Archived Posts

Kristen Juskiewicz co-authored report recently released by the U.S. Government Accountability Office

Kristen Juskiewicz

Kristen Juskiewicz served as a Program Analyst for the Forensic Audits and Investigative Service team during her Summer 2017 internship with the U.S. Government Accountability Office (GAO) in Washington, D.C. She was assigned to the federal audit of the Affordable Care Act, specifically an audit of the applicant enrollment and eligibility-verification process for the Federal Health-Insurance Marketplace. The purpose of this audit was to investigate possible fraudulent or improper enrollments for plan year 2015.

During the course of her 11-week internship, Ms. Juskiewicz assisted in the qualitative analysis of sample cases, interviews with stakeholders, source documentation and management, and the presentation of initial findings. She co-authored a number of internal reports, which served to document legal background, interviews records, and analysis records. Through this internship, she was able to experience portions of the entire GAO audit process via a shadowing program with team directors and assistant directors. Ms. Juskiewicz also forged a relationship with the GAO Applied Research and Methodology team, and aided them in exploration of Geographic Information Systems (GIS) via R packages.

The report is available at: https://www.gao.gov/products/GAO-18-169

RMME Community Members Discuss Research at NERA 2017

RMME Community members (now, both RMME PhD alumni), David Alexandro and Xiaowen Liu, discuss presented research at NERA 2017. Congratulations on this successful presentation, from the Research Methods, Measurement, & Evaluation Community!

 

RMME PhD Students, David Alexandro and Xiaowen Liu Discuss a Poster Presentation at NERA 2017

 

Presenter: David Alexandro

Authors: Charles Martie, David Alexandro, William Estepar-Garcia, & Ajit Gopalakrishnan

Poster Presentation Title: Every Target and Milestone Matters: Developing Connecticut’s Evidence-Based Early Indication Tool (EIT)

Poster Abstract: Early warning systems typically focus on students’ dropout risk. The Connecticut State Department of Education extended this model to create the Early Indication Tool (EIT), a K-12 system that predicts student performance, identifies students who are at-risk of missing milestones and/or dropping out, and ultimately facilitates more timely interventions.

We are seeking graduate students for the 2018-2019 academic year!

The MEA program is seeking bright, motivated, quantitatively oriented graduate students for our M.A. and Ph.D. programs.  All current faculty will consider accepting new advisees for the 2018-2019 academic year.  We anticipate being able to offer full graduate assistantships to 3-5 incoming graduate students. To learn more about our graduate programs, feel free to email any of the MEA program faculty.

2018 Modern Modeling Methods Conference- May 21-24, 2018

The 2018 Modern Modeling Methods conference will be held at the University of Connecticut May 21-24, 2018. Keynote speakers include Susan A. Murphy (Harvard), Peter Molenaar (Penn State), and Tenko Raykov (MSU).  The proposal submission site is now open.  Proposals are due 2/1/18. Please go to www.modeling.uconn.edu for more details about presenting and attending.