Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…

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…

Recent studies on the use of Intelligent Personal Assistant (IPA) for second language (L2) learning have found that IPAs such as "Amazon's Alexa" is useful and motivating for L2 learners and that learners' language proficiency might influence their perceptions toward IPAs. However, most existing studies focused on the potentials of…

This study focuses on how teachers' pedagogical content knowledge (PCK) of mathematics may differ depending on teacher interactions in an online teacher community of practice (CoP). The study utilizes data from 26,857 posts collected from the South Korean self-generated online teacher CoP, 'Indischool'. This data was then analyzed using natural…

Anthropogenic climate change is a scientific fact, but U.S. public discourse around the issue remains mired in controversy, including in education. Our study leverages natural language processing methods to give a precise look into the extent to which climate change-related topics are covered in 30 of the most widely used high school history…

Following the burgeoning growth of artificial intelligence (AI) and machine learning (ML) applications in language assessment in recent years, the meteoric rise of ChatGPT and its sweeping applications in almost every sector have left us in awe, scrambling to catch up by developing theories and best practices. This special issue features studies…

Multiple-choice quizzes (MCQs) are a popular form of assessment. A rapid shift to online assessment during the COVID-19 pandemic in 2020, drove the uptake of MCQs, yet limited invigilation and wide access to material on the internet allow students to solve the questions via internet search. ChatGPT, an artificial intelligence (AI) agent trained on…

This study aims to evaluate the effectiveness and potential utility of using machine learning and natural language processing techniques to develop models that can reliably predict the relative difficulty of incoming chat reference questions. Using a relatively large sample size of chat transcripts (N = 15,690), an empirical experimental design…

Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…

Peer assessment has been widely applied across diverse academic fields over the last few decades, and has demonstrated its effectiveness. However, the advantages of peer assessment can only be achieved with high-quality peer reviews. Previous studies have found that high-quality review comments usually comprise several features (e.g., contain…

The advancement of artificial intelligence (AI) tools has revolutionized teaching and learning, particularly in healthcare education, where they enhance pedagogy, foster immersive learning, and support healthcare provision. However, their use in healthcare education is contentious, warranting careful examination, especially regarding Generative AI…

The application of natural language processing (NLP) technology in the field of education has attracted considerable attention. This study takes 716 articles from the Web of Science database from 1998 to 2023 as its research sample. Using bibliometrics as the theoretical foundation, and employing methods such as literature review and knowledge…

As AI technologies like GPT models continue to reshape various aspects of society, it is imperative to investigate the perceptions and ethical considerations of graduate students regarding GPT's use in academic settings. This mixed-method exploratory study engaged 21 graduate students through surveys and focus group interviews. The findings…

This study investigates the perceptions of English language teachers regarding the use of ChatGPT in English Language Teaching (ELT). The study aims to fill the research gap by exploring teachers' perspectives on the integration of ChatGPT as an instructional tool and its implications for ELT practices. Using a mixed methods approach, the study…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…