This article is from the In-Depth Report Learning in the Digital Age

How Big Data Is Taking Teachers Out of the Lecturing Business

Schools and universities are embracing technology that tailors content to students' abilities and takes teachers out of the lecturing business. But is it an improvement?

Conti's letter is only one example of the backlash building against tech-oriented, testing-focused education reform. In January teachers at Garfield High School in Seattle voted to boycott the Measures of Academic Progress (MAP) test, administered in school districts across the country to assess student performance. After tangling with their district's superintendent and school board, the teachers continued the boycott, which soon spread to other Seattle schools. Educators in Chicago and elsewhere held protests to show solidarity. In mid-May it was announced that Seattle high schools would be allowed to opt out of MAP, as long as they replaced it with some other evaluation.

It would be easy for proponents of data-driven learning to counter these protests if they could definitely prove that their methods work better than the status quo. But they cannot do that, at least not yet. Empirical evidence about effectiveness is, as Darrell M. West, an adaptive-learning proponent and founder of the Brookings Institution's Center for Technology Innovation, has written, “preliminary and impressionistic.” Any accurate evaluation of adaptive-learning technology would have to isolate and account for all variables: increases or decreases in a class's size; whether the classroom was “flipped” (meaning homework was done in class and lectures were delivered via video on the students' own time); whether the material was delivered via video, text or game; and so on. Arizona State says 78 percent of students taking the Knewton-ized developmental math course passed, up from 56 percent before. Yet it is always possible that more students are passing not because of technology but because of a change in policy: the university now lets students retake developmental math or stretch it over two semesters without paying tuition twice.

Even if proponents of adaptive technology prove that it works wonderfully, they will still have to contend with privacy concerns. It turns out that plenty of people find pervasive psychometric-data gathering unnerving. Witness the fury that greeted inBloom earlier this year. InBloom essentially offers off-site digital storage for student data—names, addresses, phone numbers, attendance, test scores, health records—formatted in a way that enables third-party education applications to use it. When inBloom was launched in February, the company announced partnerships with school districts in nine states, and parents were outraged. Fears of a “national database” of student information spread. Critics said that school districts, through inBloom, were giving their children's confidential data away to companies who sought to profit by proposing a solution to a problem that does not exist. Since then, all but three of those nine states have backed out.

This might all seem like overreaction, but to be fair, adaptive-education proponents already talk about a student's data-generated profile following them throughout their educational career and even beyond. Last fall the education-reform campaign Digital Learning Now released a paper arguing for the creation of “data backpacks” for pre-K–12 students—electronic transcripts that kids would carry with them from grade to grade so that they will show up on the first day of school with “data about their learning preferences, motivations, personal accomplishments, and an expanded record of their achievement over time.” Once it comes time to apply for college or look for a job, why not use the scores stored in their data backpacks as credentials? Something similar is already happening in Japan, where it is common for managers who have studied English with the adaptive-learning software iKnow to list their iKnow scores on their resumes.

This Is Not a Test

It is far from clear whether concerned parents and scorned instructors are enough to stop the march of big data on education. “The reality is that it's going to be done,” says Eva Baker, director of the Center for the Study of Evaluation at the University of California, Los Angeles. “It's not going to be a little part. It's going to be a big part. And it's going to be put in place partly because it's going to be less expensive than doing professional development.”

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This article was originally published with the title "Machine Learning."

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