Searching the internet for recipes, academic papers or ex boyfriends is easy. But if you’re a teacher looking for a lesson plan, a textbook excerpt, or a fun brain teaser to share with your class, good luck.
For example, I just googled “multiplying exponents”. A bunch of results pop up. If you’re a parent, it would take a few minutes to digest the first five of them and then explain how to multiply 10² x 10³ to your kid. But, if you’re a teacher, you’d have to dig for quite some time before you found an age-appropriate textbook explanation, worksheet exercises, or a lesson plan you could present in a classroom.
A lot of people are working to try to change that and give teachers the power to comb through instructional material in seconds. (To understand the kind of searches that educators are dreaming of, check out recipe searches on Google. You can search by ingredient, cooking time and calories).
The main obstacle in searching for educational material is that it first needs to be tagged with keywords by humans. Metadata is the information that describes things so that anyone can search and find them. In art, it might be the artist’s name, whether it’s a painting or a sculpture, the art movement he comes out of, etc. In education, it could be whether it’s a video or a worksheet, the subject matter and when it was created.
I talked with Michael Jay, president of Educational Systemics. He’s a former science teacher who’s been working on creating so-called metadata for instructional content. He was also a presenter at the National Center for Education Statistics (NCES) STATS-DC 2013 July data conference, where there were several sessions devoted to metadata.
The first question I had was, why do we need to spend thousands, maybe millions, to hire and pay humans to tag instructional content on the Internet? The geniuses at Google have figured out how to write algorithms to search everything else. Why is education different?, I wondered.
Jay explained the problem with education is that the indexing tools cannot figure out instructional intent. Say, for example, Jay creates an exercise where he has kids take off all their shoes. Then the kids group the shoes in various categories as a way of learning how scientists classify things.
“Unless I write out that intent of ‘categorization’ specifically, that higher level goal that you’re trying to achieve, Google can’t infer that. It has to be written explicitly,” said Jay. “We’re often not explicit about instructional intent in the activities we engage kids in.” That’s where you need humans to describe the instructional materials through metadata.
Naturally, there are a variety of competing efforts to come up with a universal metadata standard. There’s a multi-state tagging initiative. And some organizations, such as Khan Academy, are tagging their videos and online worksheets their own way.
But one of the leading metadata initiatives is something called, the Learning Resource Metadata Initiative or LRMI. It’s funded by the Gates Foundation, which is also among the funders of The Hechinger Report, where I work and which produces this blog.
LRMI has been at this for more than two years and it’s taken this group of experts, which Jay is a part of, a long time to even come to an agreement on what the categories of metadata should be. Some people wanted instructional material tagged by grade level, from preschool to college. Others wanted a child’s age specified. Some people wanted to include ratings to help teachers and parents judge the quality of content, like the star ratings on Yelp. But that “paradata” has been pushed to the back burner for another time. In the end, the LRMI working group settled on this list:
1) Target audience (students, teachers, parents)
2) Aligns with which educational standards (Common Core, Next Generation Science Standards, other international standards)
3) Purpose (assignment, group work, field trip, reading)
4) Time required (30 minutes, 1 hour)
5) Age range of end user (5-7, 7-9)
6) Intellectual property rights (open resource, specific publisher)
Even with the categories in place, there are plenty of controversies on how to tag properly. For example, an educational video game might have multiple purposes. Educators even argue about simple things. What is a book in our digital-reader age?
Mediating these controversies is difficult. Some suggest crowd sourcing can resolve disputes. But Jay argues there should be a governance structure. “If you ask 10 educators about something, you get 15 answers. Crowd sourcing doesn’t work with education,” he said.
A big breakthrough for the metadata folks happened two months ago, when Schema.org adopted the metadata categories established by the Learning Resource Metadata Initiative (LRMI). That’s an important step because all the major search engines, from Google to Yahoo to Bing, use schema.org.
So, far only one organization has created an intelligent search engine using the new education metadata. That’s ISLE, the Illinois Shared Learning Environment, and it was rolled out only three weeks ago in July 2013. It has 170,000 educational resources tagged in its search engine. InBloom is working on a search engine using the same LRMI metadata.
The big goal is for a major search engine, such as Google, to use the LRMI metadata and launch a search engine for educational content. When that will be is anyone’s guess. Back in the fall of 2011 Google was excitedly talking about rolling out an education search engine, but it seems to have pulled back since then.
Jay says it’s a classic chicken and egg problem. “They (a major search engine) want to do it as soon as there’s a critical mass (of tagged educational content), but how do you get a critical mass until they do it.”