In automated essay scoring (AES) systems, similarity techniques are used to compute the score for student answers. Several methods to compute similarity have emerged over the years. However, only a few of them have been widely used in the AES domain. This work shows the findings of a ten-year review on similarity techniques applied in AES systems…

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…

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…

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…

Automated Essay Scoring (AES) technologies provide innovative solutions to score the written essays with a much shorter time span and at a fraction of the current cost. Traditionally, AES emphasized the importance of capturing the "coherence" of writing because abundant evidence indicated the connection between coherence and the overall…

Automated essay scoring (AES), where natural language processing is applied to score written text, can underpin educational resources in blended and distance learning. AES performance has typically been reported in terms of correlation coefficients or agreement statistics calculated between a system and an expert human examiner. We describe the…

In higher education, the entry-level, not-for-credit courses in Developmental Education play a pivotal role for incoming degree-seeking students. Focusing specifically on Developmental Writing, at two- and four-year public and private institutions across the country, a common requirement to pass the course is a summative argumentative essay that…

Automated Essay Scoring (AES) using neural networks has helped increase the accuracy and efficiency of scoring students' written tasks. Generally, the improved accuracy of neural network approaches has been attributed to the use of modern word embedding techniques. However, which word embedding techniques produce higher accuracy in AES systems…

Purpose: The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the…

Grouping individuals according to a set of measured characteristics, or profiling, is frequently used in describing, understanding, and acting on a phenomenon. The advent of computer-based assessment offers new possibilities for profiling writing because aspects can be captured that were not heretofore observable. We explored whether writing…

Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…

Agreement statistics and measures of prediction accuracy are often used to assess the quality of two measures of a construct. Agreement statistics are appropriate for measures that are supposed to be interchangeable, whereas prediction accuracy statistics are appropriate for situations where one variable is the target and the other variables are…

Scoring essays is generally an exhausting and time-consuming task for teachers. Automated Essay Scoring (AES) facilitates the scoring process to be faster and more consistent. The most logical way to assess the performance of an automated scorer is by measuring the score agreement with the human raters. However, we provide empirical evidence that…

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…

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…