The Berkeley Evaluation and Assessment Research (BEAR) Center designs and delivers educational assessment instruments, performs research in assessment and psychometrics, and trains graduate students in these areas.
We collaborate with researchers in universities across the United States and abroad to develop software and other resources for constructing, managing, administering, and analyzing assessments.
The Desired Results Developmental Profile (DRDP) is the assessment required for all children in all state-funded early care and education programs in California. DRDP assesses the key domains of development for children from early infancy through kindergarten. Beginning in 2001, the BEAR Center researchers have designed and implemented valid and reliable measurement of development in early childhood, and created the DRDPtech assessment software system for teachers.
The Carbon Cycle Project involves the development of a research-based learning progression for an important topic in the life, physical, and earth sciences. These processes are a fundamental part of the K-12 science curriculum, and their importance is likely to grow in the future.
The BEAR Center is collaborating with a team of mathematics education content experts at Arizona State University led by Pat Thompson on this NSF-funded project. The goal of Project Aspire is to develop an instrument that assesses secondary mathematics teachers’ mathematical knowledge for teaching secondary mathematics.
The ADM project aims to develop an assessment system to evaluate elementary and middle school students’ skills and understanding related to data modeling and statistical reasoning.
This issue is dedicated to the analysis of factorial versus typological models, with a target article by Von Davier, Naemi and Roberts that describes an exploration of the distinction between typological and factorial latent variables in the domain of personality theory.
Selected presentations by BEAR Center researchers:
Minjeong Jeon - University of California, Berkeley
In this study, a first-order autoregressive or dynamic IRT growth model is proposed for longitudinal binary item analysis where responses to the same items are conditionally dependent across time given the latent trait. The initial conditions problem is treated using the idea suggested by Heckman (1981) and the implementation by Aitkin and Alfo (2003). The implication of this treatment is examined with respect to measurement invariance.
Poster and paper presentations for AERA 2013 by BEAR team members and QME students. Poster Presentation 1. Improving Explanatory Inferences from Assessments Presenter - Ronli Diakow Paper Presentations 1. Coding Student Responses: An Iterative and Construct-Driven Approach that uses Multiple Sources of Data. Tina Chiu and Linda Morell...
The Role of Teacher Personal Characteristics, School and Municipality Characteristics in Two Teacher Quality Measures
María Verónica Santelices
There is ample research documenting the importance of teacher quality for effective student learning. This general agreement has sparked renewed interest in assessing and rewarding teacher performance, especially in countries where student achievement has stayed below expectations. The way in which to measure teacher quality and implement teacher performance assessment is diverse and depends on each national or local context.