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PDG + LENA

Write LENA Grow
into your PDG application.


➡️ LENA Grow: Evidence-based professional development for early childhood educators.

➡️ 60,000+ children and 16,000+ educators served since 2016.

➡️ Strong evidence of positive impacts on classroom quality, kindergarten readiness, & language, literacy, and social-emotional development.

➡️ Successfully included in PDG funding in Ohio and Arkansas. Read a case study about Ohio's LENA Grow implementation.

➡️ Added to the research clearinghouses in North Carolina, Oklahoma, and Tennessee.

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Make every interaction count in early childhood education.
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Plug-and-Play Language

for PDG Applications

LENA Grow Crosswalk with PDG

 

About LENA Grow

LENA Grow is unique among the professional development opportunities available for early childhood educators. The program delivers a single, straightforward, evidence-based solution to improving classroom quality. That solution: A laser focus on conversational turns.

We don't just think conversational turns matter. We know they do.

More than 250 peer-reviewed research studies have relied on LENA technology. Among other things, these studies have linked conversational turns to:

  • Brain structure.1,2
  • Brain function.3
  • Language development and IQ scores.4
  • Social-emotional development.5
  • Vocabulary skills.6
  • Executive function.7
  • Early literacy skills.8,9

Conversational turns matter, and LENA Grow increases them. The collateral benefits for children and teachers alike are profound.  



References

  1. Romeo, R., et al. (2018). Language Exposure Relates to Structural Neural Connectivity in Childhood. Journal of Neuroscience 38(36): 7870-7877. https://doi.org/10.1523/JNEUROSCI.0484-18.2018
  2. Huber, E., et al. (2023). Language Experience During Infancy Predicts White Matter Myelination at Age 2 Years. Journal of Neuroscience 43(9): 1590-1599. https://doi.org/10.1523/JNEUROSCI.1043-22.2023
  3. Romeo, R., et al. (2018). Beyond the 30-Million-Word Gap: Children’s Conversational Exposure Is Associated with Language-Related Brain Function. Psychological Science 29(5). https://doi.org/10.1177/0956797617742725
  4. Gilkerson, J. et al. (2018). Language experience in the second year of life and language outcomes in late childhood. Pediatrics 142(4). https://doi.org/10.1542/peds.2017-4276
  5. Gómez, E., & Strasser, K. (2021). Language and socioemotional development in early childhood: The role of conversational turns. Developmental Science, 24(5). https://doi.org/10.1111/desc.13109
  6. Duncan, R., et al. (2022). Predictors of preschool language environments and their relations to children’s vocabulary. Infant and Child Development 32(1). https://doi.org/10.1002/icd.2381
  7. Romeo, R., et al. (2021). Neuroplasticity associated with changes in conversational turn-taking following a family-based intervention. Developmental Cognitive Neuroscience 49. https://doi.org/10.1016/j.dcn.2021.100967
  8. Merz, E. C., et al. (2020). Socioeconomic disparities in language input are associated with children's language-related brain structure and reading skills. Child Development 97(3). https://doi.org/10.1111 /cdev.13239
  9. Weiss, Y., et al. (2022). Language input in late infancy scaffolds emergent literacy skills and predicts reading related white matter development. Frontiers in Human Neuroscience 16. https://doi.org/10.3389/fnhum.2022.922552

Video: How LENA Grow Works

About LENA Technology

LENA's "talk pedometer" technology — some people call it a "FitBit for conversation" — is trusted by 400+ research institutions around the world and has powered 200+ peer-reviewed studies. LENA Grow puts that same technology directly into the hands of early childhood educators. 

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After a full day of talk is captured by the LENA device, the audio files are transferred to a cloud processing system that uses complex algorithms to analyze the audio file. The algorithms are trained to identify and differentiate adult speech, child speech, and tv/electronic noise. The algorithms can also differentiate the speech of the key child from the speech of other children and from non-speech sounds like cries.

The software then generates objective, actionable feedback reports for caregivers on the quantity and quality of talk in their child’s environment.

 

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