Tanesia Beverly successfully defended her doctoral dissertation entitled, “Examining Within Person Changes in Speed in a Verbal Reasoning Test.” Congratulations, Dr. Beverly!

Looking to enhance your skills in program evaluation, quantitative research, measurement and/or data analysis? Know a colleague who wants to develop this in-demand skill set? Get prepared for the future of Research Methods, Measurement, & Evaluation (RMME) at the University of Connecticut!

 

With 100% Online or Campus-based options for our 12-credit Graduate Certificate in Program Evaluation and 30-credit RMME Master’s Degree, we offer:

– Flexibility for working professionals—Study anytime, anywhere;

– Courses designed and taught by expert RMME faculty;

– Opportunities for individualized course selection to facilitate your personal career goals;

 And more!

 

Furthermore, with advanced planning, it is even possible to earn BOTH the Graduate Certificate in Program Evaluation and the RMME Master’s Degree WITH NO ADDITIONAL COURSEWORK (beyond the 30 credits required for the master’s degree).

For more information, please visit:

100% Online Program Evaluation Certificate

100% Online RMME Master’s Degree

Or email: methods@uconn.edu

 

Start your journey today—Spring 2021 application deadlines for both the Program Evaluation Certificate and RMME Master’s Degree programs are November 6, 2020, 11:59pm EST!

Come meet our faculty and learn more about UConn’s Research Methods, Measurement, & Evaluation (RMME) program! On Thursday, October 15th 2020, from 2:00 pm – 5:00 pm EDT, several RMME faculty members/graduates will participate in UConn’s Virtual Graduate School Fair. With one-on-one appointments and group information sessions (M.A. from 3:00pm – 3:30pm; Ph.D. from 3:30pm – 4:00pm), this event offers everything you need to decide that RMME is for you!

View our virtual profile at: https://app.joinhandshake.com/employers/572568 

Sarah D. Newton successfully defended her doctoral dissertation entitled, “Multilevel Model Selection and Effective Sample Size—In Information Criteria We Trust.” Congratulations, Dr. Newton!

Dakota Cintron successfully defended his doctoral dissertation entitled, “Statistical Estimation of Large Ordinal Factor Analysis Models.” Congratulations, Dr. Cintron!

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!

 

 

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.