development of a trans-field learning system based on multidimensional topic maps
Post on 20-Jun-2015
580 Views
Preview:
DESCRIPTION
TRANSCRIPT
Development of a Trans-Field Learning SystemBased on Multidimensional Topic Maps
Shu Matsuura
Tokyo Gakugei University, Faculty of Education
An online learning system: “Everyday Physics on Web”
supported by Naito-san.
• To associate knowledge in a wide variety of To associate knowledge in a wide variety of fieldsfields
subject: Physics, Chemistry, Biology, Earth Sicence, subject: Physics, Chemistry, Biology, Earth Sicence, Astronomy, Environment, Sustainability, Industory, Astronomy, Environment, Sustainability, Industory, Aritifact, Daily Life, Policy, History of Science,,,Aritifact, Daily Life, Policy, History of Science,,,
• For informal learning and for self-learning ( of For informal learning and for self-learning ( of students, teacher,,,).students, teacher,,,).
• Topic Maps application server: Ontopia Topic Maps application server: Ontopia Navigator FrameworkNavigator Frameworkat http://tm.u-gakugei.ac.jp:8080/epw/at http://tm.u-gakugei.ac.jp:8080/epw/Thanks to open-source Ontopia.Thanks to open-source Ontopia.
Photo topic link with http://psi.garshol.priv.no/tmphoto/ by TMRAP.
This site started on Sep. 2009.
Change from Course-centric to Subject-centric
Course-centric portal for online learning Course-centric portal for online learning (<2007)(<2007)
- easy to start course learning- easy to start course learning- fragmented knowledge- fragmented knowledge
- restrict the range of learning - restrict the range of learning
Subject-centric, Subject-centric, association-centric portalassociation-centric portalOne can start with any One can start with any topic, and recorded and topic, and recorded and evaluated. (<2009)evaluated. (<2009)
Topic map based Topic map based trans-field learning portaltrans-field learning portalfor informal learning.for informal learning.
position and displacementposition and displacement
velocityvelocity
accelerationaccelerationaccelerationacceleration
inertiainertiainertiainertia
a = f/ma = f/ma = f/ma = f/m
momentummomentummomentummomentum
action, action, reactionreactionaction, action,
reactionreaction
normal forcenormal forcenormal forcenormal force
frictionfrictionfrictionfriction
workworkworkwork
position and displacementposition and displacement
velocityvelocity
accelerationaccelerationaccelerationacceleration
inertiainertiainertiainertia
a = f/ma = f/ma = f/ma = f/m
action, action, reactionreactionaction, action,
reactionreaction
normal forcenormal forcenormal forcenormal force
frictionfrictionfrictionfriction
workworkworkworkDistributed knowledgeis_based_on associationDistributed knowledgeis_based_on association
Sequential learningpreceding_following associationSequential learningpreceding_following association
Associations of knowledge is not in a straight line.
1. Avoid fragmentation of knowledge
CourseCourse
Learning ResourceLearning Resource
Learning RecordLearning Record
Course-centricCourse-centricLearning ManagementLearning ManagementSystemSystem
Course-centricCourse-centricLearning ManagementLearning ManagementSystemSystem
• learning order assoc.learning order assoc.• intra-field assoc.intra-field assoc.• inter-field assoc.inter-field assoc.
Our Our Topic Maps-DrivenTopic Maps-DrivenPortalPortal
Our Our Topic Maps-DrivenTopic Maps-DrivenPortalPortal
Course-centric LMS tends to restrict the range of study.
Topic maps-driven learning system will be appropriate to free-style self-learning.
“Courses” are embedded into theassociation “preceeding_following”.
“Subjects” are embedded in the course.
Radar chart of number of learning recordson 5 fields of physics for individual learner
z 方向
“a learning vector” : L = nieri + Nez
An index a for the anisotropy of learning found in the radar chart.
a = |nieri| / N
eri is the unit vector of i’th fieldni is the number of learning records on i’th field
Anisotropy of learning vs. amount of request of individuals
aniostropy index a
a = |nieri| / NN
a
Filled black circle ●: course-centric portal used.
- Students who have large amount of request showed broader range of the anisotropy.- Students who have small amount of request showed relatively high anisotropy.
using topic maps portal (○, , □)△ :
→ Variation in the ways of learning appeared through the repetition of study.
Text on Text on “force”“force”
Text learning Text learning record record on “force”on “force”
is_subject of_ResourceText
is_subject of_TextLearningRecord
““Force” Force” subjectsubject
subject asubject a
subject bsubject b
is_based on
A Portal forA Portal for
Field Subject δ
Field Subject δ
Learning Resource layer
Learning Record layer
subject a1subject a1
subject a2subject a2
subject b1subject b1
subject b2subject b2
sub-field asub-field a
Subject Space
Field Subject αField Subject αField Subject γField Subject γ
sub-field bsub-field b
Field Subject β
Field Subject β
Inter-Field Subject Association
Fields: Physics, Chemistry, Biology, Earth Science, Astronomyenvironment, sustainability, daily life, history, policy, history
Taxonomy of topic types.Taxonomy of topic types.
