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Education, Pages: 4

Research Design – Quantitative

Research Design – Quantitative

Part 1: Definitions
Personal Definition: Definition:
Quantitative research design deals with quantities. Numeric values are the most essential aspects that researchers use in the design to evaluate and understand phenomena in their studies. The success of quantitative research depends on their statistical backgrounds. Researchers without mathematical or statistical knowledge experience challenges when computing and analyzing quantitative data. Quantitative research is an effective research design in most fields. Definition:

Quantitative is a research design that involves collecting and analyzing numerical data. Quantitative research deals with numbers, logic, and objective stances (Clark et al., 2021). The information gathered from quantitative research helps the researcher uncover trends, evaluate data averages, and reveal hidden insights about specific data. Researchers employ statistical techniques when assessing and analyzing quantitative data. Quantitative data is collected using various methods, such as surveys.

 

Reference: Clark, T., Foster, L., Bryman, A., & Sloan, L. (2021). Bryman’s social research methods. Oxford University Press.
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Part 2: Explore with Words
Synonym: Antonym:
Quantifiable, numerical, computable, calculable, gaugeable, measurable Unmeasurable, insignificant, undeterminable, imperceptible.
Words associated with: Sentence:
Hypothesis testing, subjective, predictive, objective The teacher instructed the students to collect quantitative information about human intelligence.
Part 3: Purpose and Quality Indicators
Answers Research Questions about:
Quantitative research helps researchers answer the questions “how many” and “how often.” The research questions provide a numeric answer that a researcher computes to understand the relationship between variables. Quantitative research questions provide numerical data related to different aspects of the study. Quantitative data provide adequate data to support or reject hypotheses associated with a specific research. Researchers use outcomes from quantitative research to understand and predict future expectations of a particular phenomenon. The quantifiable values help researchers understand the correlation between the independent and dependent variables under investigation. Also, quantitative data helps a researcher identify different groups’ similarities and differences.
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Characteristics:
Use of statistical analysis and techniques.

· Utilizes a large sample size to represent the study population.

· Use of measurable data.

·  Collects data using standardized research tools, such as surveys and questionnaires.

 Incorporates deductive reasoning when testing hypotheses.

·The design emphasizes objectivity (Philo-Note Admin, 2022).
Sampling / Participants
The sampling process helps researchers to obtain a sample size that is large enough to represent the entire targeted population. Researchers use probability techniques, such as simple random sampling, cluster sampling, systematic random sampling, and stratified random sampling, to set the representative sample from a large population. Also, non-probability methods, such as self-selection, snowball, and quota sampling, are used mainly in health studies. The sample size is essential for the reliability of the results obtained from quantitative research. The sample contains the research participants who provided expected data processing and analysis information. Research objectives and scope influence the sampling technique incorporated in research.
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Intervention Fidelity / Independent Variable
An independent variable is a variable that contributes to changes and is expected to cause changes to other variables in the research (Pandey & Pandey, 2021). The researcher has control over the independent variables. Sometimes, the researcher presumes the changes attributed to the variable, evaluating the changes among other variables. The independent variables have a significant on the expected results from an investigation. Researchers manipulate independent variables to impact the research, which helps them achieve intervention fidelity. The researcher exposes all participants to the same intervention dose by controlling the independent variables and ensuring that the interventionists have standardized skills to monitor and evaluate the outcomes to eradicate bias.
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Instrumentation / Measures
In quantitative research, researchers use various instruments and tools to gather data for analysis. Some commonly used instruments include questionnaires, surveys, interviews, and controlled observations. A researcher designs closed-ended questions in structured interviews or surveys, guiding the participants on the responses expected in a specific study. The reliability and accuracy of the results depend on the consistency of the procedures and the instruments incorporated in data collection. Notably, the type of quantitative data analysis influences the instrument used to collect and record information. Also, researchers should consider the ethical implications of the instrument to protect participant confidentiality. The instrument used in the research should promote efficient data analysis.
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Internal Validity
Internal validity shows the extent to which a researcher conducts a study without bias, enhancing the accuracy of the results obtained about the studied group. Internal validity portrays a researcher’s confidence in the research findings. The quality indicator helps individuals understand how research findings were acquired. A researcher achieves accuracy in results when no factor opposes their outcomes. A study with low or no contradictory cases between the cause-and-effect relationships of independent and dependent variables increases its internal validity (Villegas, 2024). A higher degree of internal validity encourages replicability, where study reviewers can adopt the research design and methods in different research to obtain similar results. A researcher’s bias significantly affects a study’s internal validity.
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Outcome Measures / Dependent Variable
The dependent variable is the primary concern of a researcher in any research. It is the variable whose findings are monitored, evaluated, and analyzed following the independent variable manipulation. The dependent variable represents the outcomes in a study, which researchers are interested in measuring. The dependent variable helps researchers record the study findings, which allows them to analyze the extent to which the independent variable influences the outcomes. The dependent variable is the effect recorded depending on the changes manipulated on the independent variable (Pandey & Pandey, 2021). For instance, in a study investigating the impact of different treatments on body pressure, blood pressure is the dependent variable since the researcher measures the changes in blood pressure depending on each type of treatment.
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Data Collection / Analysis
A researcher collects quantitative data from a specific study’s determined sample size using quantitative methods, such as interviews and surveys. The data collection method influences the participants’ responses. Hence, a researcher should identify the most effective data collection method to increase the accuracy and reliability of the information obtained from the study. A researcher may incorporate two different data collection methods, where information from each method is analyzed to help the researcher identify contextual trends. When analyzing the data, researchers can identify inconsistencies, which allows them to focus on the most accurate responses to conclude. Researchers analyze the collected data as descriptive or inferential.
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Part 4: Strengths, Weaknesses, and Critical Issues
Strengths: Weaknesses:
Quantitative research is preferred due to its objectivity and accuracy since it uses numeric data that is statistically analyzed to understand phenomena (Clark et al., 2021). A researcher’s reasoning does not affect the results.

