Here’s what Manuela Ekowo, policy analyst with the Education Policy program at New America, had to say.
2017 is shaping up to be a big year of what-if’s. The President just called and is asking for advice on shaping the U.S. education technology agenda. What do you say?
Criticisms about education technologies have existed perhaps just as long as the technologies themselves have been around. The technology has changed over the years. (Distance education took place via radio and televisions in the early 20th century and online learning and MOOCs via the Internet in the early 21st century.) However, the questions have largely stayed the same:
- Do technologies ensure quality learning and positive student outcomes?
- Do they help or hurt underrepresented students?
- Do they opens the door for companies to take the lead on how students learn and how their data is used?
The triplet challenge for education technology is this: to ensure effective tools, equitable outcomes, and equilibrium between the producers and users of education technologies.
The Trump Administration recently stated it hopes to “. . . make post-secondary options more affordable and accessible through technology enriched delivery models.” Promoting the use of education technology should not go without also working to abate the age-old concerns about efficacy and equity. Given the increased use of predictive analytics, the Administration could consider how effective tools, equity, and equilibrium are being advanced and what people, processes, policies, and tools stand in the way of progress.
Predictive analytics have long been used to help meet an institution’s business goals, like strategic enrollment management, but only recently have they been used to improve learning outcomes for students. Like most education technologies, institutions using predictive tools will have to find the happy medium between embracing innovation and letting evidence lead the way. Colleges should rely on already available evidence to guide their practices as they and researchers work to build more evidence on whether predictive tools are effective. The Administration should look to this evidence as it promotes the use of technologies in higher education.
The Administration and colleges should also consider how innovation impacts various groups, particularly traditionally underrepresented or underserved students. Important questions to ask are:
- Which technologies may help these students enjoy better outcomes more frequently?
- What evidence do we have to support it?
- How can we build evidence to support the use of particular tools, policies, and practices because of their demonstrable success for underrepresented and underserved students?
The Trump Administration should also facilitate more mutually beneficial relationships between those who create predictive tools (typically education technology vendors) and those who use them (institutions, faculty, staff, and students). For example, California recently released a report with recommendations for the edtech industry to protect student data privacy. It stresses the need for vendors not to use student data to market to them, not to sell student data to other companies, and not to make privacy policies vague or hard for students and families to access.
There is a natural tension between for-profit companies and nonprofit or mission-driven colleges and universities. When the pendulum swings towards profit-driven decisions, mission-driven ones may be muted. The Trump Administration should ensure we are as excited about education technologies that are effective, produce equitable outcomes for all students, and equalize unequal influencers as we are about the tools themselves.
