Grappling with new ways to solve problems is a regular challenge in the K–12 space, yet good ideas don’t fall from the trees. Technology is now being used to try to solve problems like differentiating learning in classrooms, but could it help us address some of K–12’s stickier system-wide challenges?
I was reading about these innovations in other sectors and wondered whether they might have a use in education:
Putting innovations in other fields to new uses
“Ninety percent of problems have already been solved in some other field,” says Tony McCaffrey, chief technology officer of Innovation Accelerator based in Natick, Massachusetts. In the patent industry, companies use language processing and machine learning technology to comb through large amounts of unstructured data, not just in patent databases and technical journals, but also in blogs, online news sites, and social networks to learn about promising new innovations from other fields that they might patent for another use. “We use our technology to create hundreds of high-quality inventions per month, which we then communicate to our customers,” says Julian Nolan, CEO of the Swiss invention-producing company, Iprova. “They can then choose to patent them.”
What if we used a similar approach to find out where promising educational solutions are arising across an international database of school systems that could be replicated in other cities? For example, education leaders could comb teacher compensation structures, recruitment and retention processes, and evaluation, assignment, and promotion protocols. They could sort by what they deem to be relevant similarities between their school system and the systems in the database. We already have baby steps toward this with respect to curriculum. The IES What Works project has a searchable database reporting on how well various in-classroom interventions have panned out, yet we have nothing like this for systems-level challenges.
Making use of “fairness” algorithms to allocate space
Equitable access to learning spaces remains a challenge in most urban education systems that have a mix of traditional and charter public schools. Sometimes the district resists providing available space to charter schools. Sometimes the space available is substandard. Sometimes it’s too expensive. Sometimes it’s unclear which charter operator should get it, or the less optimal charter gets it. Sometimes it’s dog-eat-dog for who gets what.
We’ve suggested in the past that learning space be administered by a third party that can be responsible for learning space administration throughout the city. But the question remains: how should the third party objectively and fairly allocate learning space?
Now there is software, developed by Spliddit, designed to help “…people fairly divide up goods, rent, bills in restaurants, and fares on transport, among other things.” This sort of “fairness technology” seems highly translatable to K–12 learning spaces issues. Spliddit uses algorithms of fairness to account for each participant’s preferences, then offer up agreeable solutions accordingly. If it works, the parties will be “envy free,” and they can be assured their needs were objectively taken into consideration.
To be sure, common enrollment systems are already using choice algorithms to allocate students’ school assignments in Boston, New Orleans, Newark, and Denver. The algorithms let families of students prioritize which traditional and/or charter schools they’d like to attend, then they optimize those preferences, taking various other factors into account as federal, state, or local policy requires. If school systems are not ready for third-party administration, school system leaders should be asking how these choice algorithms could be applied to existing learning space allocation disputes. Perhaps the rise of these new fairness technologies can fuel that investigation.
Collaborative problem solving
Transformation in K–12 systems is often criticized for being top-down, un/under-inclusive, or doing “to, not with” a historically underserved or disadvantaged population. The question, then, is how to empower communities and involve them as genuine stakeholders.
Technology might be able to help. In Finland, “Open Ministry,” an effort to crowd-source democracy, used online software to allow hundreds of people to draft, amend, and tweak their same-sex marriage bill. Open Ministry presently has over 100 working groups on various legislative proposals. Other related software platforms include Loomio, a collaborative decision-making tool, and Adhocracy, an online policy drafting and decision-making tool.
In K–12, we could enlist communities to help design new teacher recruitment policies, school designs, systemwide special education programs—essentially anything that is complex, in demand, and requires their buy-in. This public engagement effort could be a strong decision-making supplement to a local school board, a charter management organization, or a school leadership team. Notably, it would be harder for a special interest to co-opt or chill a solution.
K–12 education technology is a huge, growing industry with much to offer school system redesign. But why not look beyond the borders of the education realm to seek applicable solutions that have already been tried and tested?
