Research Methods

Development of Children’s Language Cognition Influence by Psychological Factors

Brief Description

The development of children’s language cognition is known to be influenced by various psychological factors. Among these factors are psychological disorders, social apprehension, and the standard of care (Dündar-Coecke, Tolmie, & Schlottmann, 2020). Children who may be undergoing abuse, discrimination and lack of cherishing are more likely to have slow cognitive learning progress. The quality standard of care is crucial for children to feel empowered and loved which then reflects in their cognitive learning ability. Children with psychological disorders or disabilities have major problems in interacting with their peers. This lack of social affection, anxiety issues and a profound lack of self-worthiness affects their language cognition and learning abilities.

Research Methods

Research methods are classified into quantitative research and qualitative research methods. Similarly, the data measured using these methods are simultaneously the quantitative and qualitative data. This discussion focuses on quantitative research measurement. The quantitative research method is used to estimate measurable quantities that are in other words called variables. Different variables have different levels of measurement depending on their nature. The four different scales of quantitative research measurement that scientists use are Nominal, Ordinal, Interval, and Ratio. These are incremental levels of measurement where each level embraces the roles of the prior level.

  • The Nominal scale is a labeling scale that gives names or labels to variables with no specific order.
  • The Ordinal scale puts prior labeled variables to a specific order or arrangement. Besides naming the variables, it assigns an order to them.
  • The Interval scale first names, orders, and then classifies the variables based on their distinguishing characteristics.
  • The Ratio scale assumes all the functions of the interval scale along with establishing a predetermined true zero value on all the variables.

Nominal Scale

This is the first level or scale of measurement where the variables are labeled. The researcher assigns random labels to variables with no specific order of arrangement. Nominal data can be collected using a variety of ways. First is asking non-leading questions and then assigning specific labels when reporting the responses. Another alternative is to name a multiple choice question with representative labels. An example of this is where the letter M is used in place of male while F stands for female. The nominal scale variable here is gender.

Ordinal Scale

Just like the name suggests, this level of measurement is used to assign an order to variables irrespective of their differences. This scale has no pre-determined starting point nor does it determine the distance between variables. This order assigned to variables brings out the rank and eases the researcher’s work in analyzing data. The ordinal scale could be used in analyzing grades where the order will start from best, good to poor performance. the options will then be accompanied by specific labels and tabulated for accurate analysis.

Interval Scale

In addition to the functions of the ordinal scale of measurement, the interval scale allows for the calculation of the difference between variables. Given that distance can be obtained, quantities such as mean and median are measurable when using this scale. Variables such as temperature and time are measured using the interval scale. However, the level does not prove zero as the true start value. This drawback introduces the next scale of measurement.

Ratio Scale

Alongside the functions of the interval scale of measurement, the ratio scale has a pre-determined true value. Its distinguishing characteristic is that it establishes zero as the starting value. It gives labels to the variables, aligns them in order and the difference between them is known. Given that there is a defined start value, the difference between each of the variables is the same. An estimate of one’s height and weight are exemplary variables that fall under the ratio scale of measurement.

Example 1

The nominal, ordinal, interval and ratio scales of measurement can be used in measurement research of the influence of psychological factors on children’s language cognition (Gregory, et al., 2020). The goal is to measure the influence of psychological factors such as the level of anxiety, sociability level, and the level of IQ on cognitive language. We first have to categorize the children according to their gender. Gender could be a possible factor influencing a child’s language cognition. This will therefore be a nominal-level variable where the digits 1 and 2 could be used to represent male and female or vice versa. There is no basis in ordering the representative digits and hence the variable cannot be ordinal. Also, there is no difference to be measured between the values and hence the variable cannot be measured using the interval or ratio scales.

Example 2

The factor of the standard of care will be measured using the ordinal scale. The children will be asked to rank their parent’s presence, love, and affection as very satisfying, a little satisfying, a little dissatisfying, or very dissatisfying. For accuracy, the children’s responses will be based solely on their own feelings. The ordinal scale is perfect, unlike the nominal, because the variable provides a rank from the most to the least satisfying. However, the difference between any two levels of psychological satisfaction cannot be measured nor are they similar. These aspects rule out the use of the interval or ratio scale of measurement.

Example 3

The level of IQ of a child can be effectively measured using the interval scale of measurement. This will reply to the factor of psychological disorders as an influence of the development of a child’s language cognition. IQ measurement lies in the interval level because the difference between an IQ of 40 and an IQ of 80 can be distinguishably interpreted. However, the variable does not fit in the ratio scale of measurement because of the true zero point on this scale. The child’s IQ cannot be nonexistent. Besides, one cannot conclude that a child with an IQ of 80 is twice as cognitive as a child with an IQ of 40.

Example 4

The measure of social apprehension as a psychological factor influencing the development of children’s language cognition can be measured by their level of sociability. Here, children will be required to state how many friends they have. While one child can have five friends, another can be having ten. Being a measurable value, the child with 10 friends can be said to have twice as many friends as the one with five, and hence a prediction of their sociability level. A child could also have zero friends. Therefore, this variable perfectly fits the ratio scale of measurement. With the existence of a zero true value and difference measurability, the variable does not fit in the nominal, ordinal, and ratio levels.


Dündar-Coecke, S., Tolmie, A., & Schlottmann, A. (2020). The role of spatial and spatial-temporal analysis in children’s causal cognition of continuous processes. PLoS ONE, 15(7).

Gregory, Grande, D., Brushe, Engelhardt, Luddy, Guhn, et al. (2020). Associations between School Readiness and Student Wellbeing: A Six-Year Follow Up Study. Child Indicators Research.

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Research Methods