Week #2 Berliner, D.C. (2002). Educational research: The hardest science of all. Educational Researcher, 31(8), 18-20.

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Berliner’s 2002 journal article makes the point that educational research is very hard to do because the subjects are human and in the context of education, humans are subject to a wide variety of influences and motivating factors. The government’s attempt to apply the same rigid funding and support decision making criteria used to evaluate technology and other “easy” research  is flawed because it runs the risk of being too narrow in its scope to be effective.

 

The journal article entitled: “Educational Research, The Hardest Science of All” makes its point that the government is doing a large disservice to students and scholars and those who depend on the government for guidance on the determining the value and integrity of educational research when it attempts to apply the relatively straightforward and clear measure of rigor found in quantitative analysis to educational research. Berliner highlights that researching education is difficult because, “humans in schools are embedded in complex and changing networks of social interaction.” So too are those those that attempt to impart the knowledge. Berliner ultimately sums up educational research as being done by individuals who are, “doing their damnedest with their minds, no holds barred.”

 

The Berliner article is particularly useful because it helps novice educational researchers and other interested parties better understand the current of political and collegiate environment (as it stood in 2002) and which influence the types of research work that is, or is not done in the field. It frames the opposing sides and continuum of ideas in the debate about the legitimacy, rigor and value of the work that educational researchers undertake and their approach. Berliner is effective in providing evidence for his conclusion that educational research is difficult  to do because the foundation is situated on a dynamic undercarriage that  does not allow for continuous transference  of  results across the domain unlike other types of  “easier” science such as biology and computer science.

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