In automated essay scoring (AES), essays are automatically graded without human raters. Many AES models based on various manually designed features or various architectures of deep neural networks (DNNs) have been proposed over the past few decades. Each AES model has unique advantages and characteristics. Therefore, rather than using a single-AES…

In automated essay scoring (AES), scores are automatically assigned to essays as an alternative to grading by humans. Traditional AES typically relies on handcrafted features, whereas recent studies have proposed AES models based on deep neural networks to obviate the need for feature engineering. Those AES models generally require training on a…

We investigated the relationship between the scores assigned by an Automated Essay Scoring (AES) system, the Intelligent Essay Assessor (IEA), and grades allocated by trained, professional human raters to English essay writing by instigating two procedures novel to written-language assessment: the logistic transformation of AES raw scores into…

This study employed a mixed-design approach and the Many-Facet Rasch Measurement (MFRM) framework to investigate whether rater bias occurred between the onscreen scoring (OSS) mode and the paper-based scoring (PBS) mode. Nine human raters analytically marked scanned scripts and paper scripts using a six-category (i.e., six-criterion) rating…

This study uses the feature sets employed by two automated scoring engines to determine if a "linguistic profile" could be formulated that would help identify items that are likely to exhibit differential item functioning (DIF) based on linguistic features. Sixteen items were administered to 1200 students where demographic information…

This study investigated the application of "WriteToLearn" on Chinese undergraduate English majors' essays in terms of its scoring ability and the accuracy of its error feedback. Participants were 163 second-year English majors from a university located in Sichuan province who wrote 326 essays from two writing prompts. Each paper was…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…