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1. Students are able to understand variables
2. Students are able to identify the types of research variables
3. Students are able to understand the types and positions of variables in research
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student ability to understand concepts and explain:
1. Understanding Research Variables
2. Types of research variables
3. Study of theory-based variables
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Research variables are anything in the form that is determined by a researcher for the purpose of studying so that information is obtained about it and a conclusion is drawn.
Variables are very important in a study because it is impossible for a researcher to conduct research without variables. Most experts define research variables as conditions that have been manipulated, controlled, or observed by a researcher in a study.
Some experts also define that what is called a variable is anything that will be the object of observation in a study. From the two definitions above, it can be interpreted that the research variables include the factors that play a role in the research process itself.
This research variable is very much determined by the theoretical basis and its clarity which is confirmed by the research hypothesis. Therefore, if the theoretical basis in a study is different, the results of the variables will be different.
Types of Research Variables
According to its nature, this variable can be divided into 5, namely: The nature of the variable, the relationship between the variables, the urgency of opening the instrument, and the type of measurement scale. Here's the explanation.
2.1. Variabels seen from Relations between variables
1. Independent Variable
This variable has an influence or causes changes in other variables. So it can be said that changes that occur in this variable are assumed to result in changes in other variables.
For example, if in a study it is stated that it will try to reveal the "influence of learning motivation on student achievement", the independent variable is "learning motivation". It is called an independent variable because this variable does not depend on other variables. Meanwhile, the variable "learning achievement" depends on and is influenced by the variable "learning motivation".
This independent or independent variable is also commonly referred to as the stimulus variable, influence and predictors. In structural equation capitalization, independent variables are called exogenous variables.
2. Dependent Variable
The dependent variable or dependent is a variable whose existence becomes a consequence due to the existence of the independent variable. It is called a related variable because the conditions or variations are related and influenced by variations in other variables.
In addition there are also other terms, namely the dependent variable, because the variation depends on the variation of other variables. Then there are those who mention the output variables, criteria, response, and indogeneity.
Examples of dependent variables: If a researcher wants to reveal "the effect of learning motivation on student achievement" then the dependent variable is "student achievement". This variable is called the dependent variable because high and low student achievement depends on the learning motivation variable.
3. Control Variable
This type of variable is a variable that is limited and whose influence is controlled so that it does not affect the symptoms being studied, in other words, the impact of the independent variable on the dependent variable is not influenced by external factors that are not studied.
In some studies, this variable is not stated explicitly, but rather in experimental research. This variable requires very important control.
This is done in such a way as to reduce the complexity of the problem being studied. Besides being used for experimental research, control variables are also often used by researchers when they want to do research that is comparative in nature.
For example, the effect of learning methods on student achievement. The independent variable in this variable is the teaching method, while the dependent variable is the student's learning achievement.
The variables that are set are the same, namely the same subjects, for example, chemistry lessons. With the determination of the control variable, the impact of the magnitude of the effect of teaching on student learning achievement can be known more with certainty.
2.2. Variables seen drom Judging from the nature
These variables are grouped into 2, namely:
1. Dynamic Variables
The definition of a dynamic variable is a variable that can be changed to increase its condition and characteristics. This variable allows manipulation or changes in accordance with the objectives desired by the researcher.
These changes can be either increase or decrease. For example, learning achievement, learning motivation, employee performance, and others
2. Static Variables
Static variables are variables that have fixed and immutable characteristics, both their existence and characteristics. Under normal conditions these properties are difficult to change.
Examples such as socioeconomic status, place of residence, gender, and others.
2.3. Variable seen from Factual Urgency
Based on whether or not an instrument is important in collecting data, it can be divided into 2, namely conceptual and factual variables, along with the explanation:
1. Conceptual Variables
They are called conceptual variables because these variables are not visible in fact and are hidden in a concept. Concept variables can only be known based on visible indicators.
Examples of concept variables are learning motivation, interests, self-concept, talents, performance, and others. Because it is hidden in the concept, the accuracy of the data contained in the concept variable depends on the accuracy of the indicators of several concepts that have been developed by the researcher.
2. Factual Variables
In contrast to the above, this variable is a variable that is in fact. Examples that you can see in this variable are genes, age, region / school of origin, religion, education, and so on.
Due to its factual nature, if there is an error in data collection it is not the instrument's fault but the respondent, for example the respondent is not honest or there are bad qualities in the respondent himself.
2.4. The variable is seen from the Tips for the Measuring Scale
There are about 4 levels in this variable, namely: Nominal, interval, and ratio, here is the explanation:
1. Nominal Variable
Nominal variables are variables that can only be grouped separately in categories and discrete. Nominal variables can also be called discrete variables. Judging from the name nominal or nomi has a name meaning, this indicates that the sign or label is only used to differentiate between variables.
Examples of this variable are: Gender, religion, region, and others. The nominal variable is also the variable that has the least variation.
