Introduction
Researchers apply several research designs when performing different types of research. A research design is important because it leads a researcher when collecting, analyzing, interpreting, and scientifically presenting data (Mitchell, & Jolly, 2012; Knight, 2010). The types of research usually vary according to the nature of data that research aims to collect, objectives of the research, and application of research. Regarding the nature of data, the research can collect qualitative data, quantitative data, or both forms of data. Grbich (2012) argues that a mixture of qualitative and quantitative data enriches and broadens research questions through integration, triangulation, and synthesis. Research can also vary depending on the objectives of the research. As objectives, research can be a descriptive and an exploratory one, which aims at describing and exploring the relationship of various variables respectively. Ultimately, research can vary according to its application, be it applied research or pure research. Thus, due to the existence of various types of research designs, the research paper assesses various research designs and recommends the appropriate design for the study, which seeks to find ways of diversifying sources of funds to enhance the financial sustainability of the Clayton County Public Library System, Georgia
Assessing Strengths and Limitations of Research Designs
Experimental Research Design
Experimental research design is a common design that scientists use in conducting research. Goos and Jones (2011) state that the main features of the experimental design are the control and experimental groups. The main strength of the experimental research design is that it allows researchers to control extrinsic and intrinsic factors, and thus enhancing the external and internal validity of the findings (Imai, Tingley, & Yamamoto, 2013). Extrinsic and intrinsic factors such as sampling, regression effect, testing, and instrumentation confound the relationships of independent and dependent variables and thus mask their causal relationships (Wang, 2011). Moreover, randomization is an important feature of experimental research design because it reduces biases, which are common in sampling (Alferes, 2012). In this view, given that the experimental research design enables researchers to control extrinsic and intrinsic factors, it is easy to establish causal relationships between independent and dependent variables. The ability to manipulate an independent variable is also the strength of experimental research design, as it enables researchers to manipulate independent variables (Stangor, 2010). According to Cramer (2012), manipulation of the independent variables is central in the establishment of the direction of causation.
Despite its strengths, the experimental research design has some limitations. One limitation of the experimental research design is that it has a weak external validity because researchers are unable to replicate circumstances that are present in a real-life situation (Thomas, Nelson, & Silverman, 2011). The experimental research design is applicable in a laboratory environment where a researcher controls extrinsic and extrinsic factors and consequently manipulates the independent variable to establish the existence of causality. In essence, the experimental conditions are different from the conditions in the real world (Gravetter, & Forzano, 2010). Thus, it is impossible to generalize the findings of experimental studies and apply them in a real-life situation without making some assumptions. Moreover, experimental research design has a weak external validity due to skewed representation of the population. Alferes (2012) asserts that, as the experimental research design relies on participants who volunteer, the participants do not reflect the general population. Hence, self-selection bias affects the external validity of the findings obtained from the experimental research design.
Quasi-experimental Research Design
The quasi-experimental research design is the application of experimental research design in natural settings. By applying the experimental research design in natural settings, the quasi-experimental research design enhances the external validity of a study, which is the strength of the design (Gravetter, & Forzano, 2010). In this view, the findings of the quasi research design have a strong external validity, which enhances their generalizability. The use of natural settings reduces the ability of the researcher to manipulate the conditions of research. Furthermore, the absence of randomization is the strength of the quasi-experimental research design because it reduces biases associated with sample selection. Boslaugh (2012) argues that quasi-experiment allows researchers to utilize natural settings without assigning participants to control and experimental groups. Hence, the quasi-experimental research design is applicable in situations that do require control and experimental groups, due to ethical and practical restrictions.
The limitation of the quasi-experimental research design is the prevalence of confounding variables. Confounding variables reduce the internal validity of the findings and consequently weaken their external validity (Stangor, 2010; Kumar, 2010). Usually, researchers make ambiguous inferences because confounding variables distort the findings. Huitema (2011) argues that spurious effects are common in quasi-experiments because researchers are unable to eliminate the confounding variables. The inability to manipulate the independent variable is another limitation of the quasi-experiments. Cramer (2012) asserts that since researchers are unable to influence the independent variable, they infer the direction of causation based on the assumptions and theories. Therefore, the quasi-experimental design has a weak internal validity due to spurious effects of confounding variables, and theoretical establishment of the direction of causation.
