1. The document proposes a trans-field learning system based on multidimensional topic maps to associate knowledge across various fields like physics, chemistry, biology, and more for informal learning. 2. It describes moving from a course-centric to subject-centric approach using topic maps to allow learners to start with any topic and see related knowledge without restrictions. 3. Examples of micro-topic maps are given to show finer details on topics like the definition of work at different levels, and an instruction scenario map linking knowledge and experiment topics.

1. Development of a Trans-Field Learning System Based on Multidimensional Topic Maps Shu Matsuura Tokyo Gakugei University, Faculty of Education

3. Photo topic link with http://psi.garshol.priv.no/tmphoto/ by TMRAP. This site started on Sep. 2009.

4. Change from Course-centric to Subject-centric Course-centric portal for online learning (<2007) - easy to start course learning - fragmented knowledge - restrict the range of learning Subject-centric, association-centric portal One can start with any topic, and recorded and evaluated. (<2009) Topic map based trans-field learning portal for informal learning.

5. Distributed knowledge is_based_on association Sequential learning preceding_following association Associations of knowledge is not in a straight line. 1. Avoid fragmentation of knowledge position and displacement velocity acceleration inertia a = f/m momentum action, reaction normal force friction work position and displacement velocity acceleration inertia a = f/m action, reaction normal force friction work

7. Radar chart of number of learning records on 5 fields of physics for individual learner z 方向 “ a learning vector” ： L =  n i e ri + N e z An index a for the anisotropy of learning found in the radar chart. a = |  n i e ri | / N e ri is the unit vector of i’th field n i is the number of learning records on i’th field

9. Text on “force” Text learning record on “force” is_subject of_ResourceText is_subject of_TextLearningRecord “ Force” subject subject a subject b is_based on A Portal for

10. Fields : Physics, Chemistry, Biology, Earth Science, Astronomy environment, sustainability, daily life, history, policy, history Field Subject δ Learning Resource layer Learning Record layer subject a1 subject a2 subject b1 subject b2 sub-field a Subject Space Field Subject α Field Subject γ sub-field b Field Subject β Inter-Field Subject Association

11. Taxonomy of topic types. Tracing up and down the hierarchy, one can find out sub-domains to explore.

12. Types of associations inside the fields look to reflect the characteristics of the field. Intra- and Inter-field subject association. Tracing the associations between topic instances is another way to explore subjects.

14. subject a1 a3 a2 a4 subject b1 b2 b3 b4 subject c1 c4 c3 c2 Field α Field β Field γ trans-field associations retrieved topic Image of a possible visualized interface for trans-field association.

15. Our present page for an instance topic: type hierarchy structure + associated topics & their occurrences. At present:

16. An example of topic instance page Google Earth, Map & YouTube as occurrences of the topic instance.

18. physics axis chemistry axis earth science axis Light scattering Mie theory Dispersed system Colloidal phenomena Atmospheric science Atmospheric optics Crepuscular ray Tyndal effec t Tyndal effect Tyndal effect Tyndal effect A multidimensional representation of a shared topic

19. subject a1 a3 a2 a4 subject a1 b2 b3 b2 subject a1 c4 c3 c2 Field α Field β Field γ subject a1 subject a1 A topic shared by 3 fields A shared topic is located at several corresponding fields.

20. a3 a2 a4 Field α Field β Field γ An image of possible visualized interface for multidimensional association. “ covalent bond”? subject a1 b2 b3 b2 subject a1 c4 c3 c2 subject a1

21. a3 a2 a4 Field α Field β Field γ Making fine structure around a topic, by adding a micro topic map a “micro” topic map that has common topics with main map. Connect a micro topic map to the main map in the application (not merging maps). a3 a2 subject a1 b2 b3 b2 subject a1 c4 c3 c2 subject a1

22. 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.

23. Instruction Scenario Introductive Experiment Questions Experimental Evidence Understanding precedes Question topics Basic Physics Subject Basic Chemistry Subject Daily Life Subject Physics Experiment Scenario Type topics An example of instruction scenario topic map with hands-on experiments. Knowledge topics and experiment topics are applied to a scenario type.