specialized
properties. The six working loads are observed in the ten types
of learning system. The classification analysis aimed to
predicate the pattern for learning system for specific learning
challenges.
Abstract - Human learning system is highly sensitive to responsive system according the processing, mapping, motion, auditory and visualization system. Special education system is implemented to overcome the demanded sense of the human special care sensitive signals. This responsive system is balanced and effectively instrumented with modern technological learning pedagogy to bring the special need learners into the normal learning system. In the learning process, cognitive human sensors directly influence the learning effectiveness. This paper attempted to observe the cognitive load such as mental , physical , temporal ,performance , effort and frustration in the long term , short term, working , instant , responsive, process, recollect , reference , instruction and action memory and classify the observed values as per the generalized and specialized properties. The six working loads are observed in the ten types of learning system. The classification analysis aimed to predicate the pattern for learning system for specific learning challenges.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
2016-05-27 Venia Legendi (CEITER): Paul Seitlinger
1. The role of primary and secondary memory
in organism-environment dynamics
...
computa(onal modeling of accruing data in collabora(ve
learning scenarios
paul seitlinger
27. 05. 2016, tallinn
1
2. Outline of my research
• Knowledge building in open/self-directed learning seDngs
• Challenges from a psychological perspec(ve
– Organism-Environment dynamics
• Interplay of primary memory (scope and control of aIen(on) and
secondary (long-term) memory during reflec(on
– Secondary memory (SM): Integra(ng episodic memory (evolving in collabora(ve learning
seDng) into seman(c (pre-exis(ng) memory [1]
– Primary memory (PM): controlled use of contextual cues (environmental, internal) to
search secondary memory (interpreta(on, reflec(on) [1]
– Socio-cogni(ve processes/co-crea(on of environments
• How stabiliza(on (paIerned prac(ces, grounding) evolves and affects PM-
SM interplay
[1] Usworth, N. & Engle, R. (2007). The nature of individual differences in working memory capacity: Ac(ve maintenance in
primary memory and controlled search of from secondary memory. Psychological Review, 114, 104-132.
2
3. Outline of my research
• Observing socio-cogni(ve learning in Web environments
– Collabora(ve learning so`ware (school, university)
– Social informa(on systems (bookmarking, tagging, informa(on search)
• Making use of accruing datasets to validate models of socio-cogni(ve learning
• 3 studies by the example of social tagging
– Study 1: Field study (university course) about effects of seman(c
stabiliza(on on individual learning [2]
– Studies 2 and 3: Measurement and computa(onal modeling to shed light
on variables giving rise to stabiliza(on [3,4]
[2] Ley, T. & Seitlinger, P. (2015). Dynamics of human categoriza(on in a collabora(ve tagging system:
how social processes of seman(c stabiliza(on shape individual ssensemaking. Computers in
Human Behavior, 51, 140-151.
[3] Seitlinger, P., Ley, T. & Albert, D. (2015). Verba(m and seman(c imita(on inindexing resources on the
Web: a fuzzy-trace account of social tagging. Applied Cogni?ve Psychology, 29, 32-48.
[4] Seitlinger, P. & Ley, T. (2016). Reconceptualizing imita(on in social tagging: a reflec(ve search model
of human web interac(on. In P. Parigi & S. Staab (Eds.), Proceedings of the 8th Interna?onal ACM
conference on Web Science Conference (in press). New York: ACM press. 3
5. Study 1: Effects of seman(c stabiliza(on on individual learning
• N=24 students of a university course on cogni(ve models in TEL
– Social bookmarking system (SOBOLEO) to collect and tag Web resources
– Training phase to become familiar with purpose of tagging
• Manipula(ng stabiliza(on (λ) of tag vocabulary (high vs. low stabiliza(on)
– Low λ (n=12): ‘Old’ and interfering tags of training phase remain in the system
– High λ (n=12): Environmental switch
• Elici(ng individual learning: Performing an aIribute lis(ng task
– Lis(ng aIributes to general, medium, and specific tags (level of specificity)
• Basic-level shiN (e.g. [7])
• Hypothesis: Individuals of the high λ group gain more knowledge about medium
and specific tags than individuals of the low λ group.
[7] Close, J. & Pothos, E. (2012). “Object categoriza(on: Reversals and explana(ons of the basic-level advantage” (Rogers
& PaIerson, 2007): A simplicity account . Quarterly Journal of Experimental Psychology, 65, 1615-1632.
