When tasked with choosing books, teachers face a daunting task. Along with the content of the book itself, there is the reading level of the book and the themes to consider. Or what if teachers want to demonstrate structure? It’s not like they have time to read the books themselves, and all that’s available is usually a summary.
The team behind ETC Highlandtown-based edtech startup Unbound Concepts sees each of those details about books as data points that teachers use to make decisions.
The company’s latest free app, Artifact, uses machine learning to help teachers make the choices. The books are in a searchable database with identifiable information. Teachers also help improve the offerings by tagging specific info as they search and use the books.
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“We’re trying to balance technology and the expertise of the teachers in building out the platform,” said CEO and cofounder Katie Palenscar.
The database is about to get an influx of more than 2,000 books, and they’ve already been used by educators who don’t necessarily have a reading list to follow.
Unbound is partnering with First Book, a nonprofit which offers low-cost books to schools and community groups in need. First Book already has information about scores of books in its online marketplace. Artifact will provide a way to search and discover that information.
“First Book has been putting books in the hands of students and kids all over the world. They know that teachers need these books as well,” Palenscar said.
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