Assisting E-Learning Initiatives with KM and Social Computing Tools

1. Assisting E-Learning Initiatives with KM and Social Computing Tools Jim Disbrow, SICoP Fifth Semantic Interoperability for E-Government Conference October 10-11, 2006 MITRE Mclean, Virginia Slide 1

2. Problems • The WWW is full of information that is not readily understandable to machines (robots), so we are building tools that lead to this. • The change to powerful tools will offer the advantages of speed, breadth and depth of the “best available” “trusted” knowledge. • The current web has limited power to supply “trusted” E-Learning. Slide 2

3. Assisting E-Learning Initiatives with KM and Social Computing Tools • Does a unifying concept exist for KM? • How do we use KM to automate the construction of large-scale knowledge bases? • How has this knowledge base been constructed? • What do we do to cope with the "critical mass" and "complexity" issues? • When do we apply KM and knowledge bases to E-Learning? • What do we look forward to in Social Computing Tools? • Applying Social Computing Tools to E-Learning Slide 3

4. Does a unifying concept exist for KM? According to Edward O. Wilson, a unifying concept exists: Consilience (the word means "a jumping together," in this case of the many branches of human knowledge), a wonderfully broad study that encourages scholars to bridge the many gaps that yawn between and within the cultures of science and the arts. No such gaps should exist –The sciences, humanities, and arts have a common goal: to give understanding a purpose, "a conviction, far deeper than a mere working proposition, that the world is orderly and can be explained by a small number of natural laws." All subjects of human inquiry can be reunited under the umbrella of "Consilience." Slide 4

5. What supports this idea? The "National Science Education Standards", (1996, National Academy Press, ISBN 0-309-05326-9) identifies energy as central to "unifying concepts in science". These standards were prepared by the National Research Council of the National Academies of Science, Engineering and Medicine. See: http://www.nap.edu/readingroom/books/nses/html/6b.html Slide 5

6. How do we use KM to automate the construction of large-scale knowledge bases? The Energy Community vkwiki is one of several SICoP Pilot Projects. Common natural language terms are used systematically. See: http://vkwiki.visualknowledge.com How is the Energy Community distinctive? Just as chairs are stable when they have four legs, all life (including all sectors our economy) is stable only with plentiful natural resources, available capital, trained labor, and energy. Since everything we do, build or buy has a energy component, energy could be a unifying concept. The construction of the Energy Community is taking aim at this, in hopes that this will work as a unifying concept. The missing pieces or stubs might be fillable using automated tools – but might still need subject matter expertise to integrate correctly. Slide 6

7. How do we use KM to automate the construction of large-scale knowledge bases (cont’d)? Multiple instances of correct usage support abductive reasoning. For example, within the Energy Community’s vkwiki find “acceleration” – a word used in physics - and check it out. Because of multiple instances of previously unrelated subjects within a structure of knowledge, automated construction might always require the human touch. Once the relationship structures have stabilized, automated extraction (e.g., from ANSI Standards), might proceed with the right tools. Slide 7

8. How has the Energy Community’s knowledge base been constructed? The Energy Community’s knowledge base is from trusted sources: Physical Fuel Cycle (EIA, Education Committee, 2004) Developmentally Layered Knowledge of Energy (DOE Kids Zone, 2002-2005) Pre-reader to expert. Energy and Watersheds (prepared for Virginia Assoc. of Science Teachers’ Professional Development Seminars, 2004-2006) Energy and the Environment (EIA, Environmental Issues Committee Bibliography, 1999) Science Taxonomy / Energy Related Terms (OSTI, W. Watson, 2005) Greenhouse Gases (M.A. DeLucchi, Life Cycle Emissions Model, UC-Davis) Strands of Knowledge (Ref.: National Science Teachers Association “Strands”) Visuals of Energy Flow (Modeled after the first world-class thematic graphic:Minard’s map of Napoleon's 1812 Invasion of Russia with six levels of historical information in one powerful design – geography, time, temperature, the course and direction of the army’s movement, and the quantity of Napoleon’s troops remaining ) Slide 8

9. How has the Energy Community’s been constructed (cont’d)? Cellular Automata Concepts of Relationships (e.g., Wolfram Applications) Recycling (from the Kids Zone at http://faculty.washington.edu/crowther/KidsZone/recycling.html , 2002) Nuclear Materials Nondestructive Assay Measurement Control and Assurance (Institute of Nuclear Materials Management, Nuclear Standard N-15-36) Some of the best instructional sites (all free and built by trusted sources): Earth science, environmental science, and geography: http://webs.cmich.edu/resgi/ . Internet Science and Technology Fair’s winning websites are at: http://istf.ucf.edu/Tools/NCTs/ (organized by National Critical Technologies). Science music has been organized at:http://www.science-groove.org/SSA/resource.html Slide 9

10. What do we do to cope with the “critical mass" issues? Critical Mass refers to having a sufficient number of semantics (wikiwords) that cross-link and backlink, engendering both broad and deep knowledge. Simple semantics do not demonstrate this, but imply the existence of the capability. Experience indicates a threshold (i.e., a critical mass) must be crossed before fusion can be achieved. Having a critical mass of knowledge – in the form of subject matter experts to fuse their knowledge – is a second part of the issue. In a world of busy people, how do we get people to focus their passion on this kind of sharing of knowledge? How can we accelerate their involvement? How do the “trusted sources” self-identify? Slide 10

11. What do we do to cope with the "complexity" issues? Semantics: Cross-discipline subject matter experts may have difficulty when they work together because they don’t share the same semantics. Allowing instances handles this. How do we communicate in a world where people use the same words to mean different things, or use different words to explain one relationship, or even use the wrong word consistently? For example, on the previous slide, two “nuclear physics” terms - “critical mass” and “fusion” - have different meanings in this new context. How do we add relationships when the natural language is noun-oriented and copula bound? Why is this important? Slide 11