5
6. Study 1: Effects of seman(c stabiliza(on on individual learning
0 50 100 150
010305070
Consecutive tag assignments
Numberuniquetags
λ high
λ low
N = H * (1 – e-λt)
λ high = .009
λ low = .006
Stabiliza(on on group level: Higher
stabiliza(on in high than in low λ group
12345
Specificity
Numberlistedattributes
General Medium Specific
λ high
λ low
Individual learning: More knowledge about
medium and specific tags (basic-level shi`) in
high than low λ group
[2] Ley, T. & Seitlinger, P. (2015). Dynamics of human categoriza(on in a collabora(ve tagging system: how social
processes of seman(c stabiliza(on shape individual ssensemaking. Computers in Human Behavior, 51, 140-151.
F2,21 = 5.06, p < .05
6
7. Study 1: Effects of seman(c stabiliza(on on individual learning
• Stabiliza(on during collabora(on supports learning
– Tag-based (seman(c) priming inves(gated
by [6]
– Goals of studies 2 and 3: Revealing
interplay of remaining variables
• Study 2: Measuring i) contribu(ons of
PM-SM interplay and ii) impact of
intersubjec(vity on imita(on
• Study 3: Computa(onal model of
mechanisms underlying these variables
[6] Fu, W.-T., Kannampallil, T., Kang, R. & He, J. (2010). Seman(c imita(on in social tagging. ACM Transac?ons on
Computer-Human Interac?ons, 17, 12:1-12:37.
Tag
(contextual cue)
Search of memory
(PM-SM interplay)
Semantic priming
Reflection
(PM-SM interplay)
Intersubjectivity
Imitation
Semantic
stabilization
7
8. Study 2: Measuring the impact of intersubjec(vity on imita(on
• Web-based experiment
• 48 students conduc(ng an
informa(on search
• Incidental learning: Browsing
pictures (taken by famous
photographers; e.g., Henri Car(er-
Bresson) interpreted and
annotated by tag clouds
• Tagging phase: Re-exposed to
pictures to reflect on it and derive
own interpreta(ons and tag
assignments
• Frequency distribu(ons for the act of imita(ng (I) vs. not imita(ng (N) previously seen tags
• Analysis in terms of theore(cal constructs (e.g., PM, SM, intersubjec(vity) through
Mul(nomial Processing Tree (MPT) derived from Fuzzy-Trace Theory (e.g., [8])
[8] Brainerd, C. & Reyna, V. (2010). Recollec(ve and non-recollec(ve recall. Journal of Memory and Language, 63, 425-445. 8
9. Study 2: Measuring the impact of intersubjec(vity on imita(on
Automatic unloading
from PM
Reflective search
of memory
PM-SM interplay
Similar reflection
(Intersubjectivity)
1-S
Same tag choice
1-C
1
1-C
2
Imitation, VI
Web
resource
No Imitation, N
Imitation, I
D
1-D S
C
1
C
2 Imitation, I
No Imitation, N
Same tag choice
Different
reflection
[3] Seitlinger, P., Ley, T. & Albert, D. (2015). Verba(m and seman(c imita(on inindexing resources on the Web: a fuzzy-
trace account of social tagging. Applied Cogni?ve Psychology, 29, 32-48.
• Performing maximum likelihood es(ma(on to test model fit and quan(fy contribu(on of
cogni(ve processes
9
10. Automatic unloading
from PM
Reflective Search
of memory
PM-SM interplay
Similar reflection
(Intersubjectivity)
1-S=0.81
Same tag choice
1-C
1
=0.37
1-C
2
=0.97
Imitation, I
Web
resource
No Imitation, N
Imitation, ID=0.15
1-D=0.85 S=0.19
C
1
=0.63
Imitation, I
No Imitation, N
Same tag choice
C
2
=0.03Different
reflection
Model fit, G2(4)=0.78, n.s.
P(I)=0.10
P(I)=0.02
Probability
P(I)=0.15
Study 2: Measuring the impact of intersubjec(vity on imita(on
• PM-SM interplay crucial to model students’ interpreta(ons and annota(ons
• Intersubjec(vity (state of reflec(ve agreement) as a driving force behind imita(on
and thus, stabiliza(on
[3] Seitlinger, P., Ley, T. & Albert, D. (2015). Verba(m and seman(c imita(on inindexing resources on the Web: a fuzzy-
trace account of social tagging. Applied Cogni?ve Psychology, 29, 32-48.
10
12. Context Maintenance and Retrieval Model (CMR [9])
PM-SM interplay when reflec(ng on environmental objects
Article about
learning and
memory
“Brain” “Synapse”
“Kandel”
Item layer F
Context layer C
Context evolution (internal spotlight)
Episodic learning (integration of item-context associations into MFC
and MCF
MFC
MFC MFC
MCF
MCF MCF
Stream of thoughts triggered by environmental item
* PM: Turning environmental cues into context
** Using context to search SM
[9] Polyn, S., Norman, K. & Kahana, M. (2009). A context maintenance and retrieval model of organiza(onal processes in
free recall. Psychological Review, 116, 129-156.
