In this webinar, learn more about the relationship between self-efficacy and the achievement gap for English Language Learners (ELLs).

Through a series of simulation and empirical studies, we produce scores in a single-cohort repeated measure design using sum scores as well as multiple IRT approaches and compare the recovery of growth estimates from longitudinal growth models using each set of scores.

In this study, we conducted empirical and simulation analyses in which we scored surveys using item response theory (IRT) models that do and do not account for response styles, and then used those different scores in growth models and compared results.

This study leveraged a racially/ethnically diverse sample of third and fourth grade students and teachers in a large, urban district to investigate whether stable student and teacher characteristics (e.g., sex) and observed quality of classroom interactions influenced change in students’ perceptions of interactions with their teacher.

This study explored how response style affects estimates of growth.

A huge portion of what we know about how humans develop, learn, behave, and interact is based on survey data. Although there is great deal of guidance on scaling and linking IRT-based large-scale educational assessment to facilitate the estimation of examinee growth, little of this expertise is brought to bear in the scaling of psychological and social-emotional constructs. Through a series of simulation and empirical studies, we produce scores in a single-cohort repeated measure design using sum scores as well as multiple IRT approaches and compare the recovery of growth estimates from longitudinal growth models using each set of scores.

To avoid the subjectivity of having a single person evaluate a construct of interest (e.g., a student’s self-efficacy in school), multiple raters are often used. This study provides a model for estimating growth in the presence of multiple raters.