Part 4: STRENGTHS AND LIMITATIONS OF QUANTITATIVE RESEARCH DESIGNS

One benefit of conducting experimental research is that it enables researchers to confidently attribute the results to the experiment's effects. This differs from descriptive and correlational research, which uses fewer rigid approaches to explore and describe phenomena and may not yield clear conclusions. Experimental research's scientific and statistical rigour maximises internal validity and increases the likelihood of generalising findings beyond the study sample. However, it is essential to note that the literature highlights methodological limitations that could impact research results' internal and external validity, ultimately limiting their practical applications (Walker, 2005).

Achieving sample randomisation in a study is essential for ensuring that the sample accurately reflects the parent population and that the findings are generalisable. Without randomisation, it can be challenging for researchers to match participants based on critical traits that could impact the study's outcomes. Even with systematic and protocolised procedures in place, external factors can still influence the results of experiments with humans, especially in longitudinal research designs.

Challenges to validity, both internal and external, as well as the Hawthorne effect, pose limitations to experimental research. Participants may alter their behaviour simply because they are observed, prompting researchers to adopt a 'double-blind' technique. Additionally, reliable, and validated outcome measures are crucial for meaningful results. Quantitative research designs can contribute significantly to the evidence base, while descriptive and correlational designs are essential for generating questions and hypotheses. Despite rigorous procedures to control error and bias, ethical and methodological concerns remain for experimental research.

A sound research design aims to reduce bias and increase the dependability of the data gathered and analysed. The design that produces the least experimental error is typically considered the optimal approach in scientific inquiry. Likewise, a suitable and effective design results in the acquisition of comprehensive information and enables consideration of various facets of a given problem. The traits of a robust research design include:

• Accuracy is crucial regarding the methods used to collect data and evaluate responses. To ensure Objectivity, it is essential to implement unbiased measuring tools that deliver consistent results, regardless of who performs the evaluation.
• Reliability, in turn, refers to the degree of consistency in responses obtained from multiple measurements. Essentially, if a participant offers a specific response to a particular question, they are expected to provide the same response if the question is posed again. Any fluctuations in their answers may weaken the Reliability of the data gathered. As such, researchers must design their surveys to ensure Reliability and consistency in the responses obtained.
• Quantitative Research Design faces a significant obstacle in accurately measuring intended variables. The validity of a measuring device or instrument must be deemed valid by measuring only what it intends to, and this quality can be demonstrated. For example, an IQ test should only measure intelligence and use appropriately framed questions. To estimate the validity of measures, including facial, convergent, discriminant, and predictive validity, agreement with available literature and quantitative analyses of consistency and available predictions are necessary despite the constantly evolving nature of measures.
• Generalizability refers to applying data collected from a sample to a larger population. It is crucial to design the research study carefully to ensure that a researcher's findings can be generalized. This involves accurately defining the population, selecting an appropriate sample, conducting proper statistical analysis, and ensuring that the study's conclusions can be applied to the population.

Sufficient information is essential to analyse the research problem from a broader perspective, create an effective research design, and identify important factors such as research objectives, methods for obtaining information, skilled human and financial resources availability, minimizing bias, and maximizing reliability and generalization. An ideal research design should be flexible, adaptable, efficient, and cost-effective.

The research design is the foundation for data collection and analysis. It outlines the methods and procedures for measuring and analysing data, allowing investigators to investigate research questions and establish the conditions for data collection and analysis so that the findings of a sample can be generalized to the larger population  (Kuçuksayraç, 2007).

A research design is a foundation for data collection and analysis in a study. It outlines the methods and procedures, serving as a blueprint for measuring and analysing data. This strategy enables investigators to investigate research questions and arrange the conditions for data collection and analysis in a manner that permits the findings of a sample to be generalised to the larger population (Pandey & Pandey, 2015).

Choosing the appropriate research design is crucial while conducting research. It involves considering various factors, from broader assumptions to specific data collection and analysis techniques. It is essential to note that there is no fixed order for making these decisions, and they should depend on what is most relevant to your research objectives.

