From Learning Standards to Smart Learning Environments: A view of the challenges of technology enhanced
learning
Miguel Rodríguez Artacho
Universidad Nacional de Educación a Distancia (UNED, Spain)
[email protected] Twitter: @martacho
Manila, 14 de Octubre de 2017
Why reshape education?
• New competences
• Knowledge needs are changing
• Life long learning
• New interactions and ways to learn
• New technologies
• …
Jean-Marc Côté
Traditional education
• Prussian model since the XIX century
• Few elements: Teacher, student and educational material
• Rigid schemas: enrolment, schedule, assessment
Education “ecosystem”
• Degree
• Academic year
• Subject
• Classroom
• Lecture
• Lecture notes
• Handouts
• Exam
This model is effective but…
• Group students by age
• Regular school periods and calendar
• Ideas and content structured in matters
• Strict ethics: discipline
• Competences in reading, writing and arithmetic
Educative innovations
• Interactive software environments
• Virtual and remote laboratories
• Animations and simulations
• Exercises platforms
• Mobile applications
• eBooks
• Social networks
LMS-based learning
• First integrated technology
enhanced learning
• Industry of e-learning
• E-learning standards
• Virtual mobility (e-portfolio)
• Quality assurance models
LMS-based authoring
• Focus on reusable resources
• Label resources with metadata tags
• Use of e-learning standards
• Authoring tools
Evolution of e-learning standards
Accesibilidad
EvaluaciónActividades/Contenido
Gestión
IMS Accesibility guidelines
IMS Addition to LIP
IMS Metadata extensions
IMS QTI
IMS QTI results
IMS Content Packaging
ADL SCORM 2004
IMS Learning Design
IMS Simple Sequencing
ADL SCORM 1.3
ISO SC36/WG2 Collab. Learning
Inf. estudiante
LIP
IMS ePortfolio
iCOPER PALO
European Learner Mobility (ELM)
IMS Enterprise
IMS DRM
IMS DR
Metadata
IEEE LOM
IMS Metadata
Dublin Core
CanCore
AEN/SC36 LOM Perfil de aplicación
2000
2010
• From package to open content
• From local content to semanticsearch for suitable content
• OER + Linked data
New e-learning standards
Activity example
<john> <launched> <cool book>
<john> <read> <page 1> ( d: "PT45S" ) { p: ["chapter 1"], g: ["cool book", "cool class"] }
<john> <read> <page 2> ( d: "PT15S" ) { p: ["chapter 1"], g: ["cool book", "cool class"] }
<john> <read> <page 3> ( d: "PT55S" ) { p: ["chapter 1"], g: ["cool book", "cool class"] }
<john> <read> <page 4> ( d: "PT45S" ) { p: ["chapter 1"], g: ["cool book", "cool class"] }
<john> <watched> <video 1> ( d: "PT3M" ) { p: ["page 4"], g: ["chapter 1", "cool book", "cool
class"] }
<john> <paused> <video 1> { p: ["page 4"], g: ["chapter 1", "cool book", "cool class"] }
<john> <resumed> <video 1> { p: ["page 4"], g: ["chapter 1", "cool book", "cool class"] }
<john> <watch> <video 1> ( d: "PT2M" ) { p: ["page 4"], g: ["chapter 1", "cool book", "cool class"]
}
<john> <completed> <video 1> ( d: "PT5M" ) { p: ["page 4"], g: ["chapter 1", "cool book", "cool
class"] }
<john> <read> <page 5> ( d: "PT45S" ) { p: ["chapter 1"], g: ["cool book", "cool class"] }
Authoring issues
• E-learning Standards are complex
• Complex authoring tools
• 2 examples:• Instructional ontologies and Educational Modelling Languages
• Inferring new relationships in educational content
Dublin Core
• Semantic framework
• Interoperability of resources
• Simple model
• Widely used in the WWW and other industries
24
RDF
Resource Description Framework
• Representing information about web resources
• Provides a “meaning” to resources
• Suitable for software processing
• Described using XML
26
Ej. RDF
http://www.example.org/index.html tiene un creador cuyo
valor es John Smith
ex:index.html dc:creator “John Smith,#4545534"
creatorhttp://www.example.org/ind
ex.html John Smith
http://www.example.org/index.html has a creator
named John Smith
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf=http://www.w3.org/1999/02/22-rdf-syntax-ns#
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:exterms="http://www.example.org/terms/">
<rdf:Description rdf:about="http://www.example.org/index.html">
<dc:creator rdf:resource="http://www.example.org/staffid/4545534"/>
</rdf:Description>
</rdf:RDF>
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<?xml version="1.0"?>
<rdf:RDF xmlns:rdf=http://www.w3.org/1999/02/22-rdf-syntax-ns#
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:exterms="http://www.example.org/terms/">
<rdf:Description rdf:about="http://www.example.org/index.html">
<dc:creator rdf:resource="http://www.example.org/staffid/4545534"/>
</rdf:Description>
</rdf:RDF>
RDF
http://www.example.org/index.html has a creator
named John Smith
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Semantic authoring
Cognitive Design
Model
Learning Design
Model
Conceptualization level
Ontologies
Instructional templates
Instantiation level
LT specificationbased content
Instances
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SW-based authoring
…Here you can find more<relation Name="Illustrates"Domain="Conceptual"Subject="invariant"Category="Example">examples</relation>of the concept invariant. …
33
Example #2: Semantic inference of educational material
sun_java:'java/concepts/class.html'[ rdf:type->doc:Document; dc:subject->doc:OO_Class].
