Author: Paul Barnett

In Memoriam: Professor Thomas Kehle

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. (Read the full article)


The obituary from the School Psychology Program may be downloaded here.

The obituary from the Hartford Courant may be viewed here.


Students in Poverty Less Likely to be Identified as Gifted

UConn gifted education specialists have published the first study to demonstrate a link between student poverty, institutional poverty, and the lower identification rate of gifted low-income students.

The study, “Disentangling the Roles of Institutional and Individual Poverty in the Identification of Gifted Students,” was published in the journal Gifted Child Quarterly. Researchers found that students eligible for free or reduced lunch programs are less likely to be identified for gifted education services even after controlling for prior math and reading achievement scores. In addition, the findings indicated that students in low-income schools have a further reduced possibility of being identified for gifted services.  (Read the full article)

Prof. VanHeest quoted on her work on sport science in her new book!

Behind the artistry of today’s Olympic figure skaters lies some serious science. A new book by UConn professor Jaci VanHeest will make the research underlying elite skaters’ training accessible for the first time to coaches and athletes everywhere.

“Every sport has its mythology, but the science is critical,” says VanHeest.

Figure skating is one of the oldest Olympic sports, but there’s not a lot written about the science of it. Coaches who want data-driven training techniques have very little information to go on. Jaci VanHeest, associate professor of educational psychology in the Neag School of Education with a joint appointment in kinesiology in the College of Agriculture, Health, and Natural Resources, specializes in the performance of elite athletes and is a member of the Medicine and Science committee for USA Figure Skating. She and her coauthor and former graduate student in exercise physiology, Jason Vescovi, now with Skate Canada, wrote The Handbook of Sports Medicine and Science, Figure Skating to fill that gap. …(Read full article)

EPSY Ph.D. Student Co-Authors Newly Released Report to Congress

Thanks in part to the evaluation expertise of a doctoral student in the Neag School’s measurement, evaluation, and assessment (MEA) program, a recently released report from the U.S. Government Accountability Office (GAO) revealed that about 1 percent of enrollments in federal health-insurance plans in 2015 were potentially improper or fraudulent.

The report, a federal audit of the Affordable Care Act, was requested by Congress and released last month by the GAO — a nonpartisan agency that serves to investigate how the federal government spends taxpayer dollars. The GAO research team analyzed the most current data available, pulling together databases from multiple federal sources. It was as an intern this past summer with the GAO’s Forensic Audits and Investigative Services team in Washington, D.C., that Neag School Ph.D. candidate Kristen Juskiewicz assisted in executing the audit. (Read full article)

Doctoral student David Alexandro helping to predict and prevent dropouts.

In more than 30 states across the nation 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).


Read the full article here

Professor Ron Beghetto Named 2018 APA Rudolf Arnheim Award Winner

Congratulations to the 2018 Award Winners!

The winners are in! Here are the recipients of the 2018 awards for the Society for the Psychology of Aesthetics, Creativity, and the Arts.


Rudolf Arnheim Award

The Arnheim Award is given for outstanding lifetime achievement in the psychology of aesthetics, creativity and the arts.

Our winner for 2018 is Ronald Beghetto, University of Connecticut.



2018 Modern Modeling Methods Conference: Call for Proposals

The Modern Modeling Methods (M3) conference is an interdisciplinary conference designed to showcase the latest modeling methods and to present research related to these methodologies. The 8th annual M3 conference will be held May 21nd-24th, 2018 at the University of Connecticut. Keynote speakers for the 2018 conference include Dr. Susan Murphy (Harvard University), Dr. Tenko Raykov (Michigan State University) and Dr. Peter Molenaar (Pennsylvania State University). In addition, Susan Murphy and David Almirall will offer a day long pre-conference workshop on Just In Time Adaptive Interventions on Monday, May 21st. Tenko Raykov will offer a post-conference workshop on Item Response Theory: A Latent Variable Modeling Approach on Thursday, May 24th.

Submissions for the 2018 conference are due 2/1/18. We welcome both methodological research papers and papers that illustrate novel applications of methodological techniques in the area of modeling, broadly defined. Papers related to latent variable modeling, multilevel modeling, mixture modeling, longitudinal modeling, and item response theory are especially encouraged. Given the interdisciplinary focus of the conference, it is completely acceptable to present papers that have been published or presented elsewhere. Presenters may select the length of the session that they prefer: 30 minutes, 60 minutes, or 90 minutes.  We also welcome proposals for multi-paper symposia on thematically grouped topics. Generally, symposia sessions are 90 minutes in length. We are also soliciting proposals for the poster session.  Students are also encouraged to submit proposals, especially for the poster session.

Conference proposals for the Modern Modeling Methods conference may fall into one (or more) of four categories: Methodological Innovation, Methodological Application, Methodological Illustration, or Methodological Evaluation. Methodological Innovation proposals introduce a new technique. Methodological Evaluation proposals present the results of empirical research evaluating a methodology. Most often, these will involve simulation studies. Methodological Application proposals present the methods and results of a real research study in which the technique was used. Methodological Illustration proposals provide a pedagogical illustration of when and how to use the technique; these papers are designed to help the audience be able to implement the technique themselves.

