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Where does data come from?

We get information as 'signals' about what is happening around us .
 
Some signals are 'in your face'... we tend to record data associated with these 'strong signals'. 

 

For example, much of the data that we collect around behaviour records strong signals about the problematic things that a student has done. But there are also weak signals in every situation.

Valuable insights often arise from weak signals

Weak signals can cover a with range of data, including

  • hints about the deeper causes and other contributing factors originating elsewhere (other times, places) and from other  people...
  • the contrast with situations in which such problems/concerns do not arise (no problem occurs all the time and in all places)
  • non events, that is, what is not happening, where it is not happening, when it is not happening
  • indicators of opportunities to gain improvements (what is working in another time and place)
  • connections between what is (and is not) happening here and elsewhere and at other times
    trends
  • the exceptions when things go well  (or go less well)
    • many improvements are first experienced as weak signals, e.g., a reduction in the length of time taken to recover from a major incident is a weak signal
    • similarly deteriorating situations are often initially experiences as weak signals, e.g., reduced engagement with what is happening
  • and so on...

 

These insights based on weak signals often lead to effective sustainable solutions that are better and easier than implementing costly counter measures. Being creative often means seeing beyond the obvious (strong signals) and taking into account small but significant subtleties (weak signals) involved in the situations to be addressed.

Patterns

Patterns are valuable because they help us see some 'organisation' in what is occuring. They help us make better sense of what is happening. And better responses too!!

 

But patterns have their complements: the things that are not part of the patterns,  Knowledge of where things are definitely not OK (strong signal) also suggests (a weak signal) where things may be going quite well.

 

Constructing our knowledge, actions and arrangements solely on the basis of strong signals will probably be better than just guessing. Constructing actions and arrangements based on knowledge derived from both strong and weak signals can be even more productive.

 

A simple pattern: Some children are OK in the classroom but have lots of problems in the playground. So what is it about the classroom that helps to make things OK there but is not present in the playground. Can these helpful things be extended into the playground? If so, how....?

The challenge of dealing with strong signals

There is nothing wrong with strong signals... they often indicate something in need of urgent attention.

 

However, the challenge with strong signals is that they usually mask weaker signals that can be important in their own right.

  • The length of time taken a student takes to recover from a major incident is a weaker signal than the problematic behaviour in a particular incident.
  • The contribution of bystanders is also a weaker signal than the overtly problematic behaviour of the key offender in an incident.
  • Changes in recovery time and bystander behaviour are even weaker signals.

The classic example of masking??

IMHO, the classic example of masking in schools involves aggressive boys: their confident, conscious aggression (strong signal) makes it difficult for us to see how anxious, uncertain and frightened (weak signals) they really are.

Detecting weak signals

Weak signals are usually detected by

  • interrogating the data to the next level
    • as is functional analysis, or
    • looking for the exceptions: asking what, when, where....there is NOT a problem
  • working with facts within the whole context stories (not just data in isolation) and
  • listening in conversations about the concerns, connections, minor successes....
  • involving the student in the conversations
  • understanding how others (especially students and teachers) perceive the signals they receive (what is 'strong' for us may be 'weak' for them and vice versa)

Invest in detecting weak signals

Data for clarifying problems is usually available from strong signals... it is hard data. Great if one has an engineering problem.

 

Data for creating solutions is usually available from weak signals... it is soft data that is gathering by reflecting, wondering, speculating, ....

 

Crunching the hard data associated with strong signals may be a science, but detecting weak signals is an art.

 

How good is your school at detecting and recording 'weak signals'?
 
Being good at detecting and capturing 'weak signals' has several major benefits including

  • increased quality and richness of the data available
  • better decisions and responses
  • reduced risk associated with being 'data driven' (Yes, there are risks associated with being data driven)
     

 

 

Ivan Webb Pty Ltd 2001 onwards