Webcast Details
Aired on: March 8th, 2016
3:30–4:30 p.m. (ET)
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Our Guest(s) This Week
Dr. Mariam Azin
This Week's Topic
Students who are becoming disengaged from school and are at risk for dropping out and other major negative events typically show signs years in advance. Such signs of risk may be more subtle in the beginning, but tend to grow in breadth, frequency, and severity if unaddressed over time. While there is an inherent tendency to always focus on “putting out the fires,” how do we move our systems more towards “fire prevention”?
This session will share cutting edge research on how “risk” manifests itself differently across the K-12 lifespan of a student. Implications for embedding effective early warning and interven- tion systems will be discussed. This broadcast will:
•Explore the nature of “risk”—what it is, how it can be operationalized, and how it tends to manifest itself over the lifespan of a student.
• Provide an overview of the latest research and technology developments as they pertain to early warning systems (EWS), including key attributes necessary to promote the effectiveness and desired impact(s) of early warning systems.
• Enable participants to gain an understanding of common pitfalls and barriers to dropout prevention efforts and common reasons why some efforts may not produce the intended effects.
Resources:
Information on Interventions:
U.S. Department of Education “Early Warning Timely Response: A Guide to Safe Schools”. http://cecp.air.org/guide/guide.pdf This resource talks about the effectiveness of timely response to early signs of risk 
.
Kennelly, L. and M. Monrad (2007). Approaches to dropout prevention: Heeding early warning signs with appropriate interventions. Technical report, National High School Center, Washington D.C. http://www.betterhighschools.org/docs/nhsc_approachestodropoutprevention.pdf
.
The IES What Works Clearninghouse conducts reviews on the different programs, products, practices, and policies in education. Focusing on the results from high-quality research, they try to answer the question “What works in education?” including Dropout Prevention Programs.” http://ies.ed.gov/ncee/wwc.
Information on Early Warning Systems
This is an example of next generation early warning systems that are research-based and data driven, utilizing a predictive analytics framework: http://brightbytes.net/solutions/early-warning/
Jerald, C. D. (2006). Identifying potential dropouts: Key lessons for building an early warning data system. Technical report, Achieve, Inc., Washington D.C. http://www.jff.org/sites/default/files/IdentifyingPotentialDropouts.pdf
Additional article on the use of predictive modeling in promoting more accurate identification of potential dropouts: Examining the Multiple Trajectories Associated with Dropping Out of High School
Kennelly, L. and M. Monrad (2007). Approaches to dropout prevention: Heeding early warning signs with appropriate interventions. Technical report, National High School Center, Washington D.C. http://www.betterhighschools.org/docs/nhsc_approachestodropoutprevention.pdf