Cross-sectional Research Design
Like quasi-experimental research design, cross-sectional research design relies on the natural settings in experimenting. The use of natural settings as experimental conditions is the strength of the cross-sectional research design because it enhances the external validity of the findings. Elmes, Kantowitz, and Roediger (2011) explain that cross-sectional research design applies descriptive and observational approaches in analyzing a given phenomenon in natural settings. Thus, the cross-sectional research design has strong external validity. Furthermore, the lack of randomization is also the strength of the cross-sectional design (Gravetter & Forzano, 2010). The lack of randomization avoids biases, which usually influence the assignment of participants to control and experimental groups. Babbie (2012) identifies the descriptive ability of the cross-sectional design as the strength. Since the cross-sectional design describes the association of variables, it provides an in-depth view of a given study.
One limitation of the cross-sectional design is that it is prone to spurious effects, which emanate from confounding variables because researchers are unable to control the extrinsic and intrinsic variables (Little, 2013). The second limitation is that the cross-sectional design is prone to selection bias. Treiman (2009) holds that selection bias is a limitation of the cross-sectional design because it entails the selection of participants or objects of study. As a third limitation, the cross-sectional research design aims at proving the existence of an association between variables but does not aim to prove the existence of causation between independent t and dependent variables of a study (Alder & Clark, 2010). Thus, one cannot establish causal relationships using a cross-sectional design.
Recommendations
Appropriate Research Design
The most appropriate research design for the quantitative study is the cross-sectional design, the descriptive one. Since the study aims at describing the association between sources of funds and financial sustainability of Clayton Public Library System, a descriptive form of cross-sectional research design is appropriate. Gorard (2013) explains that descriptive research describes trends of a given phenomenon, and therefore, it provides the basis for projecting certain trends. In this view, given that the study focuses on the trend of financial sustainability, descriptive research is appropriate.
Moreover, the cross-sectional design is appropriate because the study seeks to examine property-disposition relationships (Mangal, 2013). The property of the study is the source of funds, while the disposition is the financial sustainability of the public library. To establish the existence of an association between sources of funds and the sustainability of the public library, long-term projections are necessary. In this view, the research questions and hypotheses focus on the long-term financial sustainability of the public library using diverse sources of funds. Beryman (2012) asserts that the cross-sectional design is appropriate in establishing the existence of an association among variables over a long period. Given that the existence and direction of causation are obvious, what is essential is the association between sources of funds and the financial sustainability of the public library.
Given that the study will utilize quantitative data in terms of funds to establish their use in enhancing the sustainability of the public library, it fits descriptive research. Quantitative data plays a central role in the descriptive study because statistical analysis produces descriptive statistics, which provide a snapshot of the relationships among variables (Richardson, Goodwin, & Vine, 2011). Therefore, the study would utilize descriptive statistics in analyzing and presenting the findings.
Inappropriate Research Designs
The experimental research design is inappropriate to the study because research questions and hypotheses do not meet its requirements. The experimental design is appropriate in a study that seeks to compare a group or more groups with the control group (Kabe, & Gupta, 2010). Moreover, the experimental design is applicable in a laboratory environment where one can control independent variables and eliminate confounding variables. However, although it is possible to control sources of funds, as an independent variable, it is difficult to eliminate confounding variables that influence the financial sustainability of the public library.
The quasi-experimental research design is also not appropriate for the study because the questions and hypotheses do not require the comparison of control and experimental groups. Thyer (2012) argues that the quasi-experimental design utilizes natural settings as a laboratory environment and creates control and treatment groups. Hence, given that the research questions and hypotheses do not seek to compare any form of control and treatment groups, they do meet the requirements of the quasi-experimental design. Since it is impossible to control the independent variable of the study, which is sources of funds, the quasi-experimental design is not suitable.
Conclusion
Research designs that researchers apply in various studies vary according to the nature of data, objectives, and application of research. Experimental research design, quasi-experimental research design, and cross-sectional research design are common designs that researchers apply in a quantitative study. Assessment of these research designs indicates that each of them has different levels of strengths and limitations, which relate to the external and internal validity of a study. While experimental research design has a weak external validity and strong internal validity, quasi-experimental design and cross-sectional research design have strong external validity and weak internal validity. Assessment of these designs reveals that the cross-sectional design is appropriate in the study of the financial sustainability of the public library. Thus, the assessment recommends the application of cross-sectional design and descriptive research in the study of financial sustainability of public libraries due to diversification funds.
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