Tim Konold headshot
TK

Timothy R. Konold

Professor
Program Coordinator
Unit: Curry School of Education
Department: Curry School of Education
Office location and address
417 Emmet St S
Charlottesville, Virginia 22903
Education
Ph.D., University of Delaware, 1995
M.A., University of Delaware, 1993
M.S., Shippensburg University of Pennsylvania, 1990
Biography

Tim Konold, Ph.D. is Professor and Director of the Research, Statistics, and Evaluation program in the Curry School at the University of Virginia; and holds faculty affiliations with the Center for the Advanced Study of Teaching and Learning (CASTL), the Virginia Education Science Training (VEST) program, and the Youth Violence Project (YVP). He has taught introductory and advanced graduate level courses in psychometric theory and advanced quantitative methods at the University of Virginia for the past 20 years, and has served as the senior psychometric consultant for the Chartered Financial Analyst (CFA) international testing program for 15 years. He has authored more than 100 peer-reviewed articles, book chapters, published tests, and technical reports on topics that seek to infuse contemporary quantitative methods into work that has direct implications for policy and the education of children and youth with focus on large scale test use as it pertains to construction, interpretation, classification and errors of measurement.

CU-Project VISTA FY2013 ARRA
Source: Oregon State University
October 01, 2012 – September 30, 2015
CU-Project VISTA FY2013
Source: Oregon State University
October 01, 2012 – March 31, 2013
EDLF 5985: Internship
Credits: 1–6
Students apply academic experiences in professional and/or research settings; reflect and critically and constructively analyze experiences from multiple perspectives; and view the work as connecting course content authentic contexts. Students work as professionals with site supervisors and instructors to complete related assignments and relevant background research on the professional and academic resources available.
EDLF 7420: Quantitative Methods II: General Linear Models
Credits: 3
This course provides a theoretical and applied understanding of the general linear model in the context of continuous outcomes. Focus is on multiple regression with continuous predictors, dichotomous and multi-category predictors (i.e., ANOVA in a regression framework), and models that include combinations of these predictor types. Emphasis will also be placed on moderation and mediation, and model assumptions.
EDLF 8350: Multivariate Statistics
Credits: 3
Presents the theory and rationale of selected multivariate statistical techniques. Topics include multivariate analysis of variance canonical correlation, discriminant analysis, exploratory factor analysis, and confirmatory factor analysis. Emphasizes computer-assisted analysis and the application of appropriate statistical methods to research data. Prerequisite: EDLF 8300 and 8310, or instructor permission.
EDLF 9993: Independent Study
Credits: 1–12
Under close faculty guidance, students work on an area of interest not covered by the curriculum. A plan of study must be signed by the faculty sponsor and filed in the student's permanent file in the Office of Student Affairs. Prerequisite: Instructor permission.
EDLF 9998: Doctoral Research Apprenticeship
Credits: 3–12
Designed to give doctoral students experience conducting research in professional settings appropriate to their disciplines. Prerequisites: Advisor Permission Required.
EDLF 9999: Doctoral Dissertation
Credits: 3–12
Doctoral Dissertation Research completed under the guidance of dissertation committee. 12 hours is required for graduation. Permission of instructor required.