Literacy Express

Local governments can invest in this strategy using State and Local Fiscal Recovery Funds (SLFRF) from the American Rescue Plan Act (ARPA).
  • This strategy can help address educational disparities. The U.S. Department of Treasury has indicated that strategies that help achieve this outcome are eligible for the use of Fiscal Recovery Funds.
  • Investments in this strategy are SLFRF-eligible as long as they are made in qualified census tracts or are designed to assist populations or communities disproportionately impacted by COVID-19.

Program overview

  • Preschool curriculum for children aged three to five, primarily intended to improve language development and early literacy
  • Structured around 10 thematic units, covered in three to four weeks each
  • Can be used in half- or full-day preschools, can be used for typically developing children, children with special needs, and children from non-English speaking families
  • Provides professional development to teachers and staff
  • Includes teaching materials, suggested activities, daily schedules, and classroom management recommendations
Issue Areas
Early childhood
Target Population
Children under 5
Cost per Participant
$2,300 per classroom package

Evidence and impacts

Proven

Ranked as having the highest level of evidence by the U.S. Department of Education's What Works Clearinghouse

  • Positive effects on oral language, print knowledge, and phonological processing
  • No discernible effects on cognition and math skills
  • Oral language skills improved by an average of 12 percentile points
  • Print language skills improved by an average of 15 percentile points
  • Phonological processing improved by an average of 12 percentile points

Best practices in implementation

  • Note: This content is under review
  • As with all evidence-based curricula, Literacy Express must be delivered with fidelity in order to achieve positive outcomes.
  • Teachers must be provided with ample professional development opportunities to master curriculum and should be evaluated regularly to ensure that model is delivered with fidelity.