Research approaches consist of many plans and procedures that guide the steps from broader assumptions to detailed data collection, analysis, and interpretation methods. When selecting an approach to study a topic, you need to consider the philosophical assumptions, procedures of inquiry (research designs), and specific research methods of data collection, analysis, and interpretation. Your choice of a research approach should be informed by the nature of the research problem or issue, your personal experiences, and the intended audience. These three elements - research approaches, research designs, and research methods - provide a framework for understanding the perspective of research.

Ultimately, your research design will depend on various factors, such as the problem or issue you are investigating, your personal experiences, and the audience you intend to reach. For instance, quantitative research may be the most suitable approach if you aim to test objective theories by examining the relationship between variables. This method involves measuring variables using instruments, which generates numerical data that can be analysed using statistical methods (Creswell, 2014).

A design or structure must be established to begin data collection or analysis in social research. However, a research design is more than just a work plan. While a work plan outlines the steps necessary to complete a project, it is based on the research design. Essentially, the function of a research design is to ensure that the evidence collected allows us to answer the initial question clearly.

It is important to note that research design is a logical problem rather than a logistical one. In social research, factors such as sampling, data collection method, and question design are all subsidiary to the question of what evidence needs to be collected. Unfortunately, many researchers jump into designing questionnaires or conducting interviews before considering what information they need to answer their research questions.

It is also essential to distinguish between the research design and the data collection method. The data collection method has no bearing on the logic of the design. Explanatory research seeks to develop and evaluate causal theories, but in social sciences, causation is probabilistic rather than deterministic. This is why the role of research design is so crucial - it minimises the likelihood of drawing incorrect causal inferences from data. When designing research, the type of evidence needed to answer the research question convincingly must be identified.

The research purpose serves as a statement explaining why a study is being conducted and what the study aims to achieve. It typically involves identifying, describing, explaining, or predicting a specific concept, situation or solution. The purpose statement is important because it clarifies the variables, population, and setting for the study, and it is usually derived from the research problem. The purpose statement must be objective and free from any researcher's biases or values to ensure the research is credible and trustworthy. Typically, the purpose statement comes after the research problem and supports it by clarifying the knowledge generated through the study (Durand, 2023).

Quantitative research is rooted in deduction. This type of research is guided by theory, meaning it begins and ends with theory. Before embarking on any research project, researchers need to become acquainted with the relevant literature. This involves understanding the established theories and explanations about the phenomenon being studied and identifying gaps or controversies in the existing knowledge (Fig. 13.). By utilising this knowledge, researchers can develop hypotheses to address these gaps or controversies. The primary aim of quantitative research is to test existing theories using new quantitative data to establish the limits of a theory or determine the conditions under which it applies. Regardless of the research question, it must always be derived from the theory. A well-formulated research question should be pertinent and have the potential to make a theoretical contribution to the literature. It should either add to, modify, challenge, or fill gaps in the existing theory or controversies (Stockemer, 2019).

A well-crafted research design is the key to efficient and cost-effective research without compromising the accuracy of findings. It lays the foundation for the entire research journey and ensures that all aspects of the project are meticulously planned to yield valuable insights. With a solid Research Design in place, scaling becomes effortless, and resources are allocated judiciously, thus making it an indispensable element in accomplishing research objectives.

Proper research design is also crucial when mapping out methodologies for collecting pertinent data and analysing techniques while considering research objectives, staff time, and budgetary constraints. Failing to prepare a research design properly can harm the entire project (Pandey & Pandey, 2015).

Research design is like a blueprint for seamless research operations, much like a blueprint or map is necessary for a house's efficient and aesthetically pleasing construction.

Furthermore, research design offers an overview of the research process, allowing field experts to provide valuable input. It also assists investigators in organising their thoughts and identifying any potential flaws.

Ultimately, research design provides a clear trajectory for all parties involved in the research project, guaranteeing a coordinated and successful outcome.