A visual vocabulary-learning app that is looking to change the way students learn and comprehend language recently received a $250,000 joint investment from the University System of Maryland’s Momentum Fund, which supports early-stage companies.
InferCabulary, an app developed by speech and language pathologists Beth Lawrence and Deena Seifert, displays one vocabulary word at a time, accompanied by a collection of pictures, and has students infer a definition for that word based on context clues in the images.
From Lawrence and Seifert’s experience, using visual representations of new words, as opposed to strictly oral or written tools, helps students better understand the context of those words.
“Our goal with reading comprehension is for kids to make a movie in their minds,” Lawrence said. “If you don’t have background knowledge, you don’t have visuals in your mind. If you don’t have visuals in your mind, you can’t anchor the story.”
Lawrence recalled working with an 8th grade girl who had been assigned to read George Orwell’s book “Animal Farm” for class but was having difficulty understanding the text.
The primary hurdle for the student was the number of unknown vocabulary words, Lawrence said. She added that people need to know at least 95 percent of the words in a text to comprehend it.
No matter how Lawrence explained the words to the student, she still struggled to comprehend their definitions.
After analyzing the girl’s report, which showed that her nonverbal skills were in the genius range while her verbal skills were significantly lower, Lawrence had an epiphany: “Why was I using language to teach language to a student whose primary challenge was language?”
Instead, Lawrence put together a set of pictures that represented the word “prominent.” Within seconds the student told Lawrence that the word meant “standing out.”
That lesson paved the way for the idea for InferCabulary.
The app displays a vocabulary word alongside a set of pictures, which students examine for a common thread that can help them form a definition of the word. Then, they can click on each of the images to see a sentence using synonyms of the word to further build their understanding of how the word could be used. Finally, they view the actual definition of the word to see if it matches the definition they created based on context clues.
Users can also listen to the image captions and vocabulary word definitions–which can help with understanding the tone of a sentence–with recorded audio.
The app has different pricing options for parents, specialists and schools, depending on how many students are using the subscription.
Seifert and Lawrence developed InferCabulary as part of Towson University’s business incubator, which supports new startups and small businesses through mentorship, networking and other services.
The two women owned private practices as speech-language pathologists, so they each had experience running a business. But launching an app was different territory and the incubator provided resources to help make their vision a reality, Seifert said.
“They have opened doors for us that we probably wouldn’t have been able to break through,” she said.
For example, advisers at the incubator gave them suggestions about how to scale the business for a larger audience, Seifert said.
“This is not just a special ed product,” she said. “This is a product that all students can use.”
Lawrence said 65 percent of students struggle with reading comprehension, making the app useful to a wide range of students.
InferCabulary recently received a $250,000 joint investment from USM’s Momentum Fund, which Seifert said will help them hire additional staff for the business’ sales and customer support teams. Currently, Seifert said she and Lawrence are answering most of customers’ questions.
The fund invests in companies that are based in Maryland and are affiliated with the USM, either by the founder or inventor being a USM employee, alum or student; the company being based on intellectual property from a USM institution; or the company being located in a USM research park, incubator or Regional Institution Strategic Enterprise (RISE) zone.
Before the Momentum Fund investment, InferCabulary won a business pitch competition in Boston at the beginning of this year at the LearnLaunch Across Boundaries educational technology, or “ed tech,” conference.
“It’s a real honor to have competed against the hundred companies that we competed against,” Lawrence said.
Since winning, Lawrence said InferCabulary has received a lot more interest on social media and has heard from more potential investors.
In developing the app, Lawrence and Seifert said the feedback from users has been instructive in fine-tuning their product.
Students told Lawrence and Seifert they would like to be able to eliminate wrong choices by crossing them out, while teachers wanted a way to give a grade on quizzes–both suggestions that the developers are working to incorporate.
Teachers are able to assign words from books their students are reading in class. Currently, there are 4,000 K-12 words tagged to more than 500 books. If a book is not featured in the app, educators can request that words from that text be added, Lawrence said.
Seifert and Lawrence are currently working on an InferCabulary 2.0, which will add a game to the app this spring.
Lawrence said students enjoy using the app because it makes learning vocabulary entertaining.
“It’s fun, it’s gamified and that really motivates them to become self-directed learners,” she said.
Although vocabulary instruction in English classes is InferCabulary’s primary focus, Lawrence said the skills the app teaches can also improve reading comprehension in other subject areas like science, social studies and math.
“This is a tool that supplements the current curriculum by implementing explicit vocabulary instruction,” she said.
- Video of the Week: How to Pick Crabs - July 1, 2022
- Baltimore street sweeping to resume July 13 - June 30, 2022
- Baltimore Weekend Events: Fourth of July Fireworks, Cherry Hill Festival, BSO Performances, and more - June 30, 2022