Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…

The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…

In this paper, we extracted content-based and structure-based features of text to predict human annotations for claims and nonclaims in argumentative essays. We compared Logistic Regression, Bernoulli Naive Bayes, Gaussian Naive Bayes, Linear Support Vector Classification, Random Forest, and Neural Networks to train classification models. Random…

Synthesis writing is widely taught across domains and serves as an important means of assessing writing ability, text comprehension, and content learning. Synthesis writing differs from other types of writing in terms of both cognitive and task demands because it requires writers to integrate information across source materials. However, little is…

Synthesis writing is widely taught across domains and serves as an important means of assessing writing ability, text comprehension, and content learning. Synthesis writing differs from other types of writing in terms of both cognitive and task demands because it requires writers to integrate information across source materials. However, little is…

This study introduces the Constructed Response Analysis Tool (CRAT), a freely available tool to automatically assess student responses in online tutoring systems. The study tests CRAT on a dataset of chemistry responses collected in the ChemVLab+. The findings indicate that CRAT can differentiate and classify student responses based on semantic…

A number of studies have demonstrated strong links between students' language features (as found in spoken and written production) and their math performance. However, no studies have examined links between the students' language features and measures of their Math Identity. This project extends prior studies that use natural language processing…

A number of studies have demonstrated links between linguistic knowledge and performance in math. Studies examining these links in first language speakers of English have traditionally relied on correlational analyses between linguistic knowledge tests and standardized math tests. For second language (L2) speakers, the majority of studies have…

Writing training systems have been developed to provide students with instruction and deliberate practice on their writing. Although generally successful in providing accurate scores, a common criticism of these systems is their lack of personalization and adaptive instruction. In particular, these systems tend to place the strongest emphasis on…

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…

Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused…