2. HOW TO CREATE AND MAINTAIN CONCEPROCITY CAPRICE AND CAPRILOPE MODELS Mark Gregory Based on the earlier work by LICEF Version 2.1 18/10/2013

3. Left and Right Brain?  The concept of right brain and left brain thinking developed from late 1960s research of psycho- biologist Roger W Sperry, who discovered that human brain has two very different ways of thinking:  Right brain is visual and processes information in an intuitive and simultaneous way, looking first at the whole picture then the details  Left brain is verbal and processes information in an analytical and sequential way, looking first at the pieces then putting them together to get the whole

4. Illustrating Concepts  Concepts may be held both visually and linguistically  Mind Maps –Tony Buzan (Buzan & Buzan 1996)  Concept maps – Joseph Novak and collaborators (Novak & Cañas 2008) following David Ausubel (Ausubel 1963) and (Ausubel 2000)  Concept maps with typed concepts and relationships: LICEF (Paquette 2010; Basque 2013)  Concept Process maps: Conceprocity: Mark Gregory (www.markrogergregory.net)www.markrogergregory.net  Using both the visual and the linguistic (written and spoken language) stimulates better understanding of a situation and – later – better learning

5. Here is a Wading bird Tony Buzan’s Mind Maps are highly visual. However, their insistence on a single centre is unnecessarily restrictive and their strict hierarchy prevents conceptual cross-linking between branches of the tree

6. Conceprocity: An Introduction  Conceprocity – concept process reciprocity – is a visual and textual language and toolset intended for capturing, expressing, communicating and co-creating models of topic areas of domain knowledge by domain experts or learners  You decide the vocabulary  Very simple grammar rules

7. CAPRICE  Within Conceprocity there is a beginners’ profile “Simple concept mapping for beginners”, in which the only available relationship between concepts is association  This simple concept mapping for beginners usage profile is called CAPRICE: Concepts Actors Procedures Relationships Images Conditions Events  Strong emphasis on the use of sketches, icons and images to stimulate right brain involvement  There are other usage profiles which are not mentioned further in the first part of this presentation  They make use of a further notion – principles; of typed relationships; and they distinguish instances from classes

8. An example Conceprocity model and how it has been created - 1  Start with a simple English sentence: “The cat sat on the mat”  Give a specific instance: “The cat called Kat sat on the mat in my lounge”  A concrete Conceprocity map is as right  Identify concepts, any static relationships and any activities  Create a specific and a more general model using the meta- concepts (Conceprocity notions) of concept, procedure and relationship  Consider concrete and abstract representations

9.  An example Conceprocity model and how it has been created - 2  Observe, maybe discuss and then refine the resulting map  Here we choose to remove the concrete and retain the abstract elements in a conceptual model of the general situation of creatures acting in a geographical context  The model that results depends upon the viewpoint and the purpose of the modeller  A cat specialist (and a cat lover!) will take a different view from an expert in cognitive science applied to animals  But the process of dialogue and of mutual understanding can be aided by visual concept mapping and by dialogue around the models

10. Conceprocity CAPRICE: Fundamentals Paquette’s G-MOT and Conceprocity distinguish between types (classes) of objects:  Concepts - things, ideas, etc.; these are usable and (sometimes) decidable classes of knowledge or data  Actors - people, organisations, external systems  Procedures - the means of enacting knowledge in the form of specific activities, repeatable actions and processes – the latter being templates for repeated actions  Relationships: concepts are related by relationships or relationship instances (links). In CAPRICE the only available type of relationship is an association; this should be given a name  Images: images illustrate concepts or any other notion.  Conditions: logical operators XOR, OR or AND.  Events: EITHER occurrences in time that change the state of a class of objects OR named states of class of objects  Principles: constraints, rules or complex conditions. Not used in CAPRICE.

