How Big Data and Education Technology Are Changing K-12 Education

Gone are the days when someone was overwhelmed with joy simply because Amazon or Pandora correctly discerned his or her tastes. It is no longer a secret that businesses are collecting consumers’ digital footprints and translating them into personalized services through cloud computing and machine learning in this era of big data. The transformation of data into real-world impacts is not limited to shopping and entertainment; the same technologies are revolutionizing the way we learn. For example, Georgia State University uses predictive analytics to advise students in selecting their majors based on their previous grades. Moreover, with a few clicks, one can convert a laptop into a lecture hall at one of the world’s top universities, thanks to Massive Online Open Courses (MOOCs).

Supporters of this shift in education technologies, known as EdTech, include top-level public officials. Newt Gingrich, former U.S. Speaker of the House, wrote in an CNN op-ed, “pioneering projects like Khan Academy, Udacity and Coursera are pointing toward a future of learning that is more like Netflix than the chalk-and-textbook system we have today.”

Undoubtedly, it is crucial to examine whether the adoption of EdTech will necessarily lead to enhanced educational outcomes. A study published in the Journal of Education Policy by Heather Roberts-Mahoney in early 2016 pointed out several drawbacks of utilizing personalized learning technologies in K-12 education in the United States. These drawbacks stem from the commercialization of public education, insufficient proof of the efficacy of EdTech, and a lack of clear ethical commitments.

The researchers carried out a qualitative analysis based on government reports, advocacy papers, and research monographs published between July 2013 and February 2014 that were of key importance in advocacy for and legitimization of personalized learning. Similarities were identified in how these reports and papers understood: (1) the purpose of education, (2) the role of data in education, (3) the role of a teacher, and (4) the assessment of learning outcomes.

First, the reports and papers present the purpose of education in terms of ‘producing’ workers with the human capital and ‘twenty-first century’ skills needed to effectively compete in a ‘global market’ for labor. Second,  they describe the role of data in education as both accounting for test scores and other traditional cognitive measures of student performance and incorporating the collection of non-cognitive and behavioral data, through techniques such as wearable cameras and biosensors. In this way, the purpose and usefulness of data collection has grown to include accountability, performance prediction, and personalized goal setting. Third, the role of a teacher is deemphasized in the documents and the professional knowledge and experience of teachers are essentially considered less credible than computer algorithms. The documents view the future of the teacher position as a resource guide who is also involved in data collection and technology management. Fourth, the same documents present the assessment of learning outcomes as a matter of assessing the efficiency and effectiveness of learning approaches with little value ascribed to human interaction. The underlying idea is that everything that can be learned by students can also be tested by technology and stored in a database.

Based on the observations above, the authors argued that the expanded role of EdTech providers poses a threat to K-12 education. The companies who generate and control the learning data will have a strong for-profit incentive and could use students as ‘products’ to be tracked and consumed by corporations in the education sector. This is because customizing learning according to learner profiles is analogous to customizing products based on customer profiles.

While it seems certain that the autonomy of teachers will be increasingly affected by technology in the future, there is no concrete proof that human interaction and teachers’ experience can be completely replaced by digital learning and artificial intelligence, respectively. This finding may assuage the worry expressed by some opponents of EdTech that it could cause teachers to lose their jobs. Moreover, there is not yet any credible linkage between the mechanistic approach to acquiring skills enabled by EdTech and students’ future success in the twenty-first century workplace.

Finally, the discussion fits into a broader debate about what is known as “corporate school reform,” which refers to a set of neoliberal policy initiatives that view market competition and business-style management as the key to improving the United States’ education system. The potential downsides of personalized learning technologies presented by this study highlight the risks involved in attempting to align private interests with public education. Despite the apparent merits of technological advancements in the arena of education, the authors believe that promoting technologies without clear ethical commitments from those who would control the data, such as a commitment to fostering the necessary conditions for human development, are likely to do far more harm than good.

Article source: Roberts-Mahoney, Heather, Alexander J. Means, and Mark J. Garrison. “Netflixing human capital development: personalized learning technology and the corporatization of K-12 education.” Journal of Education Policy 31 (4) (2016): 405-420.

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yulp@uchicago.edu'
Leping (Tommy) Yu

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