Thomas Kehle, professor of school psychology in the Neag School Department of Educational Psychology, passed away on Feb. 7, 2018. (Photo Credit: Shawn Kornegay/Neag School)
Thomas J. Kehle, professor of school psychology in the Neag School Department of Educational Psychology, passed away on Feb. 7, 2018.
An expert in such areas as cognitive psychology, school climate, assessment, classroom discipline, and behavioral intervention, Kehle joined the faculty at the University of Connecticut in 1987.
“Tom will be remembered for his devotion to his family and friends, and his love for the University of Connecticut.”
— Scott Brown, Board of Trustees Distinguished Professor
“Tom had been a professor of educational psychology and the program director of the graduate program in school psychology for over 25 years, where he led the program through multiple APA and NASP accreditation reviews, mentored numerous doctoral and master’s students, and guided the development of one of the top five graduate programs in school psychology, nationally,” says Scott Brown, Board of Trustees Distinguished Professor of Educational Psychology and department head. “Tom will be remembered for his devotion to his family and friends, and his love for the University of Connecticut.”
Kehle was a fellow of the American Psychological Association (APA); the Association for Psychological Science; and the American Association of Applied and Preventative Psychology, as well as a licensed psychologist in the state of Connecticut and previously in Utah and Ohio. He was also a member of the National Register of Health Service Providers in Psychology, a charter member of the Society for the Study of School Psychology, and an honorary member of the American Academy of School Psychology.
He served as an associate editor of psychology in the schools and on the editorial boards of the Journal of Psychoeducational Assessment, Gifted Child Quarterly, and the International Journal of Educational and School Psychology. He had been involved in state, national, and international professional associations, including serving for several years as a folio reviewer for the National Association of School Psychologists (NASP), and as a site visitor for the APA.
He had published more than 185 peer-reviewed articles, chapters, and reviews in the professional literature, and also had presented upwards of 155 papers at national and international conferences. In a recent study, it was determined that he was the second-most prolific contributor to school psychology journals over the past decade. In addition, in the capacity of principal or co-principal investigator, Kehle had secured more than $2.2 million in contracts that primarily were used to support students. His research interests involved evidence-based interventions to promote children’s academic and social functioning, and their sense of psychological well-being.
His other honors included having received the Legends in School Psychology Award and the Outstanding Contribution to Training Award, both from the NASP; the 2006 Faculty Excellence in Research Award from the University of Connecticut; and a Reviewer of the Year Award from School Psychology Quarterly.
Kehle earned his master’s degree and Ph.D. from the University of Kentucky.
A memorial service will be held for Thomas Kehle from 12:30-4 p.m. on Saturday, March 17, at the Charles B. Gentry Building at 249 Glenbrook Road on the UConn Storrs campus. In lieu of flowers, the family requests that contributions be made to the Thomas J. Kehle Ph.D. Scholarship at s.uconn.edu/kehle. Read his obituary here.
Thanks in part to the ongoing efforts of David Alexandro, a doctoral student in the Neag School, and his colleagues at the Connecticut State Department of Education, Connecticut’s school districts will soon be using what is known as an Early Warning System (EWS) to predict students’ academic milestones and specific student outcomes. (Photo credit: Amy Jones)
Each year, more than half a million students drop out of high school in the United States.[1]But what if schools could predict which individuals were most at risk for dropping out — and perhaps even take action to prevent such an outcome? As it turns out, such a scenario is closer than ever to becoming a reality.
In more than 30 states across the nation[2] today, school districts are using what is known as an Early Warning System (EWS) to predict students’ academic milestones and specific student outcomes, including identifying those students who may be most likely to drop out. Connecticut is now on the cusp of joining them, thanks in part to the ongoing efforts of David Alexandro, a doctoral student in the Neag School’s measurement, evaluation, and assessment program, and his colleagues at the Connecticut State Department of Education (CSDE).
“State education departments, districts, and schools create early warning systems to improve student learning by addressing a range of outcomes,” says Alexandro, who is working with the CSDE to develop the state’s first EWS to help support Connecticut students in grades 1 through 12. “Within this framework, one of the most commonly studied outcomes is high school dropout. If a model can do a good job identifying potential dropouts early enough, then schools and districts can provide timelier, targeted supports and interventions to help more students graduate.”
