Our Research Base

Reading Rocket incorporates the Science of Reading and AI technology to help 5-7 year olds learn to read.

Rooted in the Science of Reading

Reading Rocket tools are aligned with the Science of Reading, a scientifically-based body of interdisciplinary research that describes how proficient readers and writers develop. Each of the Five Pillars of Reading are covered by our tool, including phonemic awareness, phonics, vocabulary, fluency, and comprehension.

According to Scarborough’s Reading Rope, skilled reading develops as word recognition becomes increasingly automatic and language comprehension becomes increasingly strategic. Reading Rocket Assess provides strategic diagnostic data related to word recognition skills, allowing teachers to make informed instructional decisions that target the individual needs of their students. Language comprehension is developed as students read AI generated texts that align to both priority skills and student interests.

Drives Individualized Instruction

Our diagnostic reporting tools provide teachers with a comprehensive overview of the reading skills your students have and have not mastered. This list of priority skills allow teachers to plan targeted instruction that focuses on the skills that young readers need to be successful.

  • Reading Rocket Assess generates data related to reading level like fluency and accuracy along with a diagnostic summary of phonic skills. This data allows teachers to design their instruction to explicitly cover the highest priority skills for each student.

  • Suggestions are generated following each assessment cycle, providing teachers with a roadmap on how to design instruction and reading activities for both individual students and small groups.

Inspires a Love of Reading

Reading Rocket takes an inventory of students’ interests, allowing for each student to have their own individualized decodable texts that meets their unique needs. Reading Rockets focuses both on the interest and reading level of each student to foster a love of reading.

Limits Assessment Bias

The Reading Rocket evaluation process minimizes the influence of implicit bias, while also valuing the expertise and insight teachers bring to reading assessment. Following the AI assessment protocol, teachers are given an individualized report for each student which will inform instructional next steps.

  • Reading Rocket Assess uses AI to generate the initial evaluation of each child’s progress monitoring session, followed by teacher review and correction, as needed. This protocol allows for less biased baseline data collection.

  • Reading Rocket recognizes and values the expertise and insight teachers bring to the reading assessment process, which is why protocols are in place to allow teachers to monitor and revise the AI-generated evaluation of student proficiency.

Increases Efficiency

The Reading Rocket platform allows for multiple students to be progress monitored at the same time, resulting in teachers taking less time to assess, The power of AI generates the first round of data collection and analysis, requiring the teacher to spend less time on calculation and error analysis.

  • Progress monitoring sessions can be done in small groups, allowing for more instructional time.

  • Data collection and analysis is conducted using the power of AI, eliminating the requirement for teachers to document during progress monitoring.

References

  1. Adams, M. J. (2009). Decodable text: Why, when, and how? In E. H. Hiebert & M. Sailors (Eds.), Finding the right texts: What works for beginning and struggling readers (pp. 23–46). New York: The Guilford Press.

  2. Ainley, M. D., Hidi, S., & Berndorff, D. (2002). Interest, learning and the psychological processes that mediate their relationship. Journal of Educational Psychology, 94, 1–17.

  3. Costello, P. (September 14, 2021). Evidence of Teacher Bias. AmeriCorps Montgomery. https://www.projectchangemaryland.org/evidence-of-teacher-bias/

  4. Farrall, M. L. (2012). Reading assessment: Linking language, literacy, and cognition. John Wiley & Sons, Inc.. https://doi.org/10.1002/9781118092668

  5. Gough, P.B. & Tunmer, W.E. (1986). Decoding, reading, and reading disability. Remedial and Special Education, 7(1), 6 - 10. https://doi.org/10.1177/074193258600700104

  6. Kim, Y.-S. G., & Davidson, M. (2019). Assessment to inform instruction: Formative assessment. Global Reading Network Critical Topics Series. Washington, D.C.: USAID. Prepared by University Research Co., LLC (URC) under the Reading within Reach (REACH) initiative for USAID’s Building Evidence and Supporting Innovation to Improve Primary Grade Assistance for the Office of Education (E3/ED). Available at www.globalreadingnetwork.net.

  7. Klein, A. (2023, March 15). Measuring Reading Comprehension Is Hard. Can AI and Adaptive Tools Help?

  8. Krapp, A., Hidi, S. & Renninger, K. A. (1992). Interest, learning, and development. In K. A. Renninger, S. Hidi, & A. Krapp (Eds.), The role of interest in learning and development (pp. 3–25). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.

  9. Lynch, M. (2023, March 17). Measuring Reading Comprehension with Ai. The Edvocate. https://www.theedadvocate.org/measuring-reading-comprehension-with-ai/#:~:text =By%20analyzing%20linguistic%20structure%2C%20context,plans%20to%20sup port%20individual%20learners.

  10. Malcolm, U. (2022, March 22). Evidence-Based Assessment in the Science of Reading. LDAOeng. https://www.ldatschool.ca/evidence-based-assessment-reading/

  11. National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific research literature and its implications for reading instruction. National Institute of Child Health and Human Development.

  12. Nickerson, R.S. (1998). Confirmation Bias: A Ubiquitous Phenomenon in Many Guises. Review of General Psychology 2(2), 175-220.

  13. Ordetx, K. (2021, January 14). What is the Science of Reading? The IMSE Journal.https://journal.imse.com/what-is-the-science-of-reading/

  14. Renaissance (2023). Putting the Science of Reading into Practice
    Saha, N. (2022, December 14). The Science Behind Decodable Books. Meta Metrics.

  15. Springer, S. (2017, March 23). From Surviving to Thriving: Four Research-Based Principles to Build Students’ Reading Interest. https://doi.org/10.1002/trtr.1581

  16. Steinke, P. & Fitch, P. Minimizing Bias When Assessing Student Work. (2017). Research and Practice in Assessment 12, 87-95. https://files.eric.ed.gov/fulltext/ED506195.pdf