The digital transformation in educational assessment has led to the proliferation of large-scale data, offering unprecedented opportunities to enhance language learning, and testing through machine learning (ML) techniques. Drawing on the extensive data generated by online English language assessments, this dissertation investigates the efficacy…

This study explored the impact of integrating ChatGPT into asynchronous online discussions. The analysis encompassed students' log data from Canvas and their perspectives on using ChatGPT. Results revealed a significant enhancement in overall discussion participation when ChatGPT is encouraged, emphasizing its potential as a catalyst for…

Leveraging the campus learning management system and rapid e-learning development software such as Articulate Storyline allows educators to develop and deploy interactive tutorials for performance assessment of students' knowledge. This quick hit chronicles the development, deployment, and assessment of a suite of tutorials for information…

This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…

Accurately grading open-ended assignments in large or massive open online courses is nontrivial. Peer review is a promising solution but can be unreliable due to few reviewers and an unevaluated review form. To date, no work has leveraged sentiment analysis in the peer-review process to inform or validate grades or utilized aspect extraction to…

A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…

Language proficiency diagnosis is essential to extract fine-grained information about the linguistic knowledge states and skill mastery levels of test takers based on their performance on language tests. Different from comprehensive standardized tests, many language learning apps often revolve around word-level questions. Therefore, knowledge…

Recent research on learning analytics dashboards has focused on designing user interfaces that offer various forms of "visualization guidance" (often referring to notions such as "data storytelling" or "narrative visualization") to teachers (e.g., emphasizing data points or trends with colour and adding annotations),…

This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…

Drawing upon the growing datafication of contemporary schooling, our purpose in this article is to use topological thinking as an analytical device to better understand the professionals and practices within emergent data infrastructures. We address this by attending to an influential national (and subnational) data infrastructure of school…

Item response theory (IRT) is a popular method to infer student abilities and item difficulties from observed test responses. However, IRT struggles with two challenges: How to map items to skills if multiple skills are present? And how to infer the ability of new students that have not been part of the training data? Inspired by recent advances…

The 2022 EUROCALL conference was held in Reykjavik on 17-19 August 2022 as a fully online event hosted by the Vigdís Finnbogadóttir Institute for Foreign Languages, the University of Iceland, and the Árni Magnússon Institute for Icelandic Studies. The conference theme was "Intelligent CALL, granular systems and learner data." This theme…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

This paper discusses key concepts in the emerging field of technology-mediated task-based language teaching (TMTBLT) and provides a research agenda for moving this sub-field forward in a theoretically sound and data-driven way. We first define TMTBLT and discuss the importance of considering technological affordances and specific learning contexts…

Using a corpora approach involves using a series of texts in the language under study as a type of corpus on which to base acquisition. Languages in all forms (written, spoken, performed, formal, informal, etc.) are captured all the time through online and digital platforms, apps, etc. making them highly accessible. Applying corpora in teaching…