11. CAPRICE fundamentals

12. Abstract knowledge Conceprocity CAPRICE: Representation WHAT? HOW? Procedures Procedural K Concepts Conceptual K WHO? Actors K wielders Abstract knowledge

13. Representing CAPRICE relationships Different kinds of arrow are used: SymbolMeaning Association. This needs a text label, such as is-a, is-composed-of, etc. Flow of control or of data Is instantiated as Regulates. An actor or principle controls or governs a concept or procedure Commentary concerning the diagram

14. Images: Conceprocity for the Right Brain  Conceprocity makes it easy to include visual elements. Beyond Conceprocity’s own symbols, we can include images and icons.  You can either locate these for yourself, or you can use Google Images search, or they may be sketches made using apps such as ArtRage, or they may be sketches (e.g. fragments of rich pictures) drawn freehand on paper and then photographed and uploaded.  Sketches – less formal diagrams – frequently have a role, particularly in the early development or the informal presentation of a model (especially during whiteboard sessions). You may even include a complete rich picture (Checkland 1981; Checkland & Tsouvalis 1997) or elements of a rich picture.

15. 14 Modelling businesses using rich pictures Use few words Use lots of pictures

16. 15 Making rich pictures Rich pictures (situation summaries) are used to depict complicated situations Encapsulate the real situation through a no-holds-barred, cartoon representation of layout, connections, relationships, influences, cause-and-effect etc. - objective notions Should try to depict subjective elements such as character and characteristics, points of view and prejudices, spirit and human nature If possible, ask the actors themselves rather than focusing on your own interpretation of the situation Allow competing pictures; don’t “reconcile”; perhaps “accommodate”?

17. Begin to build a model What is the question or topic area that you are addressing? What are the top five or so concepts? Are there any direct relationships (associations) between these concepts? E.g.: is-a-kind-of, consists-of… Otherwise: what processes link or transform the concepts? Make lists of likely concepts and procedures Perhaps later keep these lists in a formal Conceprocity dictionary? Sketch out an initial CAPRICE model – on a large sheet of paper or on a whiteboard – preserve this using a smartphone picture Include rich picture elements on the CAPRICE map

18. How to get started with a CAPRICE model Identify and make lists of concepts and their “obvious” structural links / associations Example: beech is-a-kind-of tree Take care to distinguish concepts as classes (often distinguished by an indefinite article in natural language) and instances of concepts (often distinguished by the definite article or evidently proper names) In English and in French, but not in German, the distinction is often made clear by the use of Capitals (instances) and lower-case (concepts) The difference is often that between abstract concepts and concrete facts Identify processes which link concepts where one needs to be changed or transformed in some way which goes beyond a structural association Cow gives-birth-to calf (Better models are possible…)

19. Your task: to create a simple CAPRICE model of the general principles of an e-marketing campaign Over to you: Twenty minutes as separate teams Present, compare, contrast, reject, synthesise for five minutes Tell / show us your tentative conclusions on the flipboard Modelling a marketing campaign

20. Full-fat Conceprocity: CAPRILOPE  CAPRILOPE: Concepts Actors Procedures Relationships Images Logical Operators Principles Events  More emphasis on principles  Fully typed relationships

21. CAPRILOPE fundamentals

22. The correct way to install Google Drive and Lucidchart  You must install and use the Google Chrome browser and use it when setting up or changing Google Drive and Lucidchart accounts  Subsequently it’s OK to use Firefox etc.  You must ensure that BOTH your Google Drive email account AND your Lucidchart account are set to be your ESC Rennes username – that is, something like pierre.martin@esc-rennes.fr pierre.martin@esc-rennes.fr

23. Start from Google Drive  First: connect to and learn to use Google Drive  To do this, use the address https://drive.google.com/a/esc-rennes.fr/#my-drive https://drive.google.com/a/esc-rennes.fr/#my-drive  Although it is not essential to do so, you are advised to Install Google Drive for PC, Mac or Android as appropriate  This permits you to move files between your computer and Google Drive very easily using your file manager (e.g. Windows Explorer, Mac Finder)

24. Go on to install Lucidchart  To install Lucidchart, use Google Chrome. Disconnect from any other Google Account. Connect to your ESC Rennes address.  From your Drive homepage Create > More > Get more apps and search 'Lucidchart’Drive homepage  Once the app is installed, you will see Lucidchart listed under Create → More in Google Drive  You can use this feature to create new Lucidchart documents, in the same way that you start new Google documents or spreadsheets – BUT use our templates  For other questions, please see the Lucidchart Google Drive documentation

