A research study is simply an enquiry undertaken in a rigorous and systematic way with a desire to answer a question or some questions in a manner that produces conclusive answers. The answers obtained must be irrefutable and indefeasible. In order to achieve this, research studies are undertaken using universally accepted approaches, methods and techniques that have been shown to be valid, reliable and unbiased. However there is no approach, method or technique that is foolproof. The researcher has to be aware of the limitations and take appropriate steps to mitigate the effects on the final results.
Weaknesses and Limitations of Quantitative Methodological Approach
The quantitative methodological approach is well suited for research work that features the collection and analysis of a large number of data. The basic tools of analysis are scientific in nature giving an impression that it is an objective approach. Hughes (1997) points out that this view can be mistaken and that being scientific is not sufficient in establishing the legitimacy of a research approach. While the approach has some advantages such as precision and control, there are serious limitations that have to be taken into consideration in the design stages of the study.
Quantitative methods are confirmation biased. They are designed to confirm hypotheses and are not useful in the generation of hypotheses. Thus the collection, selection and analysis of data give room to criticism in the manner in which they are employed casting doubt on the objectivity of the approach. Quantitative methods are unable to account for behavioral aspect of human beings involving ethical issues, moral responsibility and free choice. Moreover the results obtained are temporal in nature and do not acknowledge that the same conditions can yield different results at different times with different people. Burns (2000) questions the notion of empiricism and objectivity in scientific study.
Weaknesses and Limitations of Convenience Sampling
Sampling is a means of extrapolation from a few chosen members to the universe of members. Although it is ideal to test the whole population, it is impracticable on most occasions to have access to all members of a defined population. The researcher has to choose a sample that is representative of the whole class in order to make inferences. There are two kinds of sampling that are generally employed, namely probability and non-probability sampling each with its own advantages and disadvantages.
Convenience sampling, sometimes known as Accidental sampling is the most common and is a non-probability type that uses individual members of a population that are readily available and accessible (Boxill et al., 1997, p.36). Sampling is based on the individual judgment of the researcher. The major drawback in this method is that the sample obtained may not be representative of the universal set from which it is drawn. In cases where human beings are subjects of the enquiry, for instance, it introduces the possibility of bias because the samples obtained may have an added dimension of motives in participating in the experiment. Hence it is difficult to make conclusive statements about the population.
Another limitation is that it is very difficult to replicate the results obtained from convenience sampling. In addition it is sometimes impossible to estimate the errors involved in the sample because the method does attempt to identify completely the population from which the sample came. However there are many occasions in which convenience sampling is sufficient for the validity of the enquiry. Researchers, for instance, would be justified in choosing this method in order to establish the existence of an attribute in a population (Cochran, 1977).
Mixed- Method Methodological Approach
The best way to tackle the weaknesses and limitations of the quantitative methodological approach is by using the mixed- method approach. The greatest advantage in this approach is that it combines the positive aspects of both qualitative and quantitative methods by collecting both types of data and developing a strategy for mixing at different stages of the study (Creswell & Plano-Clark, 2007). While the strength of quantitative methods is limited to the description of the outcomes, the mixed-methods procedure adds an extra dimension of describing and analysing the processes that are encountered in the course of the enquiry.
In so doing, it addresses the criticisms levelled against both the qualitative and quantitative approaches and presents better answers to any ontological or epistemological questions regarding the design of the experiment. A typical mixed method approach would employ an open ended interview to obtain data and proceed to analyze them using a survey technique. The researcher supports his or her claims with an appropriate theory coupled with a visual presentation of the enquiry method (Greene, 2007).
The method also includes the use of convergence and triangulation that yield not only stronger evidence to support the findings of the research study but also present a more comprehensive picture of the problem. It is a pragmatic method that is well suited to the study of practical issues that require participatory and community based approaches (Greene & Caracelli, 1997) and is potentially stronger than quantitative methods in providing multiple perspectives of the problem under review.
Strengths of Layered Sampling
Layered sampling, also known as stratified random sampling, is an alternative method that can be used to address the weaknesses and limitations inherent in the convenience sampling technique. The method involves partitioning the population into multiple groups, called strata, by identifying some common characteristics existing amongst the members. A robust statistical theory is then applied in the random selection of samples from each stratum based on the proportion of the size of each group to the population (Cochran, 1977). The underlying assumption in this sampling procedure is that there is a variety of characteristics that can be identified and that the strata are mutually exclusive. The researcher therefore has to identify characteristics in a population that results in each element in the population being able to be assigned to one and only one class. Hunt & Tyrell (2001) posit that the strength of the procedure is the degree of precision that can be achieved and that it presents coverage of the population that is even better than simple random sampling. The method presents the researcher an ability to estimate population characteristics while at the same time offering an insight into inter and intra stratum relationships. Another advantage is that the research team can be divided into groups and trained in a dedicated fashion to be able to capture the relevant details. Thus it makes it possible to use different procedures within different strata. In addition, prior knowledge of the population can easily be utilized in the design and implementation of the technique.
Boxill, I., Chambers, C., & Wint, E. (1997). “Introduction to Social research With Applications to the Caribbean”. University of The West Indies Press.
Burns, R. (2000). “Introduction to Research Methods”. London: Sage Publications
Cochran, W. G. (1977). “Sampling Techniques” (3rd ed.). New York: Wiley.
Creswell, J.W., & Plano-Clark, V. (2007). “Designing and conducting mixed methods research”. Thousand Oaks, CA: Sage Publications
Greene, J.C. (2007). “Mixed methods in social inquiry”. San Francisco, CA: Jossey-Bass
Greene, J., & Caracelli,V. (1997). Advances in mixed-method evaluation: the challenges and benefits of integrating diverse paradigms, New Directions for
Evaluation. San Francisco: Jossey-Foss
Hughes, C. (1997). Mystifying through coalescence: The underlying politics of methodological choices, in K Watson, C Modgil and S Modgil (Eds) Educational Dilemmas: Debate and Diversity, Quality in Education. (pp 413-420) London: Cassell
Hunt, N., &Tyrrell,S. (2001). “StratifiedSampling”. Retrieved from: http://www.coventry.ac.uk/ec/~nhunt/meths/strati.html