Evaluating written texts is believed to be a time-consuming process that can lack consistency and objectivity. Automated essay scoring (AES) can provide solutions to some of the limitations of human scoring. This research aimed to evaluate the performance of one AES system, Grammarly, in comparison to human raters. Both approaches' performances…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

The difference in how humans read and how Automated Essay Scoring (AES) systems process written language leads to a situation where a portion of student responses will be comprehensible to human markers, but unable to be parsed by AES systems. This paper examines a number of pieces of student writing that were marked by trained human markers, but…

Successful detection of unusual responses is critical for using machine scoring in the assessment context. This study evaluated the utility of approaches to detecting unusual responses in automated essay scoring. Two research questions were pursued. One question concerned the performance of various prescreening advisory flags, and the other…

Automatic essay scoring (AES) refers to the process of scoring free text responses to given prompts, considering human grader scores as the gold standard. Writing such essays is an essential component of many language and aptitude exams. Hence, AES became an active and established area of research, and there are many proprietary systems used in…

Scientific argumentation is one of the core practices for teachers to implement in science classrooms. We developed a computer-based formative assessment to support students' construction and revision of scientific arguments. The assessment is built upon automated scoring of students' arguments and provides feedback to students and teachers.…

This study explored the extent to which the ethnic identity of a writer and the background (gender and area of teaching) of a rater can influence mainstream teacher candidates' evaluation of English as a second language (ESL) writing, using a matched-guise method. A one-page essay was elicited from an ESL learner enrolled in an intensive English…

This report presents work on the development of a new corpus of non-native English writing. It will be useful for the task of native language identification, as well as grammatical error detection and correction, and automatic essay scoring. In this report, the corpus is described in detail.

This study was an expanded replication of an earlier endeavor (Shermis, Burstein, & Bliss, 2004) to document the writing outcomes associated with automated essay scoring. The focus of the current study was on determining whether exposure to multiple writing prompts facilitated writing production variables (Essay Score, Essay Length, and Number…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…