25. Check that you’ve set things up correctly  When connected to Lucidchart, click on Account and check that the Username and the Email are BOTH set to be your ESC Rennes user name  Problems? See Mark Gregory, room 338  Most common problem: you have downloaded and installed Lucidchart while connected to another Google account, not your ESC Rennes one!  PLEASE ONLY install Lucidchart while connected to your ESC Rennes free account  If you have NOT done this, see Mark in room 338

26. Sharing files with your teacher  We advise you to set up a folder for files that you want to share with your module student colleagues and with your module teacher  Please make sure that the name that you choose contains the name of your team – e.g. team 7 in group 02 is team G1T07 on module IS505E PEC; therefore call your folder something like IS505E PEC team G2T07

27. NEVER FORGET  Work with your ESC Rennes username and password when you want to create documents that teachers can access!  You have a free educational account with Lucidchart  But to use it, you MUST ALWAYS connect using your ESC Rennes username  Use Google Chrome to install Lucidchart  Lucidchart has to be installed when you are using the Google Chrome browser, and generally works best with that browser

28. How to synchronise Drive and Lucidchart  If you want to sync your files between your Lucidchart account and Drive you can select, from the Lucidchart editor, File > Google Drive Preferences, and choose what you would like  You can learn more about integration by visiting the tutorial section on Google Drive

29. Syncing Lucidchart files with Google Drive  Google Drive Preferences are accessible through the editor as well as your Account page  Allows you to modify the way you sync and secure your files to your Drive account and local backup  In Editor: File > Google Drive Preferences  Synchronization: Choose to automatically sync documents you create in Lucidchart to your Drive account  Automatic Backup: Lucidchart with Google Drive allows you to have all of your Lucidchart documents backed up daily or weekly to your Google Drive Account

30. Syncing - 2 1. Make sure you're logged into the Google account you'd like to link with Lucidchart in this browser 2. In Lucidchart, Go to Account / Documents / Google Drive to link Lucidchart to that account. 1. To get to Account, you can click on the Lucidchart logo top left of the screen

31. Getting to know Lucidchart  How Lucidchart works  Lucidchart is an online diagramming software-as-a- service. It is a chargeable service but is made available free to educational institutions, including ESC Rennes School of Business.  Getting started with Lucidchart  Follow the tutorial which you will find at https://www.lucidchart.com/pages/tutorials https://www.lucidchart.com/pages/tutorials  Start with “Create a new document” and carry on until you get bored. Then come back to this document and keep reading and working from it!

32. YOU MUST USE these Lucidchart templates PLEASE use the Lucidchart templates linked to from the latest version of those slides (and from the table which follows). On the page which then opens in your browser, click on Use as template ItemTemplate Use case diagram UCD https://www.lucidchart.com/community/examples/view/4904- 2264-50bd807f-8bbd-5a850a442276 Event process chain EPC https://www.lucidchart.com/community/examples/view/4572- ba14-5288fba4-bf49-10050a008fdc Conceprocity CAPRICE and CAPRILOPE https://www.lucidchart.com/community/examples/view/42d8- 77d0-52b93213-9de6-29ca0a009f85

33. Conceprocity CAPRICE Notions Concepts Instance of object or ideaE.g. the ball bowled by bowler Smith which captured the wicket of batsman Jones at Lords on 15/06/2015 Concept: named class of similar things or ideas, sometimes characterised by facts and measurements associated with specific instances of things; these are named properties of the concept E.g. red, hard, bounces in (somewhat) controllable fashion, used in cricket – a cricket ball Super-concepts and sub- concepts E.g. ball and cricket ball Processes One-off actions E.g. see The Hobbit Activities: repeated similar actions E.g. go to the cinema periodically Processes: activity templates E.g. plan and undertake personal cultural improvement and diversion each week Actors: Intelligent Agents Knowledge-wielding persons in roles E.g. students, teachers, administrators Knowledge-wielding intelligent agents E.g. aircraft flight control systems Relationships AssociationBook is associated with knowledge InstantiationA123 Jemimah is a (specific) student Events and logical connectors EventE.g. book returned to library Compound eventEvent associated with a logical connector Logical connector: XOR Exclusive OR: exactly one of two or more outcomes may occur in a given instance Logical connector: OR Inclusive OR: one or more possible outcomes may occur – represent zero with null process Logical connector: AND All the possible outcomes will occur in parallel and in no defined sequence

