data driven

Data Driven ACT Prep Programs

March 22, 2018


Schools that can leverage data to inform their ACT prep programs can significantly outperform their peer-schools. They can also start to implement a continuous improvement program. A recent Urban High School study found the following challenges in aggregating the data: the quality and accuracy of data, availability of data in a timely fashion, the alignment of data to teaching materials and standards, the capacity for data disaggregation and the leadership structure to support school-wide use of data.

Given these challenges, how can school leaders and teachers develop a systematic approach to use data and to improve educational outcomes? Schools that currently use a formative assessment for college and career readiness like ACT have a better shot at designing programs to measure and improve outcomes. The process at these schools usually begins with identifying at way to analyze student performance on formative assessment to answer the following questions:

What are the areas of growth for a given sub-population?
  • The top three growth areas in ACT English for Juniors are: Advanced Sentence Structure, Passage Organization, and Punctuation
  • Knowing the ACT standards to which they align would help
  • Aligning these growth areas to readily available content and/or videos could help decide the time required to help students
  • What RTI or MTSS programs need to be setup to address growth opportunities?
  • Programs should include sufficient instruction time to familiarize students to the concepts identified as growth opportunities
  • Practice materials that allows students to work on the deficit areas
  • Ability to track student proficiency in these growth areas
  • What should be the duration of the intervention programs?
  • Ideally, you would want to structure your program to span a few weeks
  • The duration of the program would also depend on any tools that you plan to deploy to monitor and track progress
  • You should also consider the need for student buy-in which may require a post-assessment. The post-assessment provides students the opportunity to see progress and buy-in into the intervention program
  • What program can be designed to help students not considered at-risk?
  • Students who typically score above benchmark are self-motivated
  • Allowing students to use homeroom or personal learning time to work on their growth areas would an effective way to engage these students
  • What best practices can be leveraged from other schools using similar programs?
  • Identifying schools with similar demographics in student body and use of formative assessment tools can help
  • Writing up a set of response to these questions will help administrators and teachers think through the needs.

    Reference Material:

    Using Data to Guide Instruction and Improve Student Learning. http://www.sedl.org/pubs/sedl-letter/v22n02/using-data.html

    Craig A. Mertler: Introduction to Data-Driven Educational Decision-Making. http://www.ascd.org/publications/books/sf114082/chapters/Introduction_to_Data-Driven_Educational_Decision_Making.aspx

    LiteracyHow: Data-Driven Differenciated (D3) Instruction. http://www.literacyhow.com/assessment-progress-monitoring/