SEMANTIC WEB and PERSONALIZATION

Cecília Tomás

Mentor: Professor Doctor António Teixeira

Presentation for the degree of Master in Education

2014

Introduction

3

General theme

Semantic

dimension and its

customizability

@ceciliatomas Introduction

The paradigm

shift in the light of

web 3.0

Specific theme

4

The separation and the interdependence,

between the social and the semantic web

The ability or level of personalization that

can lead a person to achieve aided by

the machine as instrument (extension or

addition to its capacity)


The discovery of the human being as a self

(si-mesmo) through narrative connectivity

5

4) Identify concepts

rediscovered with the

semantic web - such as

VLE, PLE, MOOC or OER;

5) Establish personalization

as a result of the Semantic

Web through the rhizome

and analytical models

from the connectivist

epistemology;

6) Advocate technology as

an instrument of

humanization.


1) Identify the differences

between the social and

semantic web;

2) Characterize the

narrative identity

recovered by the notion

of instrumentality and the

human responsibility;

3) Analyse the possibility of

technology being

extension and / or

addition to human

capabilities;

GO

ALS

6

Part I

1. Perception Levels of Web Connectivity

2. Semantic Usability

3. Virtual Learning Environments and eLearning

4. Person and Technology

@ceciliatomas

Part II

1. Research Methodology

2. Contextualization of the Case Study

3. Serendipity, the Semantic Search Engine

4. The Qualitative Data Analysis

7

Literature Review

Part I

8

Social Web Semantic Web

General Usabilities

Educational Usabilities Virtual Learning Environments

Person and Technology

Customization @ceciliatomas I. 9

I have a dream for

the Web... and it

has two parts. In

the first part, the

Web becomes a

much more

powerful means

for collaboration

between people. Berners-Lee, Tim (1998)

I. 1. @ceciliatomas

www.dmconfidential.com

10

How to manage

dispersion?

search

quality

utility

There are so much

information, data,

tools… in the WEB...

I. 1. @ceciliatomas

https://www.flickr.com/photos/kasei/4750370030

11

In the second part of the dream,

collaborations extend to computers.

Machines become capable of analyzing

all the data on the Web - the content,

links, and transactions between people

and computers.

I. 1. @ceciliatomas

www.dmnews.com

Semantic Web

Web 3.0

Linked Data

Berners-Lee, Tim (1998)

OpenData

Big Data

IoT

12

http://www.cienciahoje.pt

Search engines and

mechanisms of

intelligent

georeferencing will be,

in the near future, the

basis of human

knowledge acquisition

and tracking behavour

(objects and people)

http://www.brandstories.net/

I. 2. @ceciliatomas

Virtually obsolete

resources are

transformed into living

materials allowing its

reuse more easily.

Finding new ways of

learning by the creation

of personalized

environments

facultyecommons.org

13

http://steve-wheeler.blogspot.co.uk

+ analytic learning

I. 3. @ceciliatomas 14

Analytic

Learning

Rhizomathic

Learning

More

customized

PLEs

Closed learning systems

increasingly open and pluralistic environments

www.therabbithole.fr


“Thoughts without content are empty;

intuitions without concepts are blind” Immanuel Kant

Technology

Human Sciences

Ethical

Technophile


Case Study

Part II

18

Case Study

Documental

Analysis Asynchronous

Interview

Intrinsic

Case

Study

PERSONALIZATION

II. 1. @ceciliatomas 19

Social Web Semantic Web

OER II. 2. @ceciliatomas 20

"Open Educational Resources (OER) are a direct

reaction to knowledge privatization;

they foment their exchange to the entire world

with the aim of increase the human intellectual

capacity."

In Piedra, N. Chicaiza, J. López, J. Tovar, E. and Martínez, O. (2009) Open

Educational Practices and Resources based on Social Software, Utpl Experience

II. 3. @ceciliatomas 21

“Social and semantic web can be

complementary approaches searching web

resources. This cooperative approach lets

enable a semantic search engine to find

accurate results and annotate web resources.”

In Piedra, N. Chicaiza, J. López, J. Tovar, E. and Martínez, O. (2011 )

Finding OERs With Social-Semantic Search in Global Engineering Education Conference

I. 4. II. 3. @ceciliatomas

webcodefree.blogspot.com pt.websense.com

22

SE

MA

NT

IC

SOCIAL

23 II. 3. @ceciliatomas

“Acceso desde una sola herramienta a los recursos

producidos en diferentes instituciones, idiomas, áreas de

conocimiento y regiones.”

Piedra, Nelson. Entrevista assíncrona. Abril 2013


“La interfaz de búsqueda, basada en palabras clave, es la

forma habitual con la que están familiarizados los

usuarios.”

“Ofrece búsqueda entre categorías o facetas, esto facilita

la navegación y el filtrado de resultados.”

Advantages from Serendipity

24

“El enriquecimiento de datos desde otras fuentes como

repositorios y bases de datos de material científico.”



“La recuperación de recursos multilingüe.”

“Personalización de la experiencia de usuario, para

ello se están diseñando algunos servicios de

recomendación y de acceso personalizado.”

“(...) estamos trabajando en una herramienta de visualización

de datos (http://serendipity.utpl.edu.ec/map), y estamos

desarrollando prototipos de aplicaciones móviles OCW en

Android y iOS.”

Challenges created by the use of Serendipity

25

26 II. 4. @ceciliatomas

La aplicación de las tecnologías semánticas

puede conseguir un efecto sinérgico para

ofrecer entornos de aprendizaje

personales.



Refinamiento y filtrado

avanzado de recursos

Respuestas más

completas, directas y

precisas de acuerdo al

perfil del usuario.

Mecanismos de

navegación fáciles de

usar

27

entorno, determinar su significado y generar

nuevos datos mediante reglas lógicas.”



“(...) cierta capacidad de

entendimiento podrá ser asumida

por las máquinas para interpretar

los datos que reciben del

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II. 4. @ceciliatomas

objetivo de reducir el esfuerzo que un

profesor o un estudiante tendrían que

invertir para realizarlas.”

“(...) procesos y tareas

educativas intensivas en datos y

requerimientos de procesamiento

podrían automatizarse, con el


29

II. 4. @ceciliatomas

estudiantes adquirir competencias para

desempeñarse en el ámbito laboral y los

agentes recomendar rutas de aprendizaje

según las características de cada usuario.”

“(...) las personas y las máquinas,

cada uno, haga lo que mejor sabe

hacer. Así, las profesores tutelar el

proceso de aprendizaje, los


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Conclusions

31

Personal Identity

Openness Share

Collaboration

mckikvenarron.wordpress.com

Automation

Personalization

Narrative Identity

@ceciliatomas

conceptart.ca

conclusions 32

Research Limitations

1. The inability to adequately develop a reflection about

the shift paradigm theme by temporal and conceptual

limitations related to the type of investigation in

question.

2. Many of the considerations made in theoretical terms

are still, in practice, in an embryonic state or are

manifestations of future perspectives.

3. Density of the technical language that leaves

submerged some interpretations and intersections

between fields (technology and education, economics,

politics, and so on).

@ceciliatomas conclusions 33

@ceciliatomas

Perspectives Opened by the Study

1. Continue the investigation about the social - semantic

Web envisaging developments (as in IoT).

2. Put itself in the plane of the consequences trying to find

ideas about ways followed by humans.

It is expected that the path of human

evolution will, certainly, be a path followed

by the smart technology ... Or not?...

conclusions 34

Thank you

[email protected]

cecilia.tomas.75

ceciliatomas

@ceciliatomas

SEMANTIC WEB and PERSONALIZATION

Education

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