Knowledge Creation, According to Borland (2001), Requires

¶ … Knowledge creation, according to Borland (2001), requires the systematic analysis of data collected. Best & Kahn (1998, pg. 18) write that "research" has been classically defined as "the systematic and objective analysis and recording of controlled observations that may lead to the development of generalizations, principles, or theories, resulting in prediction and possibly ultimate control of events." The post-positivist paradigm, as Mertens (2005) writes, provides that research is designed to develop confidence that a given claim to knowledge about a particular phenomenon is either true or false, based on collected evidence from objective observations. How researchers collect information, however, depends on the circumstances surrounding the phenomena under examination, the abilities and resources of the researcher(s), as well as pragmatic considerations given the human element.

Among the methods used to conduct systematic inquiry in the social sciences are the qualitative method and the qualitative method. Taylor and Bogdan (1998) note that research methodologies differ given the means by which researchers approach methods of inquiry to better understand social phenomena. While both quantitative and qualitative research designs are empirically based, they differ significantly in not only how each research design measures phenomenon, but also differ as to what is actually measured. These differences go far beyond the simple dichotomy of qualitative research uses words and quantitative research uses numbers. Cupchik (2001) notes that, while all research involves assumptions about ontology, or how the world works, there are important differences between qualitative and quantitative research; while quantitative research methodologies assume a positivistic perspective, qualitative research methodologies tend to assume a naturalistic, phenomenological, or existentialist assumption about reality. This paper will identify three characteristics of both qualitative and quantitative research designs.

Characteristics of qualitative research

Gay (1996) observes that qualitative research studies are primarily oriented toward discerning differences in quality, rather than quantity, as is the case with quantitative research. Qualitative research involves analyzing social phenomenon with words and pictures, and, as such, qualitative researchers collect narrative data to better understand social issues. Because qualitative research involves constructivist methods for data analysis, the goal of qualitative research is to better understand the world views of research participants. Smith (2005, pg. 107) writes that issues in the qualitative realm concerning researchers is how to connect the "actualities of people's lives" with a concentrated focus of inquiry, yet with a properly positioned humanistic perspective.

There are four main methods of data collection in qualitative research designs. Interactive interviewing involves the solicitation of individuals to verbally describe their own experiences for a selected phenomenon. Written descriptions involve having researchers ask individuals to write descriptions of their experiences. In the observation method, which involves both formal and informal observations of research participants, researchers simply observe both verbal and non-verbal cues of those individuals under investigation. Focus groups involve analyzing data on cultural norms and mores of a selected group of individuals so that the researcher can better understand how differing groups approach social problems. So significant are the personal experiences of research participants, Armour (2002) notes, that every participant's experience, being individual and personal, must be relevant as the only real truth to that individual.

In an effort to gain a better understanding of human behavior, as well as the attendant justifications and reasons dictating human behavior, qualitative research methodologies investigate the underlying reasons for decisions, actions, behaviors, and thought processes in research participants. Because this level of analysis is necessarily deeper in investigative analysis, qualitative research typically involves less research participants than do quantitative research methodologies (Adler and Adler, 1987).

Among the benefits of qualitative research design methodologies is the ability of the researcher to selectively choose which phenomenon to analyze, with purposeful and directed foci of inquiry. However, this can lead to researcher bias and calls into question the ability of the researcher to remain neutral and detached from the human subjects studied.

Characteristics of quantitative research designs

Quantitative research designs are generally associated with numerical data, mathematical analysis and statistical inferential data sets. To increase the generalizability of research data as well as to provide increased statistical power, qualitative research designs typically require greater numbers of research participants than do qualitative research designs. Quantitative data involves implementing variables that are easily analyzed via statistical analyses, and, consequently, relatively easily to externally verify through such statistical formula.

Experimental research involves the administration of a treatment, or intervention, to a participant group while controlling for other variables that can impact observed results. Creswell (2003) writes that the experimental design often involves assigning participants to either a control group or an experimental group before the administration of a treatment, allowing the results to reasonably be attributed to the introduction of the treatment.

Quasi-experimental research is similar to the experimental design without the random assignment of groups (Mertens, 2005). Studying groups as they exist, the researcher quantifies the effects of a given intervention without having first randomized participants into control and experimental groups. Neuman (2006) suggests that quasi-experimental research permits researchers to examine correlations or relationships when experimental research is either not possible or not practical.

Non-experimental, or survey, research is widely used in the social sciences. Sproull (2002) writes that the benefits of surveys in quantitative research include the ability to gather data from larger groups of people than is typically possible from either experimental or quasi-experimental research designs. Because surveys are contingent upon the reports of research participants, the validity of the data reported may be compromised. Surveys allow the research to assign a numeric identifier to reported attitudes, beliefs or perceptions (Creswell, 2003). Using the survey, researchers are able to measure associations or relationships among reported variables with statistical measurements (Neuman, 2006). Controlling for extraneous variables, the survey allows the researcher to claim with a certain level of statistical certainty or significance that a claimed correlation exists; causality can never be established. Once the researcher decides to use a survey, the researcher ascertains the propriety of collecting the data from one group of participants at one point in time, from several groups at one point in time, or from one or more groups over an extended period of time. Each design has specific strengths and weaknesses.

The descriptive survey involves analyzing a single group of participant experiences at one point in time. However, the descriptive survey cannot analyze participant experiences over time and does not allow for comparisons to other sample groups. The advantage of the cross-sectional research design is the ability to collect data from groups of participants in a short time period (Mertens, 2005). However, the cross-sectional survey design is not able to indicate changes in participant experiences over time; the responses in the survey only provide information at one point in time. The longitudinal survey design allows for changes of participant experiences over time, but is expensive to conduct. Once the data collection is complete, the researcher manipulates, interprets and presents the data in ways such that the quality, or validity, of the research varies.