See part 1 here:

Curriculum task: I did a separate unit of work this term (Jan 2012) on data collection/processing and graphing.

Thinking task: to construct an algorithm for just the 'data collection and data processing' part of a scientific investigation, to begin construction on a 'Human ENV model' and a 'Graph ENV model'.

This is a Formative task: In this task I am not asking the students to form a hypothesis or decide on data to collect - only to collect/process & graph the data. 

 

Question: Is there a relationship between height and shoe size?

To do: Gather and process data to reach a conclusion.

The aims were: (see this resource also) (and this resource)

to improve students data collection process & skills and conclusions

 

data choosing skills

• what is the main element here (X)? - in this case X = humans 
• what are the variables present?
• building an ENV model for X
• which variables /values will I focus on?

data collection skills

• how will I collect the data? research/survey/measurment/from a bank? 
• recording all data in notebook (even apparently anomolous data - should be disgarded later with explanation)
• collecting accurate data (e.g. height in cm & mm not just cm) - how?
• deciding on/selecting units (e.g. shoe size eurpoean/american/british?)

data processing skills

• selecting relevant data to process for hypothesis or investigation question (height, shoe size, m/f etc. - not names)
• deciding on sufficient data for this hypothesis (not the usual - too little)
• tabulating data (not so strightforward)
• drawing the box using a ruler
• column headings & units
• recording/transcribing from notebook accurately
• doing calculations on the data (e.g. if using time are you using dates the information was collected or the age of the person?)

graphing skills

• choosing axes (what goes on x/y)
• choosing ranges for axes
• choosing & drawing scales
• labelling axes and units
• plotting points accurately
• deciding on a line of best fit
• drawing the line of best fit with a ruler
• calculating the gradient 

conclusion skills

• comparing gradients (if there are multiple gradients)
• interpreting the gradient in terms of the investigation
• interpreting the correlation strong/weak (how spread out is the data from the best fit line?)
• linking the results to the initial question!
• explaining your conclusion scientifically
• discussing how reliable the data or method/process is
• discussing future improvements (gathering different/more/better data (variables or values))
• what's next - future investigation??? leads to activity on how to construct  a hypotheses!  

technology skills 

• using Excel to do the task above

Thinking aims: (see this resource also) (and this resource)

• ENV: a better understanding of ENV as a tool for analysis (in the context of the above task there are many elements (E) variable/parameter names (N) and values of parameters (V))
• a better understanding of the building ENV models for various elements
• reflect & improve on their scientific inquiry algorithm from last year
• reflect on & compare their 2 algorithms to evaluate their own "progress" or evolution
• reflect on how defining & using a thinking model helps them
• Begin construction on "Human ENV"
• Begin construction on "Graph ENV"
• MULTISCREEN: in this task there is also the opportunity to introduce some concepts/vocabulary from the multiscreen model (systems, subsystems and functions) e.g. the data table as a subsystem of results and defining it's fuction as "changing data collected from disorganised to organised"

Potential uses for a human ENV:

a) you are starting your own business (clothing and shoe shop) and need to select not only the styles but the sizes for your stockroom.

b)