A recent meta-analysis of 17 studies that used LENA technology confirmed a significant relationship between LENA’s automated measures of the natural language environment and childhood outcomes.
Researchers found a correlation between three of LENA’s measures – adult word count, conversational turns, and child vocalizations — and children’s language and cognitive skills. Adult word count showed a small-to-medium effect size (r = 0.21) and conversational turns and child vocalizations showed a medium effect size (r = 0.31 and r = 0.32 respectively).
“This research is exciting confirmation that LENA technology is indeed measuring and quantifying the most foundational elements of early development,” said Steve Hannon, President and CEO of LENA.
The paper lends credence to LENA’s programs, which place this objective feedback on the language environment into the hands of teachers and parents to accelerate their children’s language development and learning trajectories.
The review found that the relationship between LENA’s automated measures and child language skills was robust and consistent regardless of a child’s age, of their developmental status (for example, if the child was born preterm or with hearing loss), whether the study was published or not, whether the study examined expressive or receptive language skills, and across different language testing methods.
“This excellent work confirms that LENA’s automated measures significantly predict child language outcomes."
-Dr. Jill Gilkerson
“The meta-analysis is thorough in its scope and rigor,” said Dr. Jill Gilkerson, LENA’s Chief Research and Evaluation Officer. The 17 studies analyzed included a total of 1,093 participants from five countries, who were speakers of three primary languages.
“This excellent work confirms that LENA’s automated measures significantly predict child language outcomes,” Gilkerson said. “I’m thrilled to see the scientific evidence for our work with parents, teachers, and researchers continue to accrue.”