Tracing up and down the hierarchy, one can find out sub-Tracing up and down the hierarchy, one can find out sub-domains to explore.domains to explore.
Types of associations inside the fields look to reflect the Types of associations inside the fields look to reflect the characteristics of the field.characteristics of the field.
Intra- and Inter-field subject association.Intra- and Inter-field subject association.
Tracing the associations between topic instances is another Tracing the associations between topic instances is another way to explore subjects.way to explore subjects.
subject a1
subject a1
a3a3 a2a2
a4a4
subject b1
subject b1
b2b2 b3b3
b4b4
subject c1
subject c1
c4c4
c3c3
c2c2
Field αField α
Field Field ββField Field ββField γField γ
trans-field associations
retrieved topic
Image of a possible visualized interfacefor trans-field association.
Our present page for an instance topic:type hierarchy structure + associated topics & their occurrences.
At present:
An example of topic instance page
Google Earth, Map & YouTube as occurrences of the topic instance.
Light scatteringLight scattering
Mie theoryMie theory
Tyndal 現象Tyndal 現象
Dispersed system
Dispersed system
Properties of matter
Properties of matter
Colloidal phenomena
Colloidal phenomena
Atmospheric science
Atmospheric science
Atmospheric optics
Atmospheric optics
Crepuscular rayCrepuscular ray
PhysicsChemistryEarth Science
• “Tyndal effect” is positioned in three context coordinates.• Due to the consistency of topics, topic instance cannot be duplicated.• Knowledge of Tyndal effect will be refined through understanding in the multiple fields.Tyndal 現象Tyndal 現象Tyndal
effectTyndal effect
A shared topic
physics axisphysics axis
chemistry axischemistry axis
earth science axisearth science axis
Light scattering
Light scattering
Mie theory
Mie theory
Dispersed system
Dispersed system
Colloidal phenom
enaColloidal
phenomena
Atmospheric science
Atmospheric science
Atmospheric optics
Atmospheric optics
Crepuscular ray
Crepuscular ray
Tyndal effectTyndal effect
Tyndal effect
Tyndal effect
Tyndal effectTyndal effect
Tyndal effect
Tyndal effect
A multidimensional representation of a shared topic
subject a1
subject a1
a3a3a2a2
a4a4
subject a1
subject a1
b2b2b3b3
b2b2
subject a1
subject a1
c4c4
c3c3
c2c2
Field αField α
Field Field ββField Field ββField γField γ
subject a1
subject a1
subject a1
subject a1
A topic shared by 3 fields
A shared topic is located at several corresponding fields.
subjec
t a1su
bject a1
b2b2
b3b3
b2b2
subject a1
subject a1
c4c4
c3c3c2c2
subject a1
a3a3a2a2
a4a4
Field αField α
Field Field ββField Field ββ
Field γField γ
An image of possible visualized interfacefor multidimensional association.
“covalent bond”?
subjec
t a1su
bject a1
b2b2
b3b3
b2b2
subject a1
subject a1
c4c4
c3c3c2c2
subject a1
a3a3a2a2
a4a4
Field αField α
Field Field ββField Field ββ
Field γField γ
Making fine structure around a topic, by adding a micro topic map
a “micro” topic mapthat has common topicswith main map.
Connect a micro topic map to the main mapin the application (not merging maps).
a3a3
a2a2
Work
Elementary Def. of Work
Scalar Force
Distance
Fundamental Def. of Work
Generalized Def. of Work
Is defined by
Is a function of
Vector Force
Displacement
multiplication
Scalar Product
Integral
uses operation of
A micro topic map of the definition of “Work” at three levels of generalization.
Instruction Scenario
Introductive Experiment
Introductive Experiment
QuestionsQuestions
Experimental Evidence
Experimental Evidence
UnderstandingUnderstanding
precedesQuestion topicsQuestion topics
Basic Physics Subject
Basic Physics Subject
Basic Chemistry Subject
Basic Chemistry Subject
Daily Life Subject
Daily Life Subject
Physics Experiment
Physics Experiment
Scenario Type topicsScenario Type topics
An example of instruction scenario topic map with hands-on experiments.Knowledge topics and experiment topics are applied to a scenario type.
1.1. Multiple-subject topic maps for science and technology Multiple-subject topic maps for science and technology fields were introduced, and trans-subject associations fields were introduced, and trans-subject associations were used to interlink topics in different fields.were used to interlink topics in different fields.
2.2. We discussed a multidimensional character of this topic We discussed a multidimensional character of this topic map system.map system.
3.3. Two types of micro-topic maps were created and linked Two types of micro-topic maps were created and linked with the main multidimensional map by using identical with the main multidimensional map by using identical subject identifiers for common topics.subject identifiers for common topics.
4.4. It was suggested that topic maps for various purposes It was suggested that topic maps for various purposes could be created flexibly, using the main multi-field could be created flexibly, using the main multi-field subject topic map as a knowledge base.subject topic map as a knowledge base.
Concluding remarks.
top related