Introduction
This is a study guide on understanding research methods in technology. It shows the logical of scientific processes, problem formulation, research design, type of research design, quantitative and qualitative, data collection, data analysis, data presentation and derives a logical conclusion from the study.
Research in technology or industrial engineering differs with research in other fields in which the subject maybe a human or natural phenomenon. In technology, the research tends to show that we can achieve advanced methods of conducting various procedures.
This does not imply that technology or industrial engineering research deviates from scientific principles of research methods. Instead, it supplements its processes with various techniques such as creating models and prototypes (Locke, Silverman & Spirduso, 2010).
Research
Research involves collecting, analyzing, and interpreting data in order to solve research problems. Research must be:
- Systematic.
- Verifiable.
- Empirical.
- Valid.
- Reliable.
Defining Research Problem
When formulating research problem, the researcher may choose an intervention program and consider the following:
- Interest: this drives the desire to complete the work.
- Magnitude: the problem should be manageable within time and with available resources.
- Problem concepts: indicators and measures must be clear.
- Relevance: the study must contribute to available works or bridge a gap in existing works.
- Expertise: the researcher must have adequate knowledge in the area of interest.
- Ethical issues: the researcher must identify potential effects on humans and must propose ways of overcoming ethical challenges.
The researcher must have a reasonable level of knowledge in the field of the research problem. A lack of such knowledge may not yield relevant results. The researcher must analyze the research problem in order to understand sub-areas, select interesting themes, formulate research questions, objectives and assess the objectives. There are overlapping research problems in some studies.
Research Questions
Research questions originate from research objectives and problems. Researchers must clearly define the research problems and questions. In some cases, the question maybe specific to the problem or the question may cover a broad area. Creswell recommends that a researcher “should ask one or two central questions, and then follows by no more than five to seven sub-questions” (Creswell, 2008).
Review of available literature
This acquaints the researcher with the available works on the research area. It is a part of the research work. It enables research clarity, enhances methodology, widens the researcher’s knowledge, and aids in contextualization of results. The review can cover books and journals on the research subject. The researcher can then develop theoretical and conceptual frameworks.
Research Design
This provides a conceptual structure on which to base the research study. It enables the researcher to collect relevant information from the available resources. The researcher must create a design that is suitable for a given research problem. He must consider:
- Research objectives.
- Appropriate method of data collection.
- Research sample.
- Tools for data collection.
- Data analysis techniques like qualitative or quantitative.
Methods of data collection
There are both primary and secondary data, which the researcher can collect.
- Primary data: firsthand data the researcher collects.
- Secondary data: these are available data from previous studies of other researchers.
Primary data focus on the research problem. The research may collect data on various factors related to the research problem. The researcher can gather such information from the laboratory through experiment, or in the field through observation. Surveys are effective methods of gathering such information. However, this method is costly and time-consuming.
Secondary data already exist. Therefore, it is not costly and time-consuming as collecting primary data. Such data are available with relevant institutions, authorities, experts, or professional in the area of a research study.
The research should gather secondary data first in order to know what data are not available. Secondary data act valuable sources of background information for the researcher. However, researchers must note that secondary data had different and specific problems to address. For instance, technology changes rapidly and such data may not be relevant for new issues, which result from technological innovations. It is advisable for the researcher to review existing secondary data before commencing the study.
Data Recording
The researcher can use a tape recorder or take notes. This depends on personal preferences of the researcher. However, recording is an effective form of capturing data from respondents.
Data Analysis
The researcher must make sense out of the collected data through analysis processes. The initial stage of data analysis involves the following steps:
- Checking for missing data.
- Ensuring that uniformity of responses.
- Checking for consistency of responses.
- Ensuring that responses are understandable.
After editing the data, the researcher must code data so that he can change the themes to numerical information. The researcher must list all responses against their corresponding codes in order to identify emerging research themes. After coding, the researcher can enter data into analysis software for analysis in order to get useful information. The researcher can present results in forms of descriptive statistics or apply advance techniques of data analysis.
Data interpretation and reporting
This is an important part of the research study. The researcher must show outcomes or findings from the analysis. In this section, the researcher must find responses to the original research problem. The report should provide detailed findings of the problem. The length of the report may depend on the purpose of the research.
Theoretical forms of Research
Applied Research
Applied research looks for solutions to known issues by focusing on specific questions. Thus, it is a practical approach to problems. The researcher can use applied research to gather information about markets, products, processes, competitors, and preferences among others.
Pure Research
This research probes unknown areas. It is not a response to a specific question or problem. It expands the existing knowledge on a field of study.
Quantitative
This involves collecting empirical data. Researchers consider it a neutral approach to research. It provides ease of counting and modeling data statistically.
Qualitative
This is necessary in cases where the researcher has not focused on a specific issue in a study. Therefore, it enables the researcher to determine relevant information for collection. The research focus becomes clear as the researcher makes progress.
Mixed-Methods Approach
This method combines “both qualitative and quantitative approaches” (Creswell, 2008). The approach relies on the strength of both qualitative and quantitative methods. Therefore, it eliminates inherent weaknesses in both approaches. It derives its value on exclusivity of both qualitative and quantitative approaches.
Correlational Research
The method focuses on the existence of a relationship between two or more variables of the study. The researcher gets data from different variables and applies correlational statistical techniques. Correlational method is complex than descriptive research because the researcher must investigate the relationship among variables after their identification.
Experimental Method
This is a data-driven research with conclusions that researchers can verify through experiment or observation. It is empirical research. It is suitable in cases where the researcher has to show that some variables may have effects on others. It has controlled variables and manipulated variables.
Such results are the best for supporting hypothesis.
Descriptive
Researchers apply this method to get information status of a phenomenon. In other words, they describe ‘what exists’ about a given research problem or variable under study.
Descriptive research applies descriptive data analysis techniques to analyze gathered data. It concentrates on a single variable at a time. This is univariate analysis. Descriptive analysis technique is an entry-level in understand a research problem. It identifies important variables in the study.
Interpretive
According to Yanow and Schwartz-Shea, interpretive methodologies lay emphasis on “the meaning-making practices of human actors at the center of scientific explanation” (Yanow and Schwartz-Shea, 2006). Some fields consider interpretive methods as a qualitative research. The researcher does not rely on prior concepts, but develop research concepts while on the field.
Interpretive research is analytical. It reveals ‘meaning-making’ procedures as it demonstrates how these procedures relate to provide observable results. Yanow and Schwartz-Shea note “there is some overlap between qualitative and interpretive research practices (notably, in their use of word-based data), but interpretive research is distinctive in its approach to research design, concept formation, data analysis, and standards of assessment” (Yanow and Schwartz-Shea, 2006).
References
Creswell, J. W. (2008). Research Design: Qualitative, Quantitative, and mixed methods approaches (2nd ed.). Thousand Oaks, CA: Sage Publications.
Locke, L. F., Silverman, S. J., & Spirduso, W. W. (2010). Reading and understanding research (3rd ed.). Thousand Oaks, California: Sage Publications.
Yanow, D., and Schwartz-Shea, P. (2006). Interpretation and method: Empirical research methods and the interpretive turn. Armonk, NY: M.E. Sharpe.