Reader Laura Chapmam reminds us that the corporate-government combine wants Big Data. The demise of inBloom is only one stop in a long journey that invokes hundreds of millions of dollars and a foundational belief that what can be measure matters most:

Chapman writes:

The bare bones infrastructure for data-mongering was expanding in 1990, jump-started by a concerted effort to standardize vocabularies to characterize public education–think almanac–but expanded to fit the architecture of computer and information retrieval programs.
In tandem (as usual) Gates and USDE poured massive amounts of money into data-mongering starting in 2005, this intended to link student and teacher data in a continuum from birth to college and beyond.

Gates conjured the program called Teacher Student Data Link (TSDL), one facet of a data gathering campaign funded at $390,493,545 between 2005 and mid-May 2011 by the Gates’ Foundation.

This campaign envisions the link between teacher and student data serving eight purposes: 1. Determine which teachers help students become college-ready and successful, 2. Determine characteristics of effective educators, 3. Identify programs that prepare highly qualified and effective teachers, 4. Assess the value of non-traditional teacher preparation programs, 5. Evaluate professional development programs, 6. Determine variables that help or hinder student learning, 7. Plan effective assistance for teachers early in their career, and 8. Inform policy makers of best value practices, including compensation. See http://www.dataqualitycampaign.org/about

The TSDL system is intended to ensure that all courses are based on standards, and that all responsibilities for learning are assigned to one or more “teachers of record” in charge of a student or class. A teacher of record has a unique identifier (think barcode) for an entire career in teaching. A record is generated whenever a teacher of record has some specified proportion of responsibility for “a student’s learning activities” identified by the performance measures for a particular standard, subject, and grade level.

In addition to the eight purposes noted above, the TSDL system aims to have ”period-by-period tracking of teachers and students every day; including tests, quizzes, projects, homework, classroom participation, or other forms of day-to-day assessments and progress measures”—a level of accountability (I call it surveillance) that is said to be comparable to business practices (TSDL, 2011, “Key Components”).

This system will keep current and longitudinal data on teachers and individual students, schools, districts, states, and educators ranging from principals to higher education faculty. The aim is to determine the “best value” investments in education and monitor outcomes, taking into account as many demographic factors as possible, including health records for preschoolers. In Bloom may be dead but there are data-warehouses supported in part by Gates committed to that vision of data mining ( e.g. Battelle for Kids in Ohio).

On the federal side we have The Statewide Longitudinal Data Systems (SLDS) Grant Program, authorized under Title II, Educational Technical Assistance of the ‘‘Education Sciences Reform Act of 2002 H. R. 3801.” The first grants were made in 2005, the same year that the Gates’ Foundation started the parallel Data Quality Campaign.

See http://nces.ed.gov/programs/slds/
Achieve promoted, and still promotes, the Data Quality Campaign with a special focus on getting state policy makers to track individual students’ progress from pre-K to graduation and to use that data “to improve outcomes.” The program is being extended to teacher education with college programs measured by the test scores their graduates produce when they enter classrooms. See http://aacte.org/index.php?/Media-Center/AACTE-in-the-News/administration-pushes-teacher-prep-accountability.html.

In Bloom may be dead but all this other work is still in motion.

I think it wise to listen to some experts on Big Data. “We are more susceptible than we may think to the ‘dictatorship of data’—that is, letting the data govern us in ways that may do as much harm as good. The threat is that we will let our-selves be mindlessly bound by the output of our analyses even when we have reasonable grounds for suspecting something is amiss.

Or that we will attribute a degree of truth to data which it does not deserve.” Viktor Mayer-Schönberger & Kenneth Cukier. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Boston: Houghton Mifflin. p. 166.