Automated essay scoring (AES), where natural language processing is applied to score written text, can underpin educational resources in blended and distance learning. AES performance has typically been reported in terms of correlation coefficients or agreement statistics calculated between a system and an expert human examiner. We describe the…

In order to accurately assess the English language proficiency of special populations of English learners, student assessment programs must maintain the comparability of standard and modified assessment formats, allowing for equivalent inferences to be made across student classifications. However, given the typically small size of special…

Open-ended questions in mathematics are commonly used by teachers to monitor and assess students' deeper conceptual understanding of content. Student answers to these types of questions often exhibit a combination of language, drawn diagrams and tables, and mathematical formulas and expressions that supply teachers with insight into the processes…

In test equating, one critical equating property is the group invariance property which indicates that the equating function used to convert performance on each alternate form to the reporting scale should be the same for various subgroups. To mitigate the impact of disrupted learning on the item parameters during the COVID-19 pandemic, a…

In this study we evaluated the stability of item parameters and student scores, using the pre-equated (pre-pandemic) parameters from Spring 2019 and post-equated (post-pandemic) parameters from Spring 2021 in two calibration and equating designs related to item parameter treatment: re-estimating all anchor parameters (Design 1) and holding the…

In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…

The "Framework" and NGSS bring to the forefront the role of language in doing science and in learning from doing science. Yet, most existing science assessments for elementary learners do not integrate or attend to aspects of scientific language and literacy that are essential components of science proficiency. Accordingly, there is a…

Multiple-choice items are used in large-scale assessments of mathematical achievement for secondary students in many countries. Research findings can be implemented to improve the quality of the items and hence increase the amount of information gathered about student learning from each item. One way to achieve this is to create items for which…

Increasingly content area projects and programs at the K-12 level, such as in mathematics, involve a programmatic component or project emphasis on developing "teacher leadership". However, there is no consistent definition or framework for this construct and even fewer validated tools for measuring it. This paper describes our efforts in…

Vocabulary knowledge is crucial to literacy development and academic success. Previous research has shown learning the meaning of a word requires encountering it in diverse informative contexts. In this work, we try to identify "nutritious" contexts for a word--contexts that help students build a rich mental representation of the word's…

This article seeks to explain why, even in norm referenced assessment environments, students and other stakeholders should not be concerned that students who help peers learn are negatively impacting their own assessments. The article opens with a review of assessment options: norm referenced, criterion referenced and ipsative. Next, Social…

Assessing student presentations can be made more reliable with video-recording and post-performance rating. Further, self assessment and peer assessment can aid in the learning process by students when using specific, easy-to-understand rubrics. A ten-year action research study involved video-recorded performance assessment tasks using a free,…

As adaptive tutoring systems grow increasingly popular for the completion of classwork and homework, it is crucial to assess the manner in which students are scored within these platforms. The majority of systems, including ASSISTments, return the binary correctness of a student's first attempt at solving each problem. Yet for many teachers,…

We propose a novel unsupervised extractive approach for summarizing online reviews by exploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for sentence-level content scoring. The proposed method is metadata-driven, requiring no…

This study investigates a new approach to automatically assessing essay quality that combines traditional approaches based on assessing textual features with new approaches that measure student attributes such as demographic information, standardized test scores, and survey results. The results demonstrate that combining both text features and…