*
**
12
13. Study 3: Applying CMR to model students’ reflec(ons on Web
resources as a PM-SM interplay
• CMR: A valid model of PM-SM dynamics
– Tested by a series of laboratory experiments on episodic learning (e.g., [9,10])
• RQs: Does PM-SM dynamics formalized by CMR allow for modeling
– peoples’ reflec(ons on Web resources?
– the effect of intersubjec(vity on seman(c stabiliza(on?
• RQs inves(gated in a large-scale social tagging system (Delicious)
– Dataset [11]: 1,685 tags for 49,691 Bookmarks of 2,003 Wikipedia ar(cles
from 1,968Users
• Tes(ng a CMR-specific hypothesis about stabiliza(on (consensual tag use)
• Simula(ng empirical paIerns by means of a CMR-based mul(-agent
simula(on (MAS)
[9] Polyn, S., Norman, K. & Kahana, M. (2009). A context maintenance and retrieval model of organiza(onal processes in free
recall. Psychological Review, 116, 129-156.
[10] Healey, M. & Kahana, M. (2016). A four component model of age-related memory change. Psychological Review, 123, 23-69.
[11] Zubiaga, A. (2009). Enhancing naviga(on on wikipedia with social tags. In Wikimania 2009. Wikimedia Founda(on, 2009.
13
14. Hypothesis: Decreasing intersubjec(vity during reflec(ons
F
C
F
C
F
C
F
C
Evolving spotlight
tag1
tag2
tag3
tag4
Tag assignment TAS
• TAS as a manifesta(on of
resource reflec(on (Study 2)
• Each search itera(on yields a
single tag (posi(on t) within
TAS
• Dri`ing spotlight hypothesis
• The longer we reflect, the more individualis(c the spotlight (internal context
state) should be
• Intersubjec(vity should decrease along consecu(ve search itera(ons t
(TAS posi(ons)
à Less imita(on and thus, seman(c stabiliza(on (consensual tag use)
at later TAS posi(ons
14
15. 0.40.50.60.70.80.91.0
Probabilitynewtag
Consecutive TAS
1 2 3 4 5 6 7 8 9 10
With each new TAS, the probability of a new
tag declines ~ Stabiliza(on
Web
resource
TAS
1
= {Kandel, brain, synapse, learning}
TAS
2
TAS
3
TAS
10
…
Micro dynamics
Macro
dynamics
TAS…Tag assignment
Indica(on of intersubjec(vity, implicit agreement on conceptualizing an object (e.g.,[12] )
Criterion: Seman(c stabiliza(on in a social tagging system
[12] S. Sen, S., Lam, S., Rashid, A., Cosley, D., Frankowski, D., Osterhouse, J., Harper, F. & Riedl, J. (2006). Tagging, communi(es,
vocabulary, evolu(on. In Proc. 20th anniversary conference on Computer Supported Coopera(ve Work (pp. 181- 190). ACM press. 15
17. …
…
MFC
MCF
1) Category combination of present Wikipedia article fi
3) Context evolution
ci
= ci-1
+ β*cIN
2) Context retrieval
cIN
= MFC
fi
4) Activation of
item layer
fIN
= MCF
ci
Semantic
Pre-exist.
Episodic
Evolving
(1 − !)!!"#
!"
+ !!!"#
!!
Study 3: Applying CMR to model students’ reflec(ons on Web
resources as a PM-SM interplay
• MAS
– Each agent behaves according to CMR model
1) Training phase based on a real user history (sequence of bookmarked ar(cles)
Developing individual stream of consciousness (episodic learning and spotlight evolu(on)
2) Tagging phase: All agents assign 4 tags to each of 10 further ar(cles
Semantic utility
based on reflection
u(w) = p(w|fIN
)
u’(w) = u(w)[1+s(w)]Φ
O E
Environmental salience
based on previous TAS
s(w) = p(w|fi
)
5)
• Gene(c algorithm
exploring parameter space
• 500 simula(on runs with
best-fiDng parameter set
[4] Seitlinger, P. & Ley, T. (2016). Reconceptualizing imita(on in social tagging: a reflec(ve search model of human web interac(on.