doc:OO_Class[ rdf:type->doc:Concept; doc:isPrerequisiteFor->doc:OO_Inheritance; doc:subConceptOf->doc:Classes_and_objects].
doc:ClassesIntroduction[ rdf:type->doc:ConceptRole; doc:isPlayedBy->doc:OO_Class; doc:isPlayedIn->sun_java:'java/concepts/class.html'; doc:hasType->doc:Introduction].
doc:Introduction[ rdf:type->doc:ConceptRoleType; doc:subConceptRoleOf->doc:Cover].
Semantic inference
FORALL D,E weaker_example(D,E) <-
studyMaterial(D) AND example(E)
AND
EXISTS C (D[dc:subject->C] AND E[dc:subject->C]).
Weak example
• E and D are semantically labelled resources for education.
• E is an example (weak) for D if there is a C
Source: Nicola Hence et al. (2004) “Reasoning and Ontologies for Personalized E-Learning
in the Semantic Web” in Journal of Educational Technology and Society
Teacher
Educationalmaterial
Student
Profesor
Material Educativo
Estudiante
Teacher
EducationalMaterial
Student
New frontiers in education
• How to break down barriers
• Nothing from the past is useful? What can we keep?
• What are the new models
• New reference frameworks
• New ecosystem for education
MOOCs
Can’t see the woods for the trees
NON relevant questions:
¿business model?
¿Why only 2-7% finish the course?
¿Why are free?
…
MOOCs are not a panacea
MOOCs
• Massive Open Online Courses
• First success model for distance education
• Worldwide adopted in many educational institutions
• More adapted to post-industrial needs
Example: New schemas for new times
• Content of the book: from cascade to agile software development
• Book production: from traditional publisher to DIY
• Teaching model: from traditional class to MOOC and SPOC
Source: “Refactorizando la Educación” (2015) Carlos D. Kloos
Book production
• Traditional publisher
• Publisher printing
• Traditional marketing and distribution
• Slow cycles and not agile re-print
• Expensive
• Not adapted to demand
• DIY model: Do it Yourself
• LaTeX + GitHub
• Print on demand
• Print and electronic editions
• Faster cycle
• Adapted to demand
Enriched teaching resources: MOOC
http://www.saasbook.info/courses
Awesome feedback!
New learning interactions
• Formal vs. Informal learning including Higher Education
• Modularization of content https://micromasters.mit.edu
• New industries and new jobs mismatch between educational programs and current jobs
IKEA, GOOGLE training programs
• Peer to peer education
• Non centralized environments
• Knowledge generated in microsocial interactions
• Social networks as educationaltools
Social learning
• Not in the traditional ITS model
• Coacher, not teacher
• Emotive computing
• Reputation
• Context
Smart Learning Environments
Reshaping AI in Education
• Not restricted to formal learning
• Autonomous and adaptive learning just-in-time
• More than a VLE: learning guidance, hints, supportive tools
• Personal factors into account
• Multiple channels: IoT, ubiquitous computing devices, wearable computing
Smart learning environments
• Context to provide relevant information
• Presentation of information, service. Tagging of context to information
• Student achievements
• Real world: IoT and wearables
SLE: Full context awareness
• Tailor instruction to individual needs
• Collect data from disparate sources (physical, online,..)
• Inference of learning requirements
SLE: Big Data and Learning Analytics
• Emotive computing
• Dynamic adaptivity
• Autonomous pedagogical decission
• Learning support across contexts
• Personal factors into account
• Recommends learning tools and strategies
SLE: Autonomous decision making
Pedagogical innovations
• Knowledge generated from micro-social interactions
• Change in assessment practices
• Learning in ubiquitous environments: virtual and physical integration
• Real-time intervention in the learning process
Technological innovation
• Flipped classroom: combining models
• MOOCs: Open, free access, flexible, peer-to-peer
• Game-Based learning: engagement, richer interactions
• Augmented and virtual reality
• Educational robots
• Gesture-Based learning
— ”Everything needs
to change, so
everything can stay
the same.”
Giuseppe Tomasi di
Lampedusa
“The Leopard”
From Learning Standards to Smart Learning Environments: A view of the challenges of technology enhanced
learning
Miguel Rodríguez Artacho
Universidad Nacional de Educación a Distancia (UNED, Spain)
[email protected] Twitter: @martacho
Manila, 14 de Octubre de 2017
Thank you!