12. Coping With “Complexity" Issues(continued) Knowledge Deficit:The most substantive of the issues revolves around knowledge – or lack thereof: Most teachers / people don’t know a div from a divot, a curl from curling, and the relationship between a div and a curl. (Who named this mathematical operator a “curl”?) Most have never even heard of a div or curl. Most never remember seeing the most important equations / science to come out of the 19th Century (i.e., Maxwell’s Equations).And most people are formula averse. Slide 12

13. Coping With “Complexity" Issues(continued) Shock of Change:How do we break it to teachers that: Their teachers failed to teach them the importance of energy (e.g., the important inter-relationships to be considered when making informed decisions about life, science, math, economics, business, engineering, and technology), and what is most important (e.g., Maxwell’s Equations, conserving energy).Their teachers never taught them about copulas.They may be so far behind on the learning curve that they might never catch up on either. To end this transgenerational failure, they need to teach both. Slide 13

14. Coping With “Complexity" Issues(continued) Top Down or Bottom Up:Is one more right than the other?TD U BU is a locked relationship (one sheet of paper with two sides, and “trusted partners” can be trusted to merge them. Merging Ontologies: How can we merge ontologies (when the subject matter experts don’t understand how to structure complex semantic relationships)? Ontologies are made and merged manually (right now, anyways).As tools appear, how do we discover which works for our application? Subject-Predicate-Object: When OWL/RDF say to use n-triples, and this notion initially overwhelms almost everybody, what do we do when n-triples are necessary but not sufficient? Slide 14

15. When do we apply KM to E-Learning? • Pattern recognition seems to be innate to all humans. KM can take advantage of this capability by presenting pre-constructed ontologies, taxonomies, and other persona-oriented patterns. • While the issue of users with mismatched vocabularies is a tough one, the use of personas can relieve much of the stress. • The stress will fade because of the very nature of personas – the view of each subject from the persona’s perspective of a “Energy as a Unifying Concept". • Advective reasoning is supported by this approach. Learning the rules that differentiate one instance from another results from advective learning. This rule differentiation notion is at the heart of cellular automata theory. • It’s never too soon to start teaching pattern recognition. • It’s never too late to start doing the right thing. Slide 15

16. When do we apply Knowledge Bases to E-learning? • Pattern recognition seems to be innate to computers, too, but only when programmed for it. E-learning can take advantage of this capability by following preconstructed OWL/RDF patterns. Slide 16

17. When do we apply Knowledge Bases to E-learning? • Patterns support knowledge mining through relationships that are OWL-compliant n-triples (subject-predicate-object). • Constructing relationships with N-triplets to respond to active-verb questions is tricky (e.g., they need parsing – concatenation – parsing). • Well formed questions can lead the way on this: http://faculty.washington.edu/crowther/KidsZone/ask.html#ask • Ontological structures lead to the use of triplets in questions. • The wiki itself allows parent-child and sibling relationships to be implied by the linking structure, fulfilling a minimal requirement for being an N-triple. Since English is a fine language for business, and business requires us to say “this is mine” and “that is yours”, these implications suffice. • However, in relationships a relator does something to something. This relationship cannot be expressed correctly within a copula bound semantic (i.e., English and the web’s noun-based approach). Slide 17

18. What do we look forward to in Social Computing Tools? • There are other partners in ontology who are working on automated tools to extract knowledge. Tools for text, music, pictures, etc. are on their way. They will embed their knowledge into this semantic web. • Tools are being constructed to take documents (e.g., ANSI Standards, glossaries, NARA records) and extract / link the appropriate wikiwords – with functional relationships (hopefully) intact. If we want to do this now, we do it manually. • As the tools are developed, they stand to complete stubs and provide extensions to the ontological structure under development. • As these things happen, we hope the results will be impressive, creating greater functionality. Slide 18

19. What do we look forward to in Social Computing Tools (cont’d)? One important section, Energy & Electricity, needs peer-review and vetting by subject matter experts who are mathematicians and Electrical Engineers. Questions for the non-experts: Does it make sense? What background material needs to be provided to help climb the learning curve - before deciding whether it makes sense? Patterns of Learning (from experience in a DC inner city school, 2002-2005). Even though there has been some peer review of these patterns, these need peer-review by people who relate to the various personas and associated developmental layers of knowledge. Slide 19

20. Applying Social Computing Tools toE-Learning • The overlap between the Energy Community and others’ interests could lead to a better solution for everyone. The website is getting more robust with each new "trusted partner“. See: http://vkwiki.visualknowledge.com/ • As teachers become "trusted partners" in the development of this ontology within the vkwiki structure, we would be supporting youth, teachers, and knowledge-seeking people looking to make informed decisions. • The current web has limited power to supply “trusted” E-Learning. The root cause of this limitation involves the lack of self-control by individuals who incorrectly represent themselves as “trustable” subject matter experts, and then advocate something for some reason. • As we refine our ability to trust “trusted partners”, the web’s supply of “trusted” E-learning will expand. Slide 20

21. Applying Social Computing Tools to E-Learning (cont’d) • Also, there are parts of the vkwiki under construction by well-rounded knowledge experts. • While it would be great to have only those who know the difference between a div and a divot, a curl and curling, and the relationship between divs and curls, there is still much to that can be done to expand the knowledge base, with or without this particular subject matter expertise. Examples: • There are several thousand "Energy Related Terms" that need to be completed and embedded into their rightful spots. • Most listed sources still have not been completely integrated. • This is a four-month old SICoP Energy Community and we are just beginning. • Join us in expressing our passion for sharing knowledge. Slide 21