In the 2019 edition of Keralanadam, I published an article dealing with three aspects related to this topic. 

They were: (1) What is science about? (2) Science process skills in relation to the scientific method and (3) Observation and Classification.

Let me elaborate a little more on the nature of science itself. When we speak of science and teaching or learning science, the first impression that comes to mind is about the content of science i.e.: the concepts of science and scientific knowledge. While these are important, there are two other important aspects which also need to be considered in connection with the learning of science. 

They are the processes for obtaining scientific knowledge and scientific attitude. 

The processes for obtaining scientific knowledge are developed by asking questions and finding answers. In fact, these are the same skills we use in our everyday lives to solve problems. So, when we learn these skills in science, we are learning skills that we can apply to every aspect of our lives. Scientific attitude constitutes the second aspect. Imagination, curiosity, and the urge to ask questions to solve problems form part of the scientific attitude. Respect for those methods and values could also be included as scientific attitude.  

In addition, seeking to answer questions using evidence, recognising the necessity of rechecking data and accepting the fact that scientific theories and knowledge change over time as more knowledge is collected, could all be regarded as traits of this aspect.

You may ask: Why is this article included in this magazine?  I would answer as follows:  

My experience is that many individuals feel disconnected from or disinterested in science and in learning of science. I am making a humble attempt here by using simple explanations to develop in readers a leaning towards a scientific disposition. To this end, readers are encouraged to choose examples to illustrate a skill/principle as far as possible from home or their local environment. In this way science may be made useful, personal and meaningful.  In working out the exercises, questions like how, why, when and what may be asked to find the answers.

Let us now consider two more science skills: inference and prediction.

Inference

Inference is an explanation based on observation. It is a link between what is observed and what is already known. In other words, it is an assumption of a cause or causes generated to explain an observed event. For example: A person observes a creature with six legs and calls it an insect because he/she has already learnt that all creatures with six legs are called insects.

So past experiences help to interpret observations. Many different inferences can be made from the same observations. Inferences may change as additional observations are made. The confidence about the inferences may be strengthened as more and more supporting evidence are gathered. For example, one person observes a chameleon changing its body colour when it is near its cage and they observe that it changes colour again as they tap on the cage. This increases the confidence in their inference that the chameleon changes colour because it is upset and is trying to defend itself. Thus, we see that additional observations can reinforce our inferences. But sometimes additional information will force us to reject or alter our inferences.

For example:

Observation: A moving car stops suddenly.

Inferences:

1. Petrol ran out 2. Electrical fault 3. Engine overheating 

Here inferences are made based on past learnt experiences — we would rule out inferences one by one based on new observations.

Exercise:  Write as many inferences as possible for the following observations:

• Water drops dripping from the ceiling of the house
• A student receives poor grades for a test
• A plant wilts in the garden

Prediction 

A prediction is an educated guess based on good observations, inferences from an observed event or prior knowledge. This process deals with projecting events or forecasting future observations.  

A prediction must be testable. We must be able to identify a trend in a body of data and to project the trend in a way that can be tested. This means that predictions can be tested or rejected based on observed criteria.  

For example:

Observed event:  Dark, thick clouds gather in the southern sky

Prediction:  Heavy rain will occur followed by thunderstorm

Daytime temperature rose to 50 degrees Celsius. Prediction?

Some students do not obey school rules. Prediction?

Predictions are concerned with the question: What will happen next?

What will happen when we add salt to boiling water? 

How many of the seeds that we plant in our garden will sprout?

Exercise:  Write as many examples as possible about your immediate environment.  Find answers and test them.

So, we have dealt here with four basic science process skills: Observation, Classification, Inference and Prediction. Simple everyday problems can be solved using these processes individually or integrated, depending on the nature of the problem. Close observations about a problem may lead to drawing inferences which may either solve a problem, or lead to a prediction, or lead to further investigations which may require complex science skills. This will be our next area of exploration.