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NLP Unit 3 – NLP & Modelling

NLP 3 Unit Description

AIM:  To ensure the ability to work with identified descriptions of an individual’s system and his/her prevailing patterns to effect desired change

  1. Apply at least three modelling methodologies to plot a description of an individual’s system
  2. Demonstrate ability to operate consistently from within the client’s model of the world, behaviourally and linguistically
  3. Provide a useful description of an individual’s system, as a result of a process of questioning and observation
  4. Identify a range of patterns emerging from within an individual’s verbal and/or non verbal communication
  5. Respond code congruently to what it happening in-the-moment
  6. Demonstrate how own interventions relate to the indentified system of the individual
  7. Devise a model to deliver a predetermined behavioural response
  8. Demonstrate how the NLP Presuppositions operate in the system of modelling

NLP 3 Assessment Activities

3 case studies and supporting notes and illustrations
1 videoed and annotated transcript
A self originated Model and an original Technique

NLP 3 Underpinning Knowledge

  1. Identity of a Modeller
  2. The range of applications for Modelling
  3. The Route Map of Modelling
    • Application Area
    • End Users
    • Focus of Enquiry
    • Sources of Information
    • Modelling Intervention
    • Modelling Outcomes
  4. Skills of Modelling
    • Systems and structure
    • Logical Levels and Logical Types
    • Precision use of language in labelling
  5. Model Types
  6. Model construction criteria

NLP 3 Skills

  1. Modelling Methodologies:
    • Grinder – Intuitive Modelling
    • Delozier – Somatic Modelling
    • Music, Art, Dance Modelling
    • Burgess – Punctuation Modelling
    • Burgess – Personality Alignment
    • Lawley and Tompkins – Symbolic Modelling
    • Gordon/Dawes – Array
    • Dilts – Analytical Modelling
    • Bailey/Charvet – Meta Programmes
  2. Gathering, Scoping and Testing information to generate a Model
  3. Holding multiple attention
  4. Flexibility with Filters
  5. Pattern detection
  6. Model construction
  7. Model Testing and Second positioning
  8. Mapping Model against needs of End User
  9. Constructing techniques