34. Conceprocity Usage Profiles - 1  A Usage Profile is a named usage of Conceprocity by a defined group of model writers and readers  These various usage profiles require few or no extensions to the Conceprocity basic notation which is richly expressive  It is possible and desirable to start with a beginners’ profile “Simple concept mapping for beginners”, in which the only available relationship is association and no use is made of principles, and only then to move on to typed relationships and principles  This is the simple concept mapping for beginners usage profile CAPRICE: Concepts Actors Procedures Relationships Images Conditions Events  Strong emphasis on the use of sketches, icons and images

35. Conceprocity Usage Profiles - 2  Simple concept mapping for beginners: CAPRICE Concepts Actors Procedures Relationships Images Conditions Events  Knowledge mapping: CAPRILOPE Very general with the full range of Conceprocity objects, Concept / Actor / Procedure / Relationship / Image / Logical Operator / Principle / Event Typical uses include: self-observation, research design, representing knowledge as-is and as-ought, demonstrating understanding, documenting a body of knowledge and design of teaching, learning and evaluation  Event-driven process chains

36. The Conceprocity CAPRICE Method – 1  Define a focus question to which your model will be a (partial) answer, or at least delimit a clear topic area  Create a Google Drive directory (folder) to contain the files that will constitute the model  Begin to build a Conceprocity dictionary (in Microsoft Excel or in Microsoft Access) and glossary containing initial lists of:Conceprocity dictionary  Concepts (and specific instances: facts)  Actors (and specific instances: e.g. named persons)  Processes

37. The Conceprocity CAPRILOPE Method – 2  Create some examples for each notion  Think about the relationships between the concepts, actors and processes  Can you identify and name relationships – associations - between concepts?  Or are concepts related only by processes?  Start to sketch out the initial Conceprocity model  It’s often necessary then to go back, reconsider and refine the initial lists in the dictionary  This stage also typically requires further research around the original question  If you wish to do so, add events and logical operators to the model  Create, refine and use the model in Lucidchart

38. STOP! GO NO FURTHER… UNLESS YOU WANT TO EXPERIENCE CAPRILOPE…

39. CAPRILOPE links and grammar  Different types of links (relationships):  Association: simple connection  Aggregation: is-a, is-made-of independent parts  Composition: is-a, is-made-of dependent parts  Specialisation / Generalisation: kind-of  Regulation: controls, directs, influences…  Precedence: comes-after, comes-before…  Entrant-Product (Input-Output, Input-Product): is an input to a procedure which yields output or product, causes, gives rise to…  Instantiation: is an example (instance) of…  Grammar Rules govern the valid types of links that may join the knowledge types  Many of the grammar rules in Conceprocity closely follow those of G-MOT – see (Paquette 2010)

40. Simple relationships: Aggregations  The Aggregation link ( G ) associates multiplicity – ordinality or cardinality – with a relationship  Aggregation is an extension of the G-MOT model  It is essential in data modelling in accordance with the relational model of (Codd 1970) Link type Representation Aggregation link ( G )

41. Simple relationships: Associations, Aggregations and Compositions  The Association link ( A ) is simply an untyped connection between concepts. By untyped, we mean that the modeller either does not yet know the type of the relationship or is not yet capable of deciding its more precise type.  The Aggregation link ( G ) is a kind of association which says that one concept is part of another, together with others of the same type, so that all the parts are together a group of parts which constitute a whole concept: a part- whole relationship. Aggregation is a special type of association used to model a "whole to its parts" relationship. In basic aggregation relationships, the lifecycle of a part class is independent from the whole class's lifecycle.  The Composition link ( C ) also connects a knowledge (object) with one of its constituents or its constitutive parts. The composition aggregation relationship is just another form of the aggregation relationship, but the child class's instance lifecycle is dependent on the parent class's instance lifecycle. Link type Representation Association link (untyped) Aggregation link ( G ) Composition link ( C )

