This study, which is part of a larger project that aims to make online math more accessible to students with visual impairments (VI), examines the text quality of math assessment items for students with VI who use screen readers. Using data from about 29.5 million students taking standard versions of the MAP Growth math assessment, and 48,845…

In contrast to simple feedback, which provides students with the correct answer, elaborated feedback provides an explanation of the correct answer with respect to the student's error. Elaborated feedback is thus a challenge for AI in education systems because it requires dynamic explanations, which traditionally require logical reasoning and…

Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…

We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…

The present study examined phonological processing skills (phonological memory, phonological awareness, and rapid automatised naming, RAN) in relation to early Chinese reading and early Chinese mathematics for young children. Early Chinese reading was assessed with single character reading and multi-character word reading, and early mathematics…

Metacognition is a valuable tool for learning, since it is closely related to self-regulation and awareness of one's own affect. However, methods for automatically detecting and studying metacognition are scarce. Thus, in this paper we describe an algorithm for automatic detection of metacognitive language in writing. We analyzed text from the…

The growing use of machine learning for the data-driven study of social issues and the implementation of data-driven decision processes has required researchers to re-examine the often implicit assumption that datadriven models are neutral and free of biases. The careful examination of machine-learned models has identified examples of how existing…

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

An NLP algorithm was developed to assess question quality to inform feedback on questions generated by students within iSTART (an intelligent tutoring system that teaches reading strategies). A corpus of 4575 questions was coded using a four-level taxonomy. NLP indices were calculated for each question and machine learning was used to predict…

The Cattell-Horn-Carroll (CHC) factors of the Woodcock-Johnson (WJ) Arabic Tests of Cognitive Abilities were studied with a group of students at risk of Math Disability (MD) (n50) and average students (n50) between second and fourth grades. Specifically, several statistical analyses were conducted using the seven CHC factors identified by the WJ…

Gesturing is ubiquitous in communication and serves an important function for listeners, who are able to glean meaningful information from the gestures they see. But gesturing also functions for speakers, whose own gestures reduce demands on their working memory. Here we ask whether gesture's beneficial effects on working memory stem from its…

This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…

The way words are used in natural language can influence how the same words are understood by students in formal educational contexts. Here we argue that this so-called semantic contamination effect plays a role in determining how students engage with mathematical proof, a fundamental aspect of learning mathematics. Analyses of responses to…

Using qualitative data collection and analyses techniques, we examined mathematical representations used by sixteen (N=16) teachers while teaching the concepts of converting among fractions, decimals, and percents. We also studied representational choices by their students (N=581). In addition to using geometric figures and manipulatives, teachers…