If you buy a book through Amazon, rent a movie through Netflix, or have a Facebook account, your information and choices are "mined" to market new products catered to what the data reveals about you. In these large databases, your choices are compared with others and a book you liked might be offered to others who seem to have similar tastes or interests. Specialized algorithms are developed that "mine" in an effective process to sell products.
Wikipedia defines algorithms in part this way:
"Algorithms are essential to the way computers process information. Many computer programs contain algorithms that specify the specific instructions a computer should perform (in a specific order) to carry out a specified task, such as calculating employees' paychecks or printing students' report cards."
NY Times contributor Seth Freeman wrote a clever article this week titled "Me and My Algorithm" of which he said:
“If this is a case of my algorithm, my cyber personal shopper, coach, guardian angel and avatar, knowing me better than I know myself, I really do need to figure out why I, a guy, get repeated offers — tied to a e-mails on vastly different subjects — for mastectomy bras and for something called a vaginal ring. Is the idea that these items make lovely gifts? Since articles I have written have circulated through the Internet by e-mail, it could easily turn out that my algorithm will soon get the opportunity to read what I have had to say about it here. What, I wonder, will it think?” (1)
Last year, Bill Gates and other Microsoft executives obtained a patent for a personal data mining system that "would analyze information and make recommendations with the goal of aiding a person's decisions and improving quality of life. The patent abstract described the system this way: "Personal data mining mechanisms and methods are employed to identify relevant information that otherwise would likely remain undiscovered." Users supply personal data that can be analyzed in conjunction with data associated with a plurality of other users to provide useful information that can improve business operations and/or quality of life. Personal data can be mined alone or in conjunction with third party data to identify correlations amongst the data and associated users. Applications or services can interact with such data and present it to users in a myriad of manners, for instance as notifications of opportunities. Of course, it's not all about improving lives: Further down, the patent explains that "such data can be afforded to businesses involved in market analysis, or the like, in a manner that balances privacy issues of users with demand for high quality information from businesses." (2)
Building Longitudinal Data Systems for Education
What does this have to do with education? Plenty. There is a widespread belief that the development of longitudinal data, from early childhood through the 12th grade and beyond is a necessary element to educational reform. The Data Quality Campaign (DQC), "a national, collaborative effort to encourage and support state policymakers to improve the availability and use of high-quality education data to improve student achievement." The organization articulates a widespread belief that "States have made remarkable progress in developing longitudinal data systems that can follow student progress over time, from early childhood through 12th grade and into postsecondary education through implementation of the 10 Essential Elements. The 10 State Actions are the fundamental steps states must put in place to change the culture around how data are used to inform decisions to improve system and student performance."
Florida received a federal grant for $9,975,288 with funding starting in July 2010 and ending in June 2013 and cited these major outcomes in their proposal
a) Upgrade the four major source data systems that are incorporated into Florida’s Education Data Warehouse (EDW)The Data Quality Campaign reaffirmed that "Florida is among the top states in collecting data (10 of 10 criteria along with 11 other states) and using it (5 of 10 criteria, better than all but two states). "When states collect the most relevant data and are able to match individual student records over time, they can answer the questions that are at the core of educational effectiveness." (4) According to their website, the founding father of the Data Quality Campaign is the Bill & Melinda Gates Foundation, with additional support from Casey Family Programs, Lumina Foundation for Education, Michael & Susan Dell Foundation, and the Pew Charitable Trusts. You can follow DQC on Facebook.
b) Employ a unique identifier system so that social security numbers are no longer the key field for tracking students between the Local Education Agencies and the State
c) Provide several different reporting capabilities for use by a myriad of stakeholders
d) Implement a data mining tool for FLDOE to analyze and evaluate its program and policies more efficiently and effectively (3)
DQC’s executive director believes that there is education data collected that is not necessary and cited Kansas and Tennessee as “leaders in establishing rules for data control.” However, the Fordham Law School Center on Law and Information Policy conducted a study (5) on the massive data collection efforts and concluded that states "are collecting far more information than necessary, failing to take appropriate measures to safeguard student privacy and protect them from data misuse, and failing to comply with the Family Educational Rights and Privacy Act (FERPA). Fordham's investigation also reveals that 80% of the states "do not have a system to delete student records. "Fordham law professor Joel R. Reidenberg, who oversaw this study, had this to say of the Center’s findings:
“Ten, 15 years later, these kids are adults, and information from their elementary, middle and high school years will easily be exposed by hackers and others who put it to misuse. States, he said, "are trampling the privacy interests of those students." (6)
Bill Gates and the entire computer industry need a literate population with financial means to buy and make use of their products. Therefore, at some level, these efforts are intended to spur improvements. I do not mean to suggest any nefarious intent. Clearly, there is business development intent. Then, I wondered what other benefits a massive data collection has. Could it be a way for an industry, like the computer industry, to be able to identify minds early on with potential to join that workforce, nurture them, and ensure that the U.S. has sufficient minds here versus importing from abroad. Right now, the jobs in this sector are blooming in China and India and likely a destination for unemployed U.S. computer guru's, leaving the potential for a U.S. brain drain. Whatever the reasons, I find it troubling. What do you think?
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