A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

The problem of taking a data set and separating it into subgroups, where the members of each subgroup are more similar to each other than they are to members outside the subgroup, has been extensively studied in science and mathematics education research. Student responses to written questions and multiple-choice tests have been characterised and…

This study aimed to explore EFL students' use of writing strategies and their attitudes towards reading-to-write and writing-only tasks. The primary purpose of this study was to see whether there was any significant difference between the writing performance of reading-to-write and writing-only task groups of Iranian EFL learners. Also, this study…

This study evaluates the use of a hierarchical classification approach to automated assessment of essays. Automated essay scoring (AES) generally relies onmachine learning techniques that compute essay scores using a set of text variables. Unlike previous studies that rely on regression models, this study computes essay scores using a hierarchical…

This study focused on investigating the types of schooling beliefs (teaching and learning) expressed through metaphorical images by prospective teachers (PTs) from the United States. Participants (N = 215) rated 10 schooling metaphors illustrating the "student-school-teacher" relationships (i.e. "Passenger-Bus-Driver"; Student…

In this paper we describe the development and refinement of "evidence rules" and "measurement models" within the "evidence model" of the "evidence-centered design" (ECD) framework in the context of the "Packet Tracer" digital learning environment of the "Cisco Networking Academy." Using…