All students enter school with a combination of "headwinds" and "tailwinds". Tailwinds are the things that make school easier for students. Tailwinds may include factors such as coming from a home with parents of high education levels and economic stability, being a native English speaker, not having a disability, or being a member of the cultural majority. Each of those characteristics plays a role in helping a student experience success in school.

Headwinds on the other hand make school more difficult. Headwinds can include having economic instability at home, parents with lower levels of education, having a disability, or still learning English. The more headwinds a student has, the more difficulty they will have in maximizing their academic potential and the more “tailwinds” they will need. Tailwinds come in the form of high-quality instruction, support, and intervention.

The Academic Support Index, or ASI, quantifies these headwinds. A student’s ASI is the sum of their headwinds. Their ASI can also be considered a measure of the amount of support that they will need in order to mitigate the impact of those educational headwinds. Students with a low ASI will likely need very little additional support outside of Tier 1 instruction. Higher ASI students will likely need proportionally higher amounts of Tier 2 and sometimes Tier 3 supports.

There is a strong relationship between the ASI and academic outcomes including assessments such as the SAT, Smarter Balanced Assessments, AP and IB tests, kindergarten screeners, grade point averages, rates of college eligibility, matriculation, and degree attainment. We have studied these effects over seven years of data as well as across urban, suburban, and rural schools. To date over 400,000 students have been scored on the ASI. (See the featured post below for a list of papers and presentations on the ASI).

Because the ASI is able to reliably predict student outcomes you have to opportunity to interrupt that predictability by using the ASI to make sure that you are identifying the right students for early intervention and support. With effective intervention, predictive analytics can become preventive analytics.

Saturday, September 15, 2018

Publications, papers, and presentations

Stevens, D., The Academic Support Index: A Tool for Contextualizing Student Data, Cambridge Handbook of Applied School Psychology
Dixon, D. Stevens, D., A Potential Avenue for Academic Success: Hope Predicts an Achievement-Oriented Psychosocial Profile in African American Adolescents,  Journal of Black Psychology 

America Educational Research Association Annual Meetings
Stevens, D., 2020, Evidence for the Validity and Reliability of Performance Clusters Within the Academic Support Index, Division D Paper
Stevens, D., 2019, Maximizing Assessment Performance of At-Risk Students Using the Academic Support Index to Engineer a Low Stress Testing Environment, Division H 
Stevens, D., 2018, Building Your Own Academic Support Index for Research, Evaluation, and Intervention Design, Division H Demonstration Session
Stevens, D., 2018, Revisiting the Academic Support Index: A Validation Study Using Data from Three School Districts, Division H Paper
Stevens, D., 2017, Using the STARS Protocol for Identifying Students At-Risk During the Transition to High School, Division D Paper
Stevens, D., 2015, Building and Utilizing an Academic Support Index to Identify and Support Students At-Risk for Academic Underachievement, Regional Distinguished Paper Session

California Educational Research Association Annual Meetings
Stevens, D., 2016, A Comparison of the Local Control Funding Formula and the Academic Support Index in Predicting Academically Underperforming Students 
Stevens, D., 2015, Identifying Students for Transition Support
Stevens, D., 2015, Boosting Test Performance for At-Risk Students
Stevens, D., 2014, Building and Utilizing an Academic Support Index to Identify and Support Students At-Risk for Academic Underachievement 

Learn more about using the ASI framework in your school or district here.