Leveraging technological tools in educational research expands investigations into participants' behaviors and provides insights into learning patterns and teaching effectiveness through innovative data collection and analysis methods. Using keylogging data software, this study explored trainee translators' process and product behaviors under two…

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…

Professionals within the field of language learning have predicted that chatbots would provide new opportunities for the teaching and learning of language. Despite the assumed benefits of utilizing chatbots in language classrooms, such as providing interactional chances or helping to create an anxiety-free atmosphere, little is known about…

Data-driven learning (DDL) is an increasingly popular area of research for language teaching and is gradually being incorporated into teacher education programs globally. However, assessing teacher trainees' (self-reported) corpus literacy, and its impact on eventually (and successfully) incorporating corpora into language teaching, is an ongoing…

This paper reports on the development and piloting of Classmoto, an online application designed to measure learner engagement. The application enables teachers to collect real-time analytics of student social, affective, and cognitive engagement. The results are immediately visible to the teacher. We investigated and reported on the engagement…

In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…

We study the automatic identification of educational items worthy of content authors' attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and…

The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…

Data-Driven Learning (DDL) is a method for learning languages that involves analyzing language usage trends and finding patterns in language data, utilizing technology and statistics. One of the key benefits of DDL is that it allows students to focus on the most relevant and useful language data for their needs. Data-driven learning is an…