Research Methodology

In common parlance, the notion of research refers to the exploration of knowledge. In more academic jargon, research denotes the collection and the analysis of data through systematic processes to investigate a problem, a question, or to provide an accurate account of a situation. (Tavakoli, 2013). In the quest to arrive at a definition of research, often the latter is associated with science and scientific knowledge. However, not all quests fall under science as there are everyday problems that everyone encounters that also require some sort of research. Thus, one would miss the complete picture correlating research solely with science. In fact, it would be rather beneficial to ponder first the notion of knowledge and its types.

            In this regard, knowledge is often looked at as “a free-flowing impersonal resource: knowledge is said to be stored in databases and libraries, and exchanged through ‘the knowledge economy’, as information-driven commerce is sometimes called”   (Nagel, 2014).  However, arriving at an exact definition of knowledge is an arduous task. Hence, the endeavor to grasp the concept of knowledge can be achieved easily by looking at its types. First, a quick literature review on the topic of knowledge divulges varying numbers. For instance, the simplest distinction that can be found is explicit versus tacit division. The former refers to the type of knowledge that is stored in books, documents, and databases. It is transmittable through formal and systematic language  (Borzillo, 2007). On the other hand, tacit knowledge was originally defined by (Polanyi, 1962), who sees that it is more context-specific and deeply rooted in action. Thus, it is more personal as it resides first in the mind of the practitioner. Furthermore, it is rather difficult to be rendered into explicit knowledge.

            Nevertheless, the matter gets further compounded by recognizing more types of knowledge. In this vein, Drew  (2020)    lists fourteen categories:

1. A posteriori knowledge
2. A Priori Knowledge
3. Dispersed or Distributed Knowledge
4. Domain or Expert Knowledge
5. Empirical Knowledge
6. Encoded Knowledge
7. Tacit Knowledge
8. Explicit Knowledge
9. Metaknowledge
10. Imperative (or Procedural) Knowledge
11. Situated Knowledge
12. Descriptive Knowledge
13. Known Unknowns
14. Unknown Unknowns

The difference between these types of knowledge lies in how facts or information are stored and retrieved. For instance, derived from Latin “that which comes after”, a posteriori knowledge stands as the types acquired after going through an experience. Trying to teach a one-year-old toddler to stay away from the house heating water radiator can be a hard job. However, only one touch is enough for the child to understand the danger. At this age, the child develops new neural pathways to grasp new information relating to the radiator with a source of intense heat. Social constructivist theories advocate this kind of knowledge as learning by doing. In education, the latter is translated into approaches such as problem-based and project-based approaches. In contrast, a priori knowledge is independent of evidence or warrant from sensory experience. Our understanding of some logical matters and mathematics is rather a good example. One does not need to think hard to figure out that one plus one equals two. The example can be extended to tautology, deduction, and pure reasoning.

The concept of distributed knowledge implies that information is dispersed among a large and diverse population. Thus, any endeavor to gather a whole lot of knowledge in one place would call for group work as it is impossible for one agent to hold all the information. For example, the sheer complexity involved in the design of an airplane requires the corporation of several specialists supervising aspects such as aerodynamic, structure, propulsion, robotics, navigation, and control.  Each one of these experts is highly knowledgeable in their domains. Thus, everyone will have what is referred to as domain or expert knowledge.

Empirical knowledge is gathered through the senses. In research, the latter means such knowledge is acquired through observation and experimentation. Empirical knowledge is also posteriori one because it can only be obtained after going through an experience. The key difference, however, lies in the source of knowledge. Knowledge from metaphysical, reflective, or dream experience is indeed posteriori but it is not empirical as the latter are not observable by senses. 

            Often when the word knowledge is mentioned, we think of the internet, books, and documents. However, that constitutes only what is deemed to be encoded knowledge. Nevertheless, it is in our minds that information is embedded first, in a form of experiences and competencies. In this vein, (Edvinsson & Malone, 1997) describe this type of knowledge as tacit knowledge which “is highly personal. It is hard to formalize and, therefore, difficult to communicate to others” (p. 10). In academia, in order for knowledge to be shared among different parties, it has to be converted into verbal statements in the form of words, numbers, and models.

            In research, knowledge plays a major role in the attainment of results. However, a substantial amount of data can prove hard to manage. In this case, comes the importance of meta-knowledge which in short is knowledge about knowledge itself. Its concern lies in how knowledge is acquired and exploited. It is not knowing so much as knowing how to find out (Clark, 2003). In research, it is of paramount importance that one is able not only to address questions rapidly and fluently but also the ability to retrieve the same data as soon as the question is posed.

            Sometimes having knowledge is not enough to carry out a task in the right way. For example, knowing the recipe to prepare a dish does not guarantee that one will be successful in such an endeavor. Thus, what is needed is knowledge of the specific steps or processes to get the job done effectively. The latter is referred to as imperative or procedural Knowledge. This knowledge is often a subject of intellectual property terms. For instance, A company would not share secrets on how a product is manufactured.

            The term situated knowledge denotes a type of knowledge that is neatly tied to a specific context without which different loose interpretations can be offered.  It is often dependent on personal perspectives, views, and motives. Consequently, this kind of knowledge would be hard to understand without comprehending the original conditions that contributed to that knowledge. To illustrate, we usually fail to understand cultural differences when they are projected on our own because both the context and perspective are lacking.

            When it comes to storing or passing knowledge, the interest is more in factual content that gives us an accurate and reasonable picture to account for the way things are. Hence, the idea is to yield descriptive knowledge in which the main aim is to prevent indulgence in feelings when reporting information. It is opposed to prescriptive knowledge that incorporates personal interpretations often to suggest methods of intervention that are most likely to be effective. In research, these interpretations are put into a broader perspective in the form of expectations that in turn fuel hypotheses.

            Research is embarking on a journey to discover the unknown.  Yet, even what we deem to be unknown can be put into two categories. First, there are known unknowns. These refer to knowledge that is usually within our grasp of understanding. In this case, we are conscious of what we don’t know. Therefore, the solution is found by asking the right questions. For instance, a student might struggle to portray his/ her abstract thinking into a concrete concept but all that requires is a literature review to render a once unclear idea into a solid one. On the contrary, there are unknown unknowns that are beyond the scope of our thinking framework, in other words, “there are things we do not know we don't know”.

1.1.                        References

Allington, D., & Swann, J. (2009). Researching literary reading as social practice. Language and Literature, 18(3), 219–230. https://doi.org/10.1177/0963947009105850

Bayley, R., & Lucas, C. (2007). Sociolinguistic variation: Theories, methods, and applications. Cambridge University Press. http://public.eblib.com/choice/publicfullrecord.aspx?p=321456

Berg, B. L. (2001). Qualitative research methods for the social sciences (4th ed). Allyn and Bacon.

Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices.

Borzillo, S. (2007). Communities of practice to actively manage best practices (1. Aufl). Dt. Univ.-Verl.

Carpi, A., & Egger, A. (2009). The Culture of Science:Scientific Ethics. Visionlearning, POS-2(5).