Inquiry Approach to Develop a Scientific Soul

Biology Read - Inquiry approach is a way that is applied to a person in order to find his own scientific facts and concepts by maximally involving all his abilities.

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The most appropriate inquiry  approach is used to grow and develop a person's scientific life, rather than using a fact approach (memorizing in words) and conceptual approach (linking some facts).

With a process skill approach, someone becomes more active, creative, innovative in solving a problem and producing a product of science. Thus, it can produce quality scientific products, and different or previously undiscovered products.

The process skill approach involves classifying objects, asking questions, making observations (observing, presenting data, interpreting data, predicting and predicting data, and identifying variables in an experiment.

1. Object Classification

Classification is an activity of grouping some objects based on certain criteria set. Classification aims to group some objects so as to facilitate the conduct of research.

For example, if we are going to conduct research on the effect of borax use on mammals, then we do not need to use all types of mammals, but simply use one of the mammal species that represent it, such as marmots.

2. Asking Questions

Research ideas can arise anytime and anywhere with high curiosity. Questions will arise if you experience or notice some strange events that can be raised into a problem and can be solved by doing research.

A number of questions using the 5W + 1H formula can be used to develop the ability to formulate problems that are the first step in scientific research. Interesting issues that can be investigated can be found intentionally or unintentionally.

Example :

Every day, Andy went to the river for fishing. Andy saw an oddity in the river, the color of the river water that turned into turbid, not as usual. Then, a few questions arise in the mind of his brain;

• Why does the river's water become cloudy?

• What made the clear, clear river waters clear?

To be able to find answers to a number of questions that arise, it is necessary to review the theory and collection of information from various sources. If the information obtained is not satisfactory, it is necessary to proceed to the next stage of research.

In addition to formulating problems in a study, questions are also needed to design an experiment. Some of the questions that arise when we do a research include the following:

• Where will the experiment be conducted?

• How long will the experiment take?

• What materials and ala tapa are needed?

•How does it work?

•What variables should there be in the experiment?

3. Doing Observations  

Observation is an activity to obtain data or information relating to the object of research by using the senses or with the help of tools.

Sensory observation can be done by looking, hearing, feeling, smelling, and tasting in accordance with the type of data to be taken.

Observation by means eg by using a ruler or gauge to measure the length of the object, thermometer for measuring temperature, hygrometer for measuring air humidity, balance (balance) for measuring mass, clock or stopwatch to measure time, litmus paper to measure the degree of acidity (pH) loop or microscope to view micro objects, and a video camera to record a process.

Data obtained from these observations can be qualitative and quantitative data:

a. Qualitative data

Qualitative data is data that can not be expressed by numbers. Qualitative data are usually obtained from observations using the senses.

Here are some examples of qualitative data:

• The color of turbid lake water

• The rose is more fragrant than jasmine flowers

b. Quantitative data

Quantitative data is data that can be expressed in numbers. Quantitative data are usually obtained from observations using aids, such as rulers, scales, thermometers, or other tools.

However, there is also quantitative data obtained without the aid of tools, such as the age of a person who can be calculated by birth year. Here are some examples of quantitative data:

• River water samples have a pH of 5.0.

• The air temperature in the field is 30 ° C

• River width 10 meters

NOTE :

Qualitative data are less precise and tend to be subjective (depending on observer) compared with quantitative data. Qualitative data can be converted into quantitative data by stating it in numbers (1, 2, 3, etc.) or using positive (+) and negative (-) marks.

Example :

• the amount of oxygen generated in the photosynthetic experiment can be expressed as an enormous (++++), many (+++), moderate (++), few (+), and none (-).

4. Presenting Data

To be more easily understood by others, observation data should be presented in a concise and systematic way.

Data can be presented in the form of tables, graphs, (diagrams), schematics, or images. Qualitative data can be presented in the form of tables, descriptions, sentence descriptions, schematics, and drawings. 

Quantitative data can be presented in the form of tables of numbers and graphs.

5. Interpreting Data

Interpreting the data is to give meaning or meaning to the observed data. In interpreting the data required a reference, such as existing theory or other events.

Predict

Predicting is making guesses based on logic. For example there is a 17-year-old child, but his body like a 7-year-old child. Both parents of the child look normal.

Predictions that can be made for example as a child, the child may be malnourished and often suffer illness.

Forecasting

Forecasting is to make guesses about an unknown event based on existing data. For example weather forecasts. Forecasts can be divided into 2 types, namely intrapolation forecasts and extrapolation forecasts.

Intrapolation forecasts are to make conjectures to events that have already occurred, but are not known. The extrapolation forecasts are to make conjectures about events that have not yet occurred and are likely to occur.

6. Identify Variables in Experiments

In the experiment, there were two sets of experimental devices: the control group and the experimental group. The control group is a non-treated experimental device. The point is as a comparison.

In the meantime, the experimental group is a specially treated experimental device. The treatment may vary, so it is called a variable.

Variable is determinants or influencing factors; can be changed or replaced. In designing an experiment.

You need to select variables that match the purpose of the experiment and the tools / materials available. Furthermore, the selected variable is studied and examined for its effect on the object you are researching.

Based on its nature, the variables that affect the life of organisms are divided into three, namely physical variables, chemical variables, biological variables.

• Physical variables, for example temperature, air pressure, sunlight, radiation, humidity, wind, and gravity.
• Chemical variables, for example oxygen levels, water, carbon dioxide, mineral salts, and pH.
• Biological variables, such as parasitic organisms, predators, other organisms in food chain relations, life cycle, and reproductive ability.

Variables in the experiment can be divided into independent variables, dependent variables, control variables, and disturbing variables.

• The independent variable (variable manipulation) is the different treatment in the experiment. Independent variables are intentionally made differently to determine the effect of independent variables on dependent variables.
• The dependent variable (response variable) is the result of different treatments in the experiment. The dependent variable is the result of the independent variable.
• The control variable (controlled variable) is the same treatment in all experiments. Because the treatment is the same, then the effect is the same in all experimental groups (controlled). The control variable is a variable that is not studied its effect and is used only as a comparison.

The annoying variable is an undesired variable, but may affect the results of the experiment. Interference variables should be avoided in order for the experimental results to be as expected.

Here is an example of variable identification in experiments on the effect of household chemical waste (detergent) on the growth of water plants Hydrilla sp.

Variables in the experiment are as follows.

• Control variables: sunlight, water, containers, aquatic plants (Hydrilla sp.), And water ,.

• Free variables: the addition of different detergents in each box.

• Dependent variable: growth of Hydrilla sp. (weight and length of plant after 2 weeks).

• Possible disruptive variables: freshness of Hydrilla sp. used may not be the same.


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