2. Ordinal Variables
Ordinal variables are variables that have variations in differences, levels, sequences, but do not have the same difference in distance and cannot be compared. In this sequence, a gradation or a level is illustrated, but it cannot be known with certainty.
An example is the ranking in honesty, where the difference that describes the distance between the achievement of the score / achievement of the 1st, 2nd, 3rd place, and so on is not a problem.
3. Interval variable
In contrast to the above variables, this type of variable scale can be distinguished, stratified and has the same distance from the unit of measurement results, but the similarities are not comparable and not absolute. '
For example intervals, receiving report cards from learning outcomes are given numbers 4, 5, 6, 7, 8, 9, 10 and so on. The grading scale from numbers 1 - 10 has units of 1 per unit. The distance of numbers 4 to 5 is the same as the distance of 5 to 6…. etc.
However, this number has no meaning of comparison, in the sense that the number 4 obtained by a student does not mean that the student's intelligence is half better than the student who gets a point 8.
4. Variable Ratio
The ratio variable is a variable that has a score and can be differentiated, sorted, there is a similarity in the distance of difference, and can be compared.
For example, height, a person who is 50 cm tall is half of a person who is 100 cm tall.
2.5. Variable seen from the Measurement Time Appearance
In the measurement time, the variables can be grouped into 2, namely: Maximum and typical variables. Check it out below.
1. Variable Maximum
The maximal variable is the variable that during the data collection process, there is an incentive for the respondent to show maximum performance. For example, creativity, talent, achievement etc.
2. Typical Variables
Typical variables are those in which when the process of data collection processes there is no incentive for the respondent to show maximum performance, but rather to be honest with the measured variables.
Examples include: Interests, personality, attitudes towards certain subjects etc.
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Broadly speaking, the operational variable is how the researcher will explain a variable to be studied. There are various ways of examining something conceptual, so the operational definition of a variable must be distinguished from the conceptual definition. Researchers sometimes confuse conceptual definitions with operational definitions in the research methodology chapter.
Generally there will be many alternatives to measure a variable. When the researcher has chosen the method he will do, when formulated in a sentence it will become an operational definition. Each operational definition must be correct, because it only shows what the researcher meant in his research. So we must be careful if we want to copy operational definitions from other studies. Do not let us even have difficulty measuring a variable due to differences between our research conditions and the conditions of our imitation research.
If we look in the literature for the definition of a variable that we will examine, generally what we get is a conceptual definition. Something in the form of a construct of thought about something that is general in nature. In order to be able to make the operationalization of the correct conceptual definition of a variable, we must know or estimate what can be used to measure the variable.
In general, the steps for preparing a good operational definition are as follows:
First, determine what variables will be studied. Make sure the function of each variable, whether as an independent variable, dependent variable, or outside variable.
Find an appropriate conceptual definition for each of these variables. It can be from dictionaries, textbooks, or other people's research. You can also formulate your own based on experience or summaries from various literature. The point is that the conceptual definition focuses more on the concept of a variable.
Identify what can be done to measure these variables. There is always more than one way to measure something. Can by observing, comparing with other things, asking, or other methods.
Choose what method to actually describe a variable. Make sure it is specific with clear references. For example, whether to refer to a standardized questionnaire or a completely new method. It is necessary to detail how it will treat the data obtained. In general, there are 4 levels of measurement: 1) nominal, 2) ordinal, 3) interval and 4) ratio.
Write in narrative or tabular form. Generally, the thesis or thesis is in the form of a table, while the scientific publication manuscripts are generally in the form of a narrative.
Researchers are free to define research variables
Remember that the operational definition of a variable is a specific way of measuring that variable in a study. Different studies may measure a variable with the same conceptual definition differently. If you are going to research ways to help people quit smoking, then quitting smoking will be the dependent variable in your research. You can define quitting smoking as a person who has not smoked in 1 month, or as a person who has not smoked in a year, or perhaps only a 50% reduction in the number of cigarettes smoked in the past month.
Formulating operational definitions of all variables in a study is an important step in research design. Several other conceptual variables that have many operational definitions include: intelligence, fitness, health, diet, and quality of life. Several specific and standardized or frequently used questionnaires have been developed to measure these conceptual variables.
Be careful when copying from other research
In scientific articles, an explanation of the variable under study is usually found in the method section. Be sure to rate scientific articles well before deciding to replicate the operational definition. Do not let a reference to an article instead become a source of problems in writing your scientific paper.
Hopefully, this paper can help answer questions related to how to properly formulate an operational definition of research variables. thanks.
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Research design is a bridge for researchers to get a theoretical foundation as a guideline for sources of hypotheses, this bridge is actually a form of knowledge about research conducted by other researchers in the research area. This knowledge is not only in the form of an understanding of these researches, but also the interconnections that are formed between these studies.
As is known, a study does not just appear, but it always tries to solve or answer problems left by previous research. It is this relationship, which, if put together thoroughly, compiles a "map" of the writing of the Scientific Writing and is usually expressed in the form of
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