“If a model can do a good job identifying potential dropouts early enough, then schools and districts can provide timelier, targeted supports and interventions to help more students graduate.”
— David Alexandro,
Ph.D. candidate, Neag School of Education
Connecticut’s Early Warning System In Connecticut, the EWS under development — called the Early Indication Tool (EIT) — relies on data that public schools and districts across the state are already required to provide to the Connecticut State Department of Education. Using this data, Connecticut’s EIT, according to Alexandro, will be able to model the probability that, for instance, a student will drop out of school based on a combination of factors, including attendance, behavior, and course performance.
Alexandro, an intern in the CSDE’s Performance Office, joined the project this past May and is building on work started by fellow Neag School doctoral student William Estépar-Garcia. Estépar-Garcia spent about a year extracting data from several CSDE databases and developing a series of models that would predict student achievement for K-12 students.
“The EIT plays an essential role in supporting local education agencies in Connecticut’s Every Student Succeeds Act (ESSA) plan,” Alexandro says. “Working at the CSDE and building the EIT models has helped me to appreciate the potential of early warning systems in education.”
In fact, developing the EIT has since become the basis of his dissertation, in which he will go beyond traditional EWS approaches by evaluating machine-learning methods to predict student dropout risk and improve early warning systems.
While traditional EWSs typically designate each student as “on-track” or “at-risk,” the EIT will go a step further by identifying a targeted support level for every student. In addition, the EIT is unique in that it will provide a longitudinal view of student data for every student in a school or district — not only those students who are at risk or in need of targeted support.
“The launch of the Early Indication Tool is a huge milestone for education in Connecticut.”
— Ajit Gopalakrishnan, Chief performance officer,
Connecticut State Department of Education
Now that the EIT’s models have been developed and tested at the state level, the tool, for students in grades 1 through 6, is being shared with districts statewide. Over recent months, Alexandro and his colleague Charles Martie, the CSDE education consultant who has been leading the state’s EWS development efforts, have been delivering presentations on the EIT to colleagues across Connecticut. In September, they presented the tool at the Performance Matters Forum, an interactive professional learning experience attended by more than 600 district and school leaders, data managers, and IT staff in Connecticut. In addition, through October and November, Alexandro and Martie presented the tool to education consultants, to CSDE leaders, at regional education research conferences, and during professional development sessions for principals, teachers, literacy coaches, and others.
David Alexandro discusses his research on the Early Indication Tool (EIT) at a 2017 Northeastern Educational Research Association poster session. (Photo courtesy of David Alexandro)
“The Connecticut State Department of Education is thrilled to provide an ‘early warning system’ tool to all school districts,” says Ajit Gopalakrishnan, CSDE’s chief performance officer. “UConn interns William Estepar-Garcia and David Alexandro worked with Dr. Charles Martie at the CSDE to conduct the requisite research and modeling that have now enabled us to launch our Early Indication Tool. Will and David are highly skilled, competent, and thoughtful professionals who are passionate about the work and eager to make a contribution. The launch of the EIT is a huge milestone for education in Connecticut.”
Meaningful Research Prior to joining the Neag School’s Ph.D. program, Alexandro had studied applied mathematics and engineering and, over the years, served as a management consultant; a programmer; a high school teacher; a volleyball, lacrosse, and basketball coach; and a high school administrator. It was his experiences in the realm of education that ultimately motivated Alexandro, a father of three, “to fully immerse [him]self in applied statistics and research, and work toward earning a Ph.D.”
The opportunity to work on the development and implementation of a successful EWS in Connecticut is one for which he is particularly grateful. “I am thrilled to have returned to my roots as a collaborative learner … while engaging in productive, interdisciplinary dialogue and meaningful research,” says Alexandro, who is working to complete his Ph.D. in May 2018.
“I would not be in a position to serve as an expert on this project without the training I received at the Neag School,” he adds, crediting Neag School faculty members Suzanne Wilson, Christopher Rhoads, Jane Rogers, Hariharan Swaminathan, and Eric Loken among his numerous mentors. “I bring a piece from each course I have taken in the measurement, evaluation, and assessment program to the EIT.”
EIT, which is currently being piloted in Connecticut, is scheduled to be fully implemented during the 2018-19 school year.
Access research reports, implementation guides, and more on Early Warning Systems compiled by the American Institutes for Research at earlywarningsystems.org.
