Evidence-based Educational Research and Decision-Making
There are different ways of evidence acquiring real or perceived authority for educational research and decision-making. First, evidence must be easy to access, as only the studies that can reach the policy-maker can be implemented into practice (Finnigan & Daily, 2013). Second, the researches should be not purely strategic; instead, they must offer specific steps to be translated into practice (Finnigan & Daily, 2013).
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Third, the evidence must come from a trustworthy source, as emotional connections can override rational perception and evaluation (Finnigan & Daily, 2013). It also worth mentioning, that research mediators is another factor that influences educational research and decision-making. As there is a considerable gap between the producers and users of the evidence, one must intermediary organizations become “brokers” of research results. Therefore, they can promote their ideas by selling only the findings that are beneficent for the organization rather than for the policy-makers (Finnigan & Daily, 2013). In brief, due to an abundance of data one must distinguish between the genuinely useful and evidence-based innovations and seemingly effective.
I believe that the evidence relevant for decision-making should be as close to gold standard as possible; at the same time, it should be acquired in school settings. While this kind of evidence is costly and slow to get, it is still the most reliable source of evidence (Means & Anderson, 2013). Although contemporary reality shows a need for updating the standard, better practices are yet to be discovered.
One of the possibilities to bridge the gap among research, policy, and practice is to use big data. Due to the abundance of relevant information available with the help of new technology, researchers can use this kind of data to acquire new options for policy-makers (Means & Anderson, 2013). Evidence obtained from big data can provide cheaper, more effective, and more politically feasible alternatives for decision-makers, which crucial according to Alexander (2013). Therefore, the use of modern technology has the potential to help in the matter.
Finding a Balance
Technologies that support online learning have become outstanding instruments for professors and students to practice collaboration skills. At the same time, there arises a privacy concern, as students produce and share an enormous amount of digital data that must be protected. Since avoiding collaboration tools is not a viable option, educational institutions, teachers, and students must elaborate means of ensuring safe utilization of the online tools (Schrameyer, Graves, Hua, & Brandt, 2016). The present paper offers three ways of preserving students’ privacy.
First, the educational process forms learning communities where privacy becomes a group responsibility. Therefore, according to Dennen (2015), these groups should develop and maintain privacy expectations. Professors are to define what data should not be used outside the educational settings and encourage their students not to share the information with third parties (Dennen, 2015). This simple intervention can promote the atmosphere of trust and mutual responsibility.
Second, as modern technology is not perfect in the question of data protection, all the member of the learning community should acknowledge the possible flaws. Privacy standards should be documented with the help of the informed consent form to ensure the appropriate use of data (Slade & Prinsloo, 2013). This form enforces the privacy expectations from the legal point of view. Therefore, such a practice can be useful for protecting private data.
Third, outside online services can be used to ensure FERPA compliance. Services like Sookasa and Cloudlock offer particular drive encryption to defend the privacy of students’ data (Schrameyer et al., 2016). The tools are cheap and compatible with most collaborating tools (Schrameyer et al., 2016). Therefore, educational institutions should consider using the tools mentioned above to avoid problems with the law. In conclusion, while the privacy question is rather complicated, the ways of dealing with the issues examined in the present paper can be useful for all the concerned parties.
Alexander, N. A. (2013). Policy analysis for educational leaders: A step-by-step approach. Web.
Dennen, V. P. (2015). Technology transience and learner data: Shifting notions of privacy in online learning. The Quarterly Review of Distance Education 16(2), 45–59.
Finnigan, K. S., & Daly, A. J. (Eds.). (2014). Using research evidence in education: From the schoolhouse door to Capitol Hill (Vol. 2). Cham, Switzerland: Springer Science & Business Media.
Means, B., & Anderson, K. (2013). Expanding Evidence Approaches for Learning in a Digital World. Web.
Schrameyer, A., Graves, T., Hua, D., & Brandt, N. (2016). Online student collaboration and FERPA considerations. Techtrends, 60(6), 540-548. Web.
Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510-1529. Web.