Social science and impact in early marriages in higher education settings.
Higher learning institutions have for a long time been associated with early marriages. Most youths get engaged to early sexual relationships leading to unwanted pregnancies and sexual transmitted diseases. In an attempt to cope with the results, the youths get married with limited financial sources to support these marriages.
More interactive results with most of these students associate the contents of the syllabuses in these institutions to this behavior. The students think that social science is too exploitative on affairs and social settings and these makes the youths believe that marriage at early ages can work. The following is a case study on the relationship of the social sciences and early marriage in higher learning institutions.
Research question.
What is the relationship between early marriages in higher learning institutes to the rising trend in early marriages among the learners?
Study design.
This survey is designed in such a way that the presence of the program gives the result. If the program is not given, then the probability of the outcome reduces. The dependent variable in this case is early marriages while social science is the independent variable.
- Experimental quantitative design.
Application of experimental design would provide evidence for each variable (Gorard, 2003). Experimental survey in this case rules out any external forces that lead to early marriages in higher institutions. In addition, using experimental design would imply that if the program is not implemented, then the survey would not have any results.
The whole study would be dependent on the implementation of the program, social science. The use of this design in this study means that the two variables are comparable. The validity of the data collected in this design increases by use of samples collected by random assignments. The data collected from the sample will include the number of students married and those engaged. These samples will be collected from the students who take social science. A sample of 20 respondents would be a representation of the population. The disadvantage of using this design is that, it would assume equivalence of the variables (Gravetter and Forzano, 2012).
This design can be termed as intrusive since there is manipulation and use of artificial situations to assess a causal relationship with high dependency of internal validity. This is contrary to quasi and non-experimental designs that combine both external and internal input in assessing data.
Quasi experiment.
This survey can be conducted using random samples from the population. A quasi design in this case suits the survey better than experimental designs since it would cover the non-dependence on the causal effect. A quasi design would ignore any dependency among the variables and implements a confounding variable to validate the data. This implies that the results are a combination of internal and external validity and will not establish causal and effect relationships that bias data.
Quasi experiment is easy to conduct, compared to experimental design. Use of questionnaires would provide clear results on the feelings and not the causes. This would simplify the process of data collection and analysis. However, the design is limited on unclear reasoning of associations. For instance, if the results indicate that social sciences impact on decisions on marriage, the design would not bring forward factor that trigger the decisions (Gravetter and Forzano, 2012).
Non-experimental design.
The purpose of using a non-experimental design would be to confirm that social science leads to early marriages. The results of this design are co relational and causal comparative. Using this design in this survey would bias and invalidate the data.
The main form of data collection in this case would be observation. This would involve the behavior of the students while in class and how they react to the concepts of the course. This may, however, not provide a comprehensive and detailed result; observation is more applicable in descriptive surveys. The observed samples would be accurate and consistent and can be used to make inferences about the whole population. The only limitation may be when the population (students) becomes aware of the research and tend to change their behavior.
Suggestions from an elementary school teacher perspective.
Quantitative surveys apply mathematical methods in making inferences on a study. Data collected using this method is reliable and valid since similar surveys provide similar result. A social research is more complex in the study than a scientific research. This is because such a study is threatened by risks of biasness and interpretation of correlations.
Quasi designs are more preferred in social studies than experimental and non-experimental. Quasi designs use randomized samples that are effective in summarizing and making inferences and generalizations on the larger population. The design provides more objectivity and accuracy than the others since they have supportive evidence on the generalizations that they support. Quantitative designs are better situated when it comes to ethics and elimination of bias.
However, the relevance of the inferences made from this study is dependent on the design used (Gorard, 2003). Proper choice of design enables filtering of both external and internal variables that enhance reliability. The results of a survey also influence the finalization of the results and testing of hypothesis. The research provides a reliable final answer and narrows down possible directions on further research. Non-experimental design is the weakest among the other quantitative research designs. This is in terms of causal assessments and internal validity; the design does not establish the relationships that exist between the program (independent variable) and the outcomes (dependent variable). The shortest form of a non-experimental design is that which involves observation as a data collection method. It’s a strong design especially on descriptive research surveys.
Reference.
Gorard, S. (2003). Quantitative methods in social sciences. New York, NY[u.a: Continuum.
Gravetter, F.J, & Forzano, L-A. B. (2012). Research methods for the behavioral sciences. Belmont, CA: Wadsworth Cengage Learning.