In P. Parigi & S. Staab (Eds.), Proceedings of the 8th Interna?onal ACM conference on Web Science Conference (in press). New York:
ACM press. 17
18. Study 3: Applying CMR to model students’ reflec(ons on Web
resources as a PM-SM interplay
0.40.60.81.0
Probabilitynewtagpnew(r,t)
Consecutive TAS r
Data
CMR
1 2 3 4 5 6 7 8 9 10
t = 1
0.40.60.81.0
Probabilitynewtagpnew(r,t)
Consecutive TAS r
Data
CMR
1 2 3 4 5 6 7 8 9 10
t = 3
0.40.60.81.0
Probabilitynewtagpnew(r,t)
Consecutive TAS r
Data
CMR
1 2 3 4 5 6 7 8 9 10
t = 4
• Model fit: χ2(29) = 13.74, χ2
crit=42.56
– CMR-based modeling of reflec(ng on resources
explains paIerns qualita(vely and quan(ta(vely
• Dri`ing spotlight hypothesis HDS
– Slope λ of pnew(r,t) along consecu(ve r decreases
with increasing t
Data CMR
pnew λ pnew λ
t = 1 .580 .093 .584 .089
t = 2 .639 .077 .633 .078
t = 3 .669 .069 .665 .069
t = 4 .708 .060 .700 .064
0.40.60.81.0
Probabilitynewtagpnew(r,t)
Consecutive TAS r
Data
CMR
1 2 3 4 5 6 7 8 9 10
t = 2
[4] Seitlinger, P. & Ley, T. (2016). Reconceptualizing imita(on in social tagging: a reflec(ve search model of human web interac(on.
In P. Parigi & S. Staab (Eds.), Proceedings of the 8th Interna?onal ACM conference on Web Science Conference (in press). New York:
ACM press. 18
19. Tag
(contextual cue)
Search of memory
(PM-SM interplay)
Semantic priming
Reflection
(PM-SM interplay)
Intersubjectivity
Imitation
Semantic
stabilization
Conclusion
• A valid model of peoples’ reflec(ons on Web resources
– PM-SM interplay (spotlight-driven search of memory)
• Precise predic(ons and modeling of stabiliza(on
– By implemen(ng result of study 2: Imita(on as an epiphenomenon of
intersubjec(vity (state of reflec(ve agreement)
• Studies 1-3 as a triangula(on of
• Field experiment: Iden(fying mutual
influences between observable variables on
group and individual
• Mul(nomial modeling of Web-based
experiments: Quan(fying contribu(ons of
latent variables to observable behavior
• Mul(-Agent Simula(on: Tes(ng assump(ons
on dynamics between mul(ple latent and
observable variables
19
20. Methodological implica(ons
• Collabora(ve learning scenario well captured by nonlinear organism-
environment dynamics
– No simple cause-effect rela(onships [13]
– Non-linear processes and mutual influences between variables
• Methodological approach
– Going beyond correla(onal analysis
– Computa(onal modeling
• Model-based simula(ons/predic(ons of system development
• Model-based representa(on and computa(on/analysis of
contextual informa(on about a student (temporal, seman(c,
social)
[13] Larsen-Freeman, D. Cameron, L. (2008). Research methodology on language development from a complex systems perspec(ve.
The Modern Language Journal, 08, 200-213.
20
21. Going beyond correla(onal analysis
• Advantage of computa(onal modeling
– Close to phenomena to be observed
• Distribu(on of informa(on through non-linear and itera(ve processes
– Intertwining theory and sta(s(cs
• Parameters directly represen(ng theore(cal constructs
– Independence of domain and data
• Fundamental mechanisms of
– learning (Hebbian learning of seman(c and episodic associa(ons)
– execu(ve func(ons (scope and control of aIen(on ~ Spotlight and spotlight-
driven search)
• should account for different behavioral data
– Self-directed naviga(on (forma(on of informa(on goals, meta-cogni(ve
processes/control)
» spotlight -> informa(on goal
» PM-SM interplay to account for meta-cogni(ve processes
– Crea(ve group cogni(on (trade-off between stabiliza(on and divergent
thinking)
» Interplay of aIen(on control and scope of aIen(on when re-combining
pre-exis(ng associa(ons
21
22. Contribu(ons to research infrastructure
• Summerschool on theory-driven analyses of human-web interac(ons
– Prof. Wai-Tat Fu (Partner in two currently running FWF projects)
• Department of Computer Science, University of Illinois at Urbana-Champaign
– Topic1: Computa(onal modeling of user behavior in crea(ve and self-directed learning
environments
– Topic 2: Design of crea(vely s(mula(ng recommenda(on mechanisms: „Escaping the
echo chamber“
• Summerschool on web-based experiments on „access to knowledge“
– Prof. Harry Bahrick (Partner in a current EU project proposal)
• Department of Psychology, Ohio Wesleyan University
– Topic: Applying MPTs to analyze learning in Web-based experiments
• Availability vs. Accessibility of knowledge
22