Posts Tagged ‘motor neuron’

Reaction times

Thursday, November 5th, 2009

ReactionTimeStepTwo from

This next lab looks at measuring reaction times.  There are several ways we could do this, but we are going to keep it simple and use the old, tried and tested method of catching a ruler.  Here’s what to do:-

  1. Find a partner.
  2. One person rests their elbow on a table with their hand extended over the edge.
  3. The partner should hold a meter ruler between the subject’s thumb and forefinger, ensuring it is at the 0cm mark.
  4. As soon as the ruler is released, the subject must try and catch it.  The distance the ruler falls can be used as a measure of reaction time.
  5. You will need to repeat this a suitable number of times to ensure the reliability of your data.
  6. Try investigating different variables, such as left-hand vs right-hand, using one eye or two eyes, sound or touch stimuli instead of sight.  THINK ABOUT CONTROL OF VARIABLES – it is very important here.
  7. Record your data in a suitable way, process it and present it appropriately.  Draw relevant conclusions.  Evaluate your results and the procedure used.  Suggest realistic improvements.

This lab will assessed for data collection and processing, and for conclusion and evaluation.




Data Collection and Processing (DCP)


Recording raw data


Processing raw data

Presenting processed data


c = 2

Records appropriate quantitative and associated qualitative raw data, including units and uncertainties where relevant. Processes the quantitative raw data correctly. Presents processed data appropriately and, where relevant, includes errors and uncertainties.

p = 1

Records appropriate quantitative and associated qualitative raw data, but with some mistakes or omissions. Processes quantitative raw data, but with some mistakes and/or omissions. Presents processed data appropriately, but with some mistakes and/or omissions.

n = 0

Does not record any appropriate quantitative raw data or raw data is incomprehensible. No processing of quantitative raw data is carried out or major mistakes are made in processing. Presents processed data inappropriately or incomprehensibly.




Conclusion and Evaluation (CE)



Evaluating procedure(s)

Improving the investigation


c = 2

States a conclusion, with justification, based on a reasonable interpretation of the data. Evaluates weaknesses and limitations. Suggests realistic improvements in respect of identified weaknesses and limitations.

p = 1

States a conclusion based on a reasonable interpretation of the data. Identifies some weaknesses and limitations, but the evaluation is weak or missing. Suggests only superficial improvements.

n = 0

States no conclusion or the conclusion is based on an unreasonable interpretation of the data. Identifies irrelevant weaknesses and limitations. Suggests unrealistic improvements.

 DUE DATE:  Tuesday 17th November

Nervous system

Thursday, October 22nd, 2009
neurons from

neurons from

Some of the questions we’ll be tackling in the next section of the syllabus (6.5) are:

Do you know what the CNS and PNS are? 

Can you explain what role receptors, sensory neurons, relay neurons, motor neurons and effectors play in conducting nerve impulses?

Can you draw and label a diagram of a motor neuron?

Can you define resting and action potentials?

Can you explain how nerve impulses pass along a neuron?

Can you explain how impulses travel from one neuron to the next?

Read through your textbook pages 240-246 to get a head start on this unit over the break 🙂

And once again, a great presentation from Mr Stephen Taylor in Bandung to help you learn this stuff!

In class we will use this presentation – Nervous System

There are some useful animations here,  here and here that might help you visualize what’s happening.