Human essay grading is a laborious task that can consume much time and effort. Automated Essay Scoring (AES) has thus been proposed as a fast and effective solution to the problem of grading student writing at scale. However, because AES typically uses supervised machine learning, a human-graded essay corpus is still required to train the AES…

In Automated Essay Scoring (AES) systems, many previous works have studied group fairness using the demographic features of essay writers. However, individual fairness also plays an important role in fair evaluation and has not been yet explored. Initialized by Dwork et al., the fundamental concept of individual fairness is "similar people…

As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need arises to automatically provide formative feedback to written responses provided by students in response to readings. This study develops models to automatically provide feedback to student summaries written at the end of intelligent textbook sections.…

Automated Essay Scoring (AES) can reliably grade essays at scale and reduce human effort in both classroom and commercial settings. There are currently three dominant supervised learning paradigms for building AES models: feature-based, neural, and hybrid. While feature-based models are more explainable, neural network models often outperform…

This quasi-experimental study seeks to improve the conceptual quality of summary essays by comparing two conditions, essay prompts with or without a list of 13 broad concepts, the concepts were selected across a continuum of the 100 most frequent words in the lesson materials. It is anticipated that only the most central concepts will be used as…

Questions exist as to whether AI tools, such as ChatGPT, can aid learning. This study examined whether in-class exercises involving error detection in text generated by ChatGPT can aid students' foreign language writing. Participants were Arabic-English speakers who were classified as ranging from modest to competent English users according to…

This short paper reports on the preliminary findings of a study into the use of Online Translators (OTs) by university language students. Students of Chinese, French, German, Japanese, and Spanish and their teachers responded to comparative surveys on their respective use and evaluation of OTs for L2 writing in formal language learning contexts.…

This study compared the effects of teacher feedback (TF) and online automated feedback (AF) on the quality of revision of English writing. It also examined the strengths and weaknesses of the two types of feedback perceived by English language learners (ELLs) as a foreign language (FL). Sixty-eight Chinese students from two English classes…

The current study examined the degree to which the quality and characteristics of students' essays could be modeled through dynamic natural language processing analyses. Undergraduate students (n = 131) wrote timed, persuasive essays in response to an argumentative writing prompt. Recurrent patterns of the words in the essays were then analyzed…

Rapid advancements in computing have enabled automatic analyses of written texts created in educational settings. The purpose of this symposium is to survey several applications of computerized text analyses used in the research and development of productive learning environments. Four featured research projects have developed or been working on:…

The paper describes initial efforts on creating a system for the automatic assessment of Swedish second language (L2) learner essays from two points of view: holistic evaluation of the reached level according to the Common European Framework of Reference (CEFR), and the lexical analysis of texts for receptive and productive vocabulary per CEFR…