– The Prevalence of Positivism in Cloud Computing and
– Postmodernism Understanding of Knowledge in Cloud Computing
Describe the field you selected and the scope and basis of your familiarity with it.
� Identify the different kinds of knowledge practitioners and researchers in the field to draw on to inform business or leadership decisions.
� Identify the philosophical assumptions underlying research and practice in the field, including operative paradigms, normal scientific and management practice, and other characteristics that seem relevant and telling in terms of their effects on the profession.
� Evaluate whether such assumptions are justified, desirable, and consciously held by practitioners and researchers in the field. Your evaluation must consider your view of the profession and how at least one approach–positivist, conventionalist, poststructuralist, postmodernist, hermeneutic, critical, or critical realists–might challenge or augment those assumptions and their practical consequences.
The Prevalence of Positivism in Cloud Computing
In the contemporary world, research studies are carried out under philosophical rubrics recognized by positivists and interpreters (Huntgeburth, 2014). These rules demand that processes of creation of theories and information should be consented by the academic communities concerned. Therefore, no new knowledge can be integrated into the field without the validation of experts in the field. This is necessary as the results are incorporated into wider applications for the benefit of wider audiences. The philosophical approach of positivism requires that scientific studies follow a deductive approach that encompasses application of mathematics and statistics in experimentation, simulation, analytical, modelling, and testing environments for proving theories (Reddy et al., 2014). In the process, it employs a quantitative approach that converts the outputs and inputs into a numerical form.
Reddy et al. (2014) utilize a positivism approach in verifying a conceptual model of cloud computing. It is based upon David Hume’s theory of the nature of reality, believing that reality is a conglomeration of individual views. He particularly emphasized the implication of all human senses in research undertakings to uncover previously unforeseeable links between various concepts. Positivism in science also incorporated Rene Descartes’s theories of epistemology, arguing that reason is the ultimate methods of creating knowledge in a particular field (Narayanan, 1998).
Positivism in dealing with challenges take a symptoms approach rather than root cause perspective. Statements valid are only those that can be subjected to empirical analysis. For a significant period, this approach plagued scientists with a plethora of problems. However, the unnecessarily tedious approaches were done away with in the second half of the 20th century, paving way for generally accepted scientific rules of research (Huntgeburth, 2014).
The field of computer science relatively employs positivist approaches in studies, often citing elements that can be perceived empirically and elucidated rationally. However, Reddy et al. (2014) states that there can be a mixture of methods in research concerning cloud computing. Interpretivism can be concurrently applied to act as a back up approach in verification of the designs applied. It is mainly used by new contributors in the field, consequently opening up minds on complex concepts for acceptability in the scientific community.
The philosophical approach of positivism stresses on in depth experimentation in isolated settings, such as labs; where complications from the external world are mitigated. This is exemplified in numerous settings in cloud computing where experiments are carried out in a monitored setting referred to as a ‘sandbox’. From the sandbox, rules and regulations concerning the proposed methodology can be established. The approach encourages a heightened form of validity especially in the context of setting. However, the approach has one main problem. We cannot deny that the results score highly in terms of internal validity; however, they are not externally valid. The relations observed in the sandbox environments may not be practically applicable (Huntgeburth, 2014).
In general, cloud computing has been well served by positive hypotheses. The philosophical view has exerted a significant stimulus in the 21st century as numerous ideas in the practice emerge. Despite some of the few setbacks of internal inconsistency in the theory, integration with interpretivism has allowed for accurate predictions. The baseline is that no solitary tactic is enough in gaining implicit knowledge of a phenomenon.
Postmodernism Understanding of Knowledge in Cloud Computing
The 21st century has particularly been hostile to positivism approaches. There is the strong urge that modern sciences should be presented as a dynamic effort towards enhancement of current studies. In computer science, it has been observed that the field is progressive, with technologists building on past concepts established at earlier stages (Beardon, 1994). It is a highly integrated field, with the encouragement of flow of ideas from one sector to another.
Rather than viewing the field as a static and enthroned field of expertise, postmodernists have always had different agendas in various contexts. It represents the implicit desire to step away from the common attitude, dethroning science as a specifically strict field. Philosophers such as Thomas Kuhn argued that despite the fact that science made progress, there existed weak means of explaining it. It lacked wholly in terms of objective truth, therefore citing innovative ways of seeing, illustrating and structuring epistemological concepts (Drolet, 2004). The West, as expected, have developed various descriptions towards modernism. It has been considered as the main thinking methodology since the end of the enlightenment period, and its cradle in disapproval in ideas represented in modern arts. Artificial intelligence is the main distinguishing factor between modernism and postmodernism
A postmodernism knowledge in cloud computing emphasizes on the pursuit of a well-functioning system that can offer reliable services according to current user needs and trends. Technological changes have had significant impact on knowledge. There are two uses of this knowledge; research and transmission (Beardon, 1994). For the first function, it provides data that can be easily understood in layman terms. Secondly, machines are becoming increasingly smaller and much dispersive. Therefore, it follows that the nature of information in this day and age must transform.
Knowledge has become the main force in production in cloud computing, rather constraining underdeveloped countries while exalting the developed ones. Science is bound to maintain its dominative eminence in the 21st century, while it is postulated to exceed limits of human understanding. The objective of truth of science have been seen as non-complacent and replaced by efficiency and performativity in various fields and professions (Drolet, 2004).
Virtual reality was a key factor of post-modernism in the computer age. As exemplified, cloud computing carried on the same, with the ‘what you do is what you get’ approach. Virtuality is ever present, concerned with appearance of unreal things made real. As postulated by the main pioneers in the field, computers and the internet offer a virtual world; in which the main act of communication occurs between the user and the computer (Drolet, 2004).
The positivism approach limited the reproducibility of a method into reality. However, it has not been completely broken from computer related activities and systems. Elements such as symbol processing and models referring to realities are still present. Nevertheless, the artificial sense of cloud computing rather brands it a postmodernism approach.
Beardon, C. (1994). Computers, postmodernism and the culture of the artificial. AI & Society, 8, 1-16.
Drolet, M. (2004). The Postmodernism Reader: Foundational Texts. London: Psychology Press.
Huntgeburth, J. (2014). Developing and Evaluating a Cloud Service Relationship Theory. Berlin: Springer.
Narayanan, A. (1998). Law, Computer Science, and Artificial Intelligence. New York: Intellect Books.
Reddy, G. T., Sudheer, K., Rajesh, K., & Lakshmanna, K. (2014). Employing data mining on highly secured private clouds for implementing a security-as-a-service framework. Journal of Theoretical and Applied Information Technology, 59(2), 317-326.