The research design uses a large sample size, allowing broader generalization of results effectively representing the targeted population. A researcher can also derive more findings from the large sample size, increasing the accuracy of their findings.

Quantitative data collection methods make data gathering faster and easier. A researcher may use digital and automated techniques like mobile surveys to gather information, requiring less effort.

The efficiency of the data collection methods makes quantitative research cost-friendly. Compared to qualitative research, less resources and effort are required to conduct quantitative research.

Quantitative data is easy to analyze, enhancing the generalization of the conclusions. When research uses online surveys, data can be categorized and processed faster, where one can apply different filters to obtain an in-depth understanding of variable relationships.

 Quantitative research requires a large sample size, which may be time-consuming in identifying the best representation of the large population. Using a small sample size increases the inaccuracy of the study findings and makes the results ineffective for generalization.

Quantitative research is subject to confirmation bias. Most researchers tend to favor responses that support their beliefs on the study. Researchers may rush to conclusions when the data aligns with their research goals.

Despite the objectivity and accuracy of quantitative data, the numerical representation of information does not explain the ‘why’ questions of the responses.

Quantitative research is a limiting design. Researchers often develop structured questionnaires with close-ended questions, limiting the outcomes since participants lack the freedom to express their feelings (Clark et al., 2021).

Quantitative research requires the researcher to be proficient with mathematical and statistical knowledge since data analysis requires intensive statistical analysis. Lack of statistical skills poses challenges in data analysis. Quantitative data is also ineffective in most studies, such as natural phenomena.
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Critical Issues to Identify:
When reviewing this type of design, it is critical to look for …

A researcher should identify the right sample size since the sample should reflect and represent the targeted large population.

Quantitative research may be time-consuming. Hence, the researcher should design simple and direct questions reflecting the expected outcomes to avoid wasting their participants’ time analyzing and understanding the questions.

Quantitative researchers should focus on honesty and value the contribution of all participants. The researcher should not focus on their own opinion, which negatively influences the accuracy of their findings.

The researcher should keep data analysis at the forefront of the research since it influences the research questions and the data gathered.
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What Will Help Me Remember:
Quantitative research design is easy to remember since it deals with logic and numbers. Also, it requires a large sample size to understand a phenomenon.
Unique to Special Education:
How does this research design meet unique needs in special education? What unique problems does this design have when implemented in special education?
Quantitative research can help educators identify student performance and behavior trends. Educators can use the design to identify factors that hinder the performance of students with special needs.

Educators can utilize quantitative research to evaluate the effectiveness of implemented interventions in the classroom by analyzing their effect on students’ performance.

Policymakers can use quantitative research to develop effective policies that support inclusion in education.

 Students with special needs encounter varying challenges in their learning environment. Hence, quantitative research design may be ineffective in identifying the unique challenges the different student presentations encounter.

Educators face resource constraints when conducting quantitative research in special education due to the large sample sizes needed.
Prominent Researchers:
Clark T., Foster L., Bryman A., Sloan L., Pandey P., Pandey M., Vellegas F.
Resources: (websites that might be most helpful)
PHILO-notes:

https://philonotes.com/2022/05/strengths-and-weaknesses-of-quantitative-research

 PHILO-notes:

https://philonotes.com/2022/05/characteristics-of-quantitative-research
FreeOnlineSurveys:

https://freeonlinesurveys.com/survey-research/quantitative-data-collection

 QuestionPro:

https://www.questionpro.com/internal-validity/

References
Clark, T., Foster, L., Bryman, A., & Sloan, L. (2021). Bryman’s social research methods. Oxford University Press.

Pandey, P., & Pandey, M. M. (2021). Research methodology tools and techniques. Bridge Center.

Philo-Note Admin. (2022, May 16). Characteristics of quantitative research – PHILO-notes. PHILO-notes – Free Online Learning Materials. https://philonotes.com/2022/05/characteristics-of-quantitative-research

Villegas, F. (2024, January 25). Internal validity in research: What it is & examples. QuestionPro. https://www.questionpro.com/blog/internal-validity/

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Question 

Overview

In order to become more familiar with the different research designs, you will complete three Research Design Assignments in this course.  For each Research Design Assignment, you will focus on the one assigned research design and state the design’s definition, purpose, characteristics, quality indicators, strengths, weaknesses, and critical issues.

Research Design - Quantitative

Research Design – Quantitative

Instructions

Using the Research Design Template provided for each of these three assignments, complete each section of the template by answering each prompt. You must incorporate at least one citation per section from a scholarly journal and list the word count for each section where requested.

Word requirements are as follows:

  • Part 1: 50-word minimum
  • Part 2: No word count requirement
  • Part 3: 100-word minimum
  • Part 4: 150-word minimum

If a question or section on the template does not have a word count listed within the questions, it does not have a word count requirement. Formatting and references must reflect current APA compliance.