42. The difference between aggregation and composition - 1– Composition  In a composition, the existence of the parts is dependent on the ongoing existence of the parent  Example: in the human body, we can inter alia distinguish a cardiovascular subsystem. That itself consists of a heart and two lungs. Normally, it is meaningless to talk about the ongoing existence of a heart after the body of which it forms a part has died.  Similarly, for most purposes, we regard an engine as part of a car  The key phrase is “is part of”, as in “An engine is part of a car”, or “is composed of” or “consists of“” – example: A body is composed of a heart and two lungs“  Composition is indicated in Conceprocity (as in UML) by a filled lozenge  For inspiration, see: http://www.c-sharpcorner.com/UploadFile/pcurnow/compagg07272007062838AM/compagg.aspx http://www.c-sharpcorner.com/UploadFile/pcurnow/compagg07272007062838AM/compagg.aspx

43. The difference between aggregation and composition – 2 - Aggregation  In an aggregation, the existence of the components is independent of the ongoing existence of the parent  Aggregation gives us a 'has-a' relationship  Within aggregation, the lifetime of the part is not managed by the whole  Thus, in a situation in which we wish to model households, neither the persons who currently constitute a household nor the address at which they live depend for their ongoing existence on the household  A child might be part of the household of his parents at one moment but will continue to exist when that household no longer does  Similarly, the address at which a household lives is a building whose existence is independent of that of the households who currently inhabit it  However, reversing the argument, a household consists of the persons who currently inhabit an address  This whole discussion is reminiscent of the distinction between strong and weak entities in the work of Peter Chen  Aggregation is indicated in Conceprocity (as in UML) by an open lozenge

44. Inheritance, generalisation and specialisation  There are many instances when a general concept gives rise to two or more specialisations  In each case, the specialisation shares certain properties with the more general concept but also possesses properties which are distinct from other specialisations  We say that each specialisation inherits the properties of its parent but also has its own distinct properties  In a University library, we have the generalisation Member and the specialisations Academic (Faculty) and Student  Faculty can borrow more books for longer than can Students  In Conceprocity (as in UML) generalisation-specialisation is represented using an open arrowhead

45. Multiplicities, cardinality and ordinality  We can ascribe a multiplicity to either end of an association, an aggregation or a composition  This multiplicity can be:  An exact number  A range of numbers, separated by two dots  An arbitrary unspecified number represented as an asterisk *  Example multiplicities: 1 1..1 0..1 1..* 0..* 3..4 – e.g. number of legs on a stool 0..0 – this means that there is NO relationship  Cardinality specifies the maximum number in relationships and ordinality specifies the absolute minimum number in relationships. When the minimum number is zero, the relationship is usually called optional and when the minimum number is one or more, the relationship is usually called mandatory.

46. Representation of links - 1 Link type Representation Generalisation / Specialisation link (G) Regulation link (R)

47. Representation of links - 2 Link type Representation Precedence link (P)

48. Representation of links - 3 Link type Representation Sequence (Entrant- Product, Input- Output link) (I/P) Instantiation link (I)

49. Type of links: some examples Characteristics Examples C S P I/P R I LINKSLINKS «Robert’s car» is an instance of «Volkswagen cars» A « table » is composed of « legs » and of a « flat surface ». « Table » is a sort of « furniture » «Prepare an outline » precedes «Write a text» An entrant or an output of a procedure «Outline » is an entrant of «Write a text» «Text» is the product of «Write a text» A principle defines a concept by constraints to be satisfied or establishes a law or a relation between several concepts. The principle typically controls from the outside the execution of a procedure or the selection of other principles. «Editing text norms» regulates «Text» Instances of concepts, procedures or principles The attributes or components of an abstracted knowledge «Air traffic control rules » regulates «Take off the plane» «Project management rules» regulates «Instructional design of a telelearning system» From specific to general From the precedent to the next

