Repercussions of Semantic Interactionwith Open Educational Resources in the Student Virtual Identity andin Online Learning Environments

1. Cecília Tomás
Mentor: Professor Doctor António Teixeira
Presentation for the degree of Master in Education
2014

2. 2

3. Introduction
3

4. General theme
Semantic
dimension and its
customizability
@ceciliatomas Introduction
The paradigm
shift in the light of
web 3.0
Specific theme
4

5. 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)
@ceciliatomas Introduction
The discovery of the human being as a self
(si-mesmo) through narrative connectivity
5

6. 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.
@ceciliatomas Introduction
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;
GOALS
6

7. 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

8. Literature Review
Part I
8

9. Social Web
Semantic Web
General Usabilities
Educational Usabilities
Virtual Learning Environments
Person and Technology
Customization
@ceciliatomas I. 9

10. 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

11. 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

12. 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

13. 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

14. http://steve-wheeler.blogspot.co.uk
+ analytic learning
I. 3.@ceciliatomas 14

15. Analytic
Learning
Rhizomathic
Learning
More
customized
PLEs
Closed learning systems
increasingly open and pluralistic environments
www.therabbithole.fr
I. 3.@ceciliatomas 15

16. I. 4.@ceciliatomas 16

17. “Thoughts without content are empty;
intuitions without concepts are blind”
Immanuel Kant
Technology Human Sciences
Ethical
Technophile
I. 4.@ceciliatomas 17

18. Case Study
Part II
18

19. Case Study
Documental
Analysis
Asynchronous
Interview
Intrinsic
Case
Study
PERSONALIZATION
II. 1.@ceciliatomas 19

20. Social Web Semantic Web
OER
II. 2.@ceciliatomas 20

21. "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

22. “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.compt.websense.com
22

23. SEMANTIC SOCIAL
23II. 3.@ceciliatomas

24. “Acceso desde una sola herramienta a los recursos
producidos en diferentes instituciones, idiomas, áreas de
conocimiento y regiones.”
Piedra, Nelson. Entrevista assíncrona. Abril 2013
I. 1.II. 4.@ceciliatomas
“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

25. “El enriquecimiento de datos desde otras fuentes como
repositorios y bases de datos de material científico.”
Piedra, Nelson. Entrevista assíncrona. Abril 2013
I. 1.II. 4.@ceciliatomas
“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. 26II. 4.@ceciliatomas

27. La aplicación de las tecnologías semánticas
puede conseguir un efecto sinérgico para
ofrecer entornos de aprendizaje
personales.
Piedra, Nelson. Entrevista assíncrona. Abril 2013
I. 1.II. 4.@ceciliatomas
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

28. entorno, determinar su significado y generar
nuevos datos mediante reglas lógicas.”
Piedra, Nelson. Entrevista assíncrona. Abril 2013
I. 1.II. 4.@ceciliatomas
“(...) cierta capacidad de
entendimiento podrá ser asumida
por las máquinas para interpretar
los datos que reciben del
28

29. 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
Piedra, Nelson. Entrevista assíncrona. Abril 2013
29

30. 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
Piedra, Nelson. Entrevista assíncrona. Abril 2013
30

31. Conclusions
31

32. Personal Identity
Openness
Share
Collaboration
mckikvenarron.wordpress.com
Automation
Personalization
Narrative Identity
@ceciliatomas
conceptart.ca
conclusions 32

33. 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

34. @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

35. Thank you
cecilia1976@gmail.com
cecilia.tomas.75
ceciliatomas
@ceciliatomas