There are three different types of presentations: Paper sessions (in which authors submit a single paper), Symposia (in which a group of authors submit a set of related talks/papers), and posters. All papers should include a 150-200 word abstract that will appear in the conference program. Methodological Research paper proposals should be no longer than 1000 words and should include purpose, background, methods, results, discussion, and significance. Methodological Illustration paper proposals should be no longer than 1,000 words and should include a description of the methodology to be illustrated as well as an outline of the paper/talk. Proposals for symposia should be include titles, authors, an abstract for the symposium, and brief descriptions/abstracts for all of the paper presentations within the symposium. Symposium proposals may be longer than 1000 words if needed, but they should be less than 2000 words. Proposals for the poster session need only submit an abstract: the 1000 word proposal is not required for poster session proposals.

Proposals for the 2018 conference are due February 1st, 2018. Notifications of presentation status will be emailed by February 19th, 2018.  To submit a conference proposal, please go to MMM2018 . For more information about the 2018 Modern Modeling Methods conference, please visit .

Data Analysis Training Institute of Connecticut (DATIC) 2018 Summer Workshops

DATIC ( is offering 4 workshops at the University of Connecticut in June, 2018: Mixture Modeling, Introduction to Data Analysis in R, Multilevel Modeling in R, and Dyadic Analysis with R.  Registration is now open.  Go to  for more information and to register for the workshops.


Mixture Modeling

June 4-6, 2018

Dr. Eric Loken


This 3-day mixture modeling workshop will survey techniques for exploring heterogeneous latent structure in data. We will begin by defining a variety of mixture models. The main focus will be on latent class analysis (LCA) and latent profile analysis (LPA), with applications in health and education. Additional models will include mixture regression models, mixture IRT, k-means clustering, and growth mixture models for longitudinal data. The course will emphasize hands-on work by participants, who will also be encouraged to make connections to their own data, learning to execute many of these models in R. Particular attention will be paid to issues that arise in applied settings including model assumptions, parameter estimation, and interpretation.


Introduction to Data Analysis in R

Instructor: Dr. Randi L. Garcia

Two separate sessions of the R workshop are being offered.

Session 1: June 7 June 8, 2018

·         Thursday and Friday (prior to Multilevel Modeling with R Workshop)

Session 2: June 21 June 22, 2018

·         Thursday and Friday (prior to Dyadic Data Analysis with R workshop)

Are you curious about using R for data analysis? Have you been thinking about making the switch to R, but don’t know where to start? This two-day workshop is the perfect quick start guide to analyzing your data with R. We will cover the fundamentals of data analysis in R with a special focus on translating your existing knowledge and skills from other software (e.g., SPSS) into R. The goal of this workshop is to develop proficiency in R for data preparation and preliminary data analysis. We will build confidence in importing data from different sources into RStudio and getting that data ready for any advanced technique you might then employ. Among the topics to be covered are intro to the RStudio environment, packages, and RMarkdown, data manipulation, data visualization, correlations, reliability tests, basic inference tests, ANOVA, linear regression, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and more. Instruction on the specific statistics and statistical models will be minimal to zero. It is assumed that you already know how to do these analyses, but you want to see how to do them in R. You do not need to be registered for any other DATIC workshops to enroll in the 2 day Introduction to Data Analysis in R workshop.


Multilevel Modeling Using R Workshop

June 11-15, 2018

Drs. D. Betsy McCoach & Randi Garcia


This workshop covers the basics and applications of multilevel modeling with extensions to more complex designs. Participants will learn how to analyze both organizational and longitudinal (mostly growth curve) data using multilevel modeling and to interpret the results from their analyses. Although the workshop does not require any prior knowledge or experience with multilevel modeling, participants are expected to have a working knowledge of multiple regression. The emphasis will be practical with minimal emphasis on statistical theory, but those seeking more statistical information can arrange an individualized session with the instructors. All analyses will be demonstrated using R. Instruction will consist of lectures, computer demonstrations of data analyses, and hands-on opportunities to analyze practice data sets using R. The workshop emphasizes practical applications and places minimal emphasis on statistical theory.   No prior familiarity with R is required, but if you have never used R and want to gain a general proficiency working with data in R, we encourage you to take the two-day DATIC Intro to R and RStudio workshop held on Thursday, June 7, through Friday, June 8, 2018.


Dyadic Data Analysis with R

June 25 – June 29, 2018

Instructors: Drs. Randi L. Garcia and David A. Kenny


The Dyadic Data Analysis workshop focuses on the analysis of dyadic data when both members of a dyad are measured on the same variables. All analyses will use multilevel modeling in R via the RStudio graphical interface. Participants will learn how to analyze dyadic data and to interpret the results from their analyses. Among the topics to be covered are the vocabulary of dyadic analysis, non-independence, data structures, and the Actor-Partner Interdependence Model. We also discuss mediation and moderation of dyadic effects. On day 4, participants choose from one of two break-out sessions: 1) the analysis of over-time dyadic data (e.g., growth curve models) or 2) dyadic data analysis with SEM using the lavaan R package (e.g., Actor‑Partner Interdependence Model and Common Fate Model). The discussion of over‑time data is limited to one day so the workshop should not be construed as workshop on longitudinal dyadic analysis. Participants should have a working knowledge of multiple regression. No prior familiarity with R is required, but if you have never used R and want to gain a general proficiency working with data in R, we encourage you to take the two-day DATIC Intro to R and RStudio workshop.