50. Representing Conceprocity relationships  Conceprocity relationships very broadly follow UML class diagram conventions rather than G-MOT ones  This is because the UML conventions are more visually expressive than the letters used in G-MOT and can be made more semantically precise  The meta-syntax is: SymbolMeaning Flow of control or of data Influences, governs, directs… Is instantiated as Commentary concerning the diagram

51. Principles and the regulation link  In Conceprocity, it is possible to link knowledge objects to each other  The links are represented by different kinds of arrow, indicating the type of links. The regulation link exists to enable links from Principles to be expressed: In conjunction with CONCEPTs: Here the principle defines some constraints that must be satisfied or establishes a law or a relation between two or more concepts In conjunction with a PROCEDURE OR ANOTHER PRINCIPLE: Here the principle controls or governs the execution of a procedure or the selection of other principles

52. Labelling relationships  Conceprocity permits relationships to be labelled, but it doesn’t insist that this be the case  In CAPRICE: YES, label the relationships because there is no other way to give meaning to the relationship  In CAPRILOPE, if concepts, procedures and principles are well named, there is usually no additional value in labelling relationships  A possible exception: multiplicities should perhaps be labelled when modelling data structures, since a relationship between classes or entity types is bi-directional and may require two labels in order more fully to express its meaning

53. Conceprocity CAPRILOPE Notions Concepts Instance of object or ideaE.g. the ball bowled by bowler Smith which captured the wicket of batsman Jones at Lords on 15/06/2015 Concept: named class of similar things or ideas, sometimes characterised by facts and measurements associated with specific instances of things; these are named properties of the concept E.g. red, hard, bounces in (somewhat) controllable fashion, used in cricket – a cricket ball Super-concepts and sub- concepts E.g. ball and cricket ball Processes One-off actions E.g. see The Hobbit Activities: repeated similar actions E.g. go to the cinema periodically Processes: activity templates E.g. plan and undertake personal cultural improvement and diversion each week Actors: Intelligent Agents Knowledge-wielding persons in roles E.g. students, teachers, administrators Knowledge-wielding intelligent agents E.g. aircraft flight control systems Relationships AssociationBook is associated with knowledge Generalisation / specialisation Book is a kind of media (medium!) CompositionA human is composed of head and four limbs and a torso RegulationAccountancy principles regulate accountancy practice PrecedenceBirth comes before life comes before death Input-Output (G- MOT: Intrant- Product) Hops + barley are brewed to make beer InstantiationA123 Jemimah is a (specific) student Events and logical connectors EventE.g. book returned to library Compound eventEvent associated with a logical connector Logical connector: XOR Exclusive OR: exactly one of two or more outcomes may occur in a given instance Logical connector: OR Inclusive OR: one or more possible outcomes may occur – represent zero with null process Logical connector: AND All the possible outcomes will occur in parallel and in no defined sequence Principles: Rules and Constraints Generalrules, permissions, constraints and logic that surround and sometimes govern or regulate the concepts Programscomputer programs - concrete expressions of algorithms and an encoding by programmers of knowledge

54. Grammar Rules  Grammar Rules govern the valid types of links that may join the knowledge types

55. CAPRILOPE Grammar Rules - 1

56. CAPRILOPE Grammar Rules - 2

57. Conceprocity event rules  Events must be preceded and followed by EITHER a procedure OR a logical connector

58. Swim Lanes in Conceprocity  Business process models realised in BPMN or as Event Process Chain EPC diagrams frequently make use of the concept of swim lanes (or swimlanes) to show ownership or responsibility for aspects of a process  The usual way to show such ownership or responsibility (or simply participation) in a Conceprocity model is to show an actor class or instance linked by a regulation link to a concept or process  Conceprocity models can include swimlanes but Conceprocity does not mandate their use  An exception occurs in the Conceprocity Event Process Chain EPC model type where swimlanes should normally be used for major actors

59. The Conceprocity CAPRILOPE Method – 1  Define a focus question to which your model will be a (partial) answer, or at least delimit a clear topic area  Decide the type of model which you wish to build  Conceptual  Procedural  Prescriptive  Methods and processes  Decide the usage profile which is appropriate to you and to the situation you are modelling  Create a Google Drive directory (folder) to contain the files that will constitute the model  Begin to build a Conceprocity dictionary and glossary containing initial lists of:Conceprocity dictionary  Concepts (and specific instances: facts)  Actors (and specific instances: e.g. named persons)  Processes

