The matrix to describe, memorize, analyze, investigate

How to observe and describe a person?

There are many elements to consider when describing a person. The Observable.fr matrix can be used as a guide to help you identify these elements and structure your observations. This matrix can also be used and duplicated to observe and describe a group...

  • ONE PERSON
    • Identity
      • Name
      • First name
      • Age
      • Type
    • Physical characteristics
      • Size
      • Weight
      • Eye color
      • Hair color
      • Distinctive signs (tattoos, piercings, etc.)
    • Mental characteristics
      • Intelligence
      • Personality (extrovert, introvert, etc.)
      • Motivation
      • Empathy
    • History
      • Family (parents, siblings, etc.)
      • Education (schools attended, degrees obtained, etc.)
      • Work experience (previous jobs, current career, etc.)
    • Relationships
      • Friends
      • Family (husband/wife, children, etc.)
      • Partner (current or past)
    • Interests
      • Hobbies (sports, video games, reading, etc.)
      • Passions (travel, painting, music, etc.)
      • Projects (personal or professional)

This example to observe and describe is given as a guide. It may vary according to context and specific needs. It's important to note that this structure can be adapted or supplemented with other nodes for additional information according to your needs.

Leave a Reply

Observation model (available in 2023)

A template is a predefined pattern of observations created by another user that you can immediately use to save time and discover different approaches. Any user can create a template and choose whether or not to share it with the public. You can add a model to your library, modify it and adapt it for new uses. You can also add a model directly to a current study or to a new study.

A template is composed of the following information:

  • The objective of the observational study

  • Possible additional explanations

  • All named analysis objectives (tabs)

  • All first-level descriptors in each analysis (N:0)

  • The category of the model according to the type of observation

  • The pseudo of the creator of the study

en_US