Knowledge Acquisition and Modelling

1. Knowledge Acquisition and Modelling Concept Mapping

2. Knowledge Tools • Technology that enables knowledge generation, codification transfer • Not all are computer based • Not information management tools • Can manipulate information • Automated information search, retrieval agents, decision support, document management

3. Mapping • An active learning strategy • moves from rote memorization to critical thinking. • Provides an explicit, encapsulated representation of important ideas on one page • Promotes a richer construction of knowledge because you must organize, select, relate and interpret data. • Requires that you break down component parts to see how things are put together. • Helps you to see gaps in knowledge and areas of oversimplification, contradiction or misinterpretation.

4. Mapping • Visual presentation at some level • Consists of • Concept catalog (allows links to other maps, even with different lexicons) • Metadata depository (files and links)

5. Concept Maps - History • Developed in 1972 by J. D. Novak, Cornell University • Powerful aspect • Ability to represent knowledge structure of an individual on any topic • Knowledge Representation • Concepts represented by nodes • Linked by words that represent a relationship between the nodes

6. Concept Maps - History • Developed a project seeking to understand changes in childrens’ knowledge of science • Based on Ausubel’s learning psychology • Learning takes place by assimilation of new concepts and propositions into existing concept and propositional framework

7. Concept Mapping • Concept mapping can be done for several reasons: • To design complex structures. • To generate ideas. • To communicate ideas. • To diagnose misunderstanding. • Concept mapping can be used in acquisition: • To elicit knowledge • To model knowledge • To communicate knowledge • To interpret knowledge • To gain new knowledge

8. Concept Mapping • Six-step procedure for using a concept map as a tool: • Preparation. • Idea generation. • Statement structuring. • Representation. • Interpretation • Utilization.

9. Terminology • Concept • “a perceived regularity or pattern in events or objects • or record of events or objects • a unit of meaning • designated by a symbol usually a word”1 • Objects are defined as things • Events are defined as happenings • Help describe the domain in which we are working 1:Concept Mapping using Cmap to enhance Meaningful Learning, Canas, AJ and novak J.D, in Knowledge Cartography, Odake, Buckingham, Shum, Sherbourne (eds), Springer-Verlag, 2008

10. Terminology • Concepts are linked • Linking phrases are usually verbs which when read with the nodes they link form a phrase or proposition • Represent relationships between concepts • Freedom to choose linking phrases distinguishes the concept map from other maps such as mind maps, process maps, etc 1:Concept Mapping using Cmap to enhance Meaningful Learning, Canas, AJ and novak J.D, in Knowledge Cartography, Odake, Buckingham, Shum, Sherbourne (eds), Springer-Verlag, 2008

11. Characteristics • Start with a Focus question • the problem or issue the concept map should help to resolve. • Propositions • a concept map consists of a graphical representation of a set of propositions about a topic. • Hierarchical structure • most general concepts are at the top of the map and the more specific, less general concepts are arranged hierarchically below. • tend to be read from the top, progressing down towards the bottom. • Not always true – map can be cyclic as long as there is logical order (e.g. using arrows or numbers). • Can be more than one root. • Structure depends on context • Cross-Links • relationships or links between concepts in different areas of the concept map. • often represent new insights on the part of the knowledge producer.

12. Relationships • Static Relationships • help to describe, define, and organize knowledge for a given domain. • inclusion (part-of), • common membership (belonging to a group) • intersection (members of a group belonging also to another group) • similarity • Dynamic Relationships • describes how the change in one concept affects the other concept. • Causality (second event is a consequence of first event) • correlation/probability (can indicate a predictive relationship, tendency to vary together)

13. Example from http://http://cmap.ihmc.us/

14. How to Draw a Concept Map • Start with a focus question • Identify the key concepts • Rank the concepts by placing the broadest and most inclusive idea at the top of the map. • Be aware of the context of the concepts we are dealing with or to have some idea of the situation for which these concepts are arranged. • Work down the paper and add more specific concepts. • This is where elicitation techniques can be useful

15. How to Draw a Concept Map • Connect the concepts by lines. • Label the lines with action or linking words. • The linking words should define the relationship between the two concepts so that it reads as a true statement, or proposition. • The connection creates meaning. • Specific examples of concepts can be added below the concept labels. (e.g., golden retriever is a specific example of a dog breed.) • As your understanding of relationships between concepts changes, so will your maps. • Refer to your previous maps to help you visualize the evolutionary process of your understanding.

16. J.D. Novak Concept Map of Concept Maps

18. Create a concept map about plants using theseconcepts

19. Exercise • Pick a topic • Using elicitation techniques covered last week, generate a set of concepts and relationships • Build a concept map to reflect