60. The Conceprocity CAPRILOPE Method – 2  Create some examples for each notion  Think about the relationships between the concepts, actors and processes  Can you identify structural relationships between concepts? See next slide…  Or are concepts related only by processes?  Can you identify principles (rules) which affect the modelled situation? Include constraints  Start to sketch out the initial Conceprocity model  It’s often necessary then to go back, reconsider and refine the initial lists in the dictionary  This stage also typically requires further research around the original question  Add principles, events and logical operators to the model  Create, refine and use the model in Lucidchart

61. Identifying structural relationships between concepts Relationship Type English statement Associationis-associated-with Try to avoid this very general relationship, in favour of: Aggregationis-a, is-made-of independent parts Compositionis-a, is-made-of dependent parts Specialisation / generalisation kind-of Precedencecomes-after, comes-before Input-Outputis-input-to, causes, gives-rise-to; an input to a procedure which yields output Regulationcontrols, directs, influences Instantiationis-an-instance-of

62. Why Conceprocity is important  Conceprocity is a semi-formal visual knowledge representation language which enables and encourages the modeller to be more precise in defining, bounding and relating conceptual and procedural knowledge  It’s a way to constrain and enhance natural language expression  to increase the precision of the meaning which the modeller needs to express  To the extent to which two modellers can agree upon a Conceprocity model, it is also a means to establish and to verify communication of ideas and concepts

63. Student use of Conceprocity  PEC students use it to map the content and meaning of a research article as their individual project  IBIS students use it in their individual project: active and reflective learning journal  MIS students use Conceprocity in their individual project: use a tool to improve the ways in which you get things done and keeps found things found and progressively enhance a Conceprocity map which shows how you use ICT to live and work more effectively  Please ALWAYS use the Conceprocity template: https://www.lucidchart.com/community/examples/view/42d 8-77d0-52b93213-9de6-29ca0a009f85 https://www.lucidchart.com/community/examples/view/42d 8-77d0-52b93213-9de6-29ca0a009f85

64. The Conceprocity template  If you use the correct template and if you are a part of the ESC Rennes Lucidchart team, you should be able to see the Conceprocity shape libraries which look like this:

65. References Ausubel, D.P., 2000. The acquisition and retention of knowledge: A cognitive view, Kluwer Academic Pub. Ausubel, D.P., 1963. The psychology of meaningful verbal learning. Available at: http://psycnet.apa.org/psycinfo/1964- 10399-000 [Accessed September 19, 2013]. Basque, J., 2013. La modélisation des connaissances en milieu organisationnel. Available at: https://oraprdnt.uqtr.uquebec.ca/pls/publ ic/docs/FWG/GSC/Publication/1518/93/1 924/1/52315/13/F2080926314_UQTR_ midi_p_dago_27mars13_VFF.pdf [Accessed April 16, 2013]. https://oraprdnt.uqtr.uquebec.ca/pls/publ ic/docs/FWG/GSC/Publication/1518/93/1 924/1/52315/13/F2080926314_UQTR_ midi_p_dago_27mars13_VFF.pdf Buzan, T. & Buzan, B., 1996. The mind map book: how to use radiant thinking to maximize your brain’s untapped potential, Plume Books. Checkland, P., 1981. Systems thinking, systems practice, Chichester: Wiley. Checkland, P. & Tsouvalis, C., 1997. Reflecting on SSM: The Link Between Root Definitions and Conceptual Models. Syst. Res. Behav. Sci., 14(3), pp.153–168. Novak, J.D. & Cañas, A.J., 2008. The theory underlying concept maps and how to construct and use them. Florida Institute for Human and Machine Cognition Pensacola Fl, www. ihmc. us.[http://cmap. ihmc. us/Publications/ResearchPapers/T heoryCmaps/TheoryUnderlyingConcept Maps. htm]. Paquette, G., 2010. Visual Knowledge and Competency Modeling - From Informal Learning Models to Semantic Web Ontologies., Hershey, PA: IGI Global.