This study examines the potential to use non-expert, crowd-sourced raters to score essays by comparing expert raters' and crowd-sourced raters' assessments of writing quality. Expert raters and crowd-sourced raters scored 400 essays using a standardised holistic rubric and comparative judgement (pairwise ratings) scoring techniques, respectively.…

Oral reading fluency (ORF) assessments are commonly used to screen at-risk readers and evaluate interventions' effectiveness as curriculum-based measurements. Similar to the standard practice in item response theory (IRT), calibrated passage parameter estimates are currently used as if they were population values in model-based ORF scoring.…

Oral reading fluency (ORF) assessments are commonly used to screen at-risk readers and to evaluate the effectiveness of interventions as curriculum-based measurements. As with other assessments, equating ORF scores becomes necessary when we want to compare ORF scores from different test forms. Recently, Kara et al. (2023) proposed a model-based…

While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision. However, a neural AES typically does not provide useful feature representations for supporting AWE. This paper presents a method for linking AWE and neural AES, by extracting…

For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

The Hearts and Flowers (H&F) task is a computerized executive functioning (EF) assessment that has been used to measure EF from early childhood to adulthood. It provides data on accuracy and reaction time (RT) across three different task blocks (hearts, flowers, and mixed). However, there is a lack of consensus in the field on how to score the…

Assessments of natural language can provide vast information about individuals' thoughts and cognitive process, but they often rely on time-intensive human scoring, deterring researchers from collecting these sources of data. Natural language processing (NLP) gives researchers the opportunity to implement automated textual analyses across a…

The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…

Survey instruments and assessments are frequently used in many domains of social science. When the constructs that these assessments try to measure become multifaceted, multidimensional item response theory (MIRT) provides a unified framework and convenient statistical tool for item analysis, calibration, and scoring. However, the computational…

Background: Researchers interested in quantitative measures of student "success" in writing cannot control completely for contextual factors which are local and site-based (i.e., in context of a specific instructor's writing classroom at a specific institution). (In)ability to control for curriculum in studies of student writing…

Recent advances in automated writing evaluation have enabled educators to use automated writing quality scores to improve assessment feasibility. However, there has been limited investigation of bias for automated writing quality scores with students from diverse racial or ethnic backgrounds. The use of biased scores could contribute to…

The objective in the current paper is to examine the processes of how our research team negotiated meaning using an iterative design approach as we established, developed, and refined a rubric to capture comprehension processes and strategies evident in students' verbal protocols. The overarching project comprises multiple data sets, multiple…

The Colleague AI platform introduces a groundbreaking Rubric Generation function designed to streamline how educators create and use rubrics for instructional and assessment purposes. This feature uses artificial intelligence (AI) to produce standards-based rubrics tailored to course content for formative and summative evaluations. By automating…

This study describes the initial psychometric evaluation of the Understanding Procedures observation rubric for use as an instrument for feedback to teachers working in mathematics intervention settings. The rubric translates the research base from mathematics education and special education into practice in the form of specific items and…