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Abstract
Quantitative researchers always carry out literature reviews since they test hypotheses based on prior work and data in their field. It is crucial to utilize the right approach while analyzing quantitative methodology in research. According to McCandless (2010), data is a creative means, and using visualization such as tables, graphs, and charts allows for knowledge compression. As Galvan (2017) reports, reviewing quantitative academic literature is essential to obtain and enhance the research skills necessary for studying social sciences. This paper aims to analyze a research article in accordance with Galvan’s guidelines on interpreting quantitative research literature.
Introduction
Firstly, a comprehensive definition of the term “quantitative methodology” and principal features of such an approach needs to be considered. As Galvan (2017) states, quantitative research “reduces information to statistics,” which makes this kind of study easy to be detected (p. 65). For this paper, the article on social science learning by Maula et al. (2018) was chosen for the analysis. The research conducted for the study is quantitative as it uses statistical techniques and focuses on the population of 68 students in an elementary school (Maula et al., 2018). The study can be qualified as nonexperimental, and participants’ social skills were measured without any attempt to change them, based on the students’ study model (CORE or TGT). Since it is not an experiment, the participants were not randomly assigned to treatment conditions; instead, they belong to two groups. Overall, the main aspects of the article, such as the sample of participants, techniques applied, and the presentation of results, indicate that it adheres to quantitative methodology.
Related Works/Literature Review
Next, the analysis should proceed to the cause-and-effect, test-retest reliability, and internal consistency reliability of the article. Upon assessing the cause-and-effect issues, a conclusion was made that intrapersonal intelligence is decisive for students’ success in obtaining social skills with a particular study model. Namely, students with more developed intrapersonal intelligence possess higher social skills if they study with the TGT model, while students with lower intrapersonal intelligence succeed with the CORE model (Maula et al., 2018). The study does not explicitly present the test-retest reliability; however, it states that correlation and regression were used to process the data. Internal consistency reliability accounts for 0.05, which is considered relatively low (Maula et al., 2018). Thus, the data suggest that more research is needed for the higher reliability of the research results.
Material & Methodology
Another critical aspect to consider while analyzing quantitative academic literature is the validity of the measure. According to Galvan (2017), even though a measure appears valid “to the extent that it measures what it is supposed to measure,” in the real world, it cannot work flawlessly (p. 70). The article does not explicitly report the validity of the measure. However, the data by Maula et al. (2018) implies that a questionnaire evaluating intrapersonal intelligence was given to the participants, while “27% of the top rank” was classified as a high intrapersonal intelligence group (p. 583). Thus, the measure should be viewed as valid for research purposes. It helps detect the link between intrapersonal intelligence and the study model in the four-graders of an elementary school. The variable of the research might differ in studies of the same subjects (Galvan, 2017). As per Maula et al. (2018), social availability is viewed as the dependent variable of the study, while the independent variable is the “cooperative learning model with intrapersonal intelligence.” (p. 583). Overall, the validity of the measure indicates whether the research results correspond to real-world conditions.
The sampling and participants’ demographics significantly influence the outcome of the research. For the study, a random sampling technique was applied as one of the seven public elementary schools in the same area was chosen (Maula et al., 2018). Then, two parallel classes were randomly assigned as an experimental and a control class. The participants’ demographics can be determined as elementary schoolers, which corresponds to the purpose of the study and allows for the determination of social skills development in children. The researchers note a significant difference between the social skills of the two groups that study with CORE and TGT models (Maula et al., 2018). Therefore, the sampling method used for the study appears effective since the population was chosen at random and matches the research goals.
Results and Discussion
Finally, all quantitative studies should be analyzed critically and thoroughly. As Galvan (2017) argues, they are always exposed to different errors and should not be considered as a universal decision to the research issue. Maula et al. (2018) conclude that the learning model influences the students’ social intelligence by “97.89%.” (p. 584). Therefore, the students’ intrapersonal intelligence should be considered while choosing the learning model, such as CORE or TGT. However, there is space for improvement, which would allow for applying the research outcome more effectively. Given the results of the study, it can be concluded that further research can be conducted to indicate the test-retest reliability and the validity of the measure.
Conclusion
In conclusion, interpreting the research results correctly and presenting data in a coherent fashion is an essential skill in the modern world, which can be improved. In this paper, the guidelines developed by Galvan (2017) were applied to the research article by Maula et al. (2018), which uses quantitative methodology and data. The guidelines were crucial to improving the quantitative research literature interpreting and contributed to a thorough analysis of the article.
References
Galvan, J. L. (2017). Writing literature reviews. (7th ed.). (M. C. Galvan, Ed.). Routledge.
Maula, L. H., Aisyah, S., & Wardana, A. E. (2018). The influence of cooperative model and intrapersonal intelligence on social skill in social science learning for student. Universitas Pendidikan Indonesia, 580–586. Web.
McCandless, D. (2010). The beauty of data visualization [Video]. TED. Web.
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