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…

Research and development of Learning Analytics (LA) have created new ways to support students' learning. However, our understanding of teachers' roles when implementing LA in classroom practices remains nascent. This study investigates how teachers can implement LA to support students' agency in directing their own inquiry, when engaging in a…

The rapid rise of information technology has popularized learning diagnostic systems in education, particularly in college English teaching. These systems boost teaching quality and enable precise instruction. This study delves into precision teaching in college English with two English major classes. Teaching experiments used data from the system…

The global expansion of online language courses is on the rise, offering greater flexibility in the approaches to learning design. This study delves into the exploration of the fundamental learning design patterns within a K-12 synchronous language course. Leveraging a rich array of textual data, including syllabi, textbooks, course outlines,…

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 edited volume explores institutional responses, equity in open education, and the future of higher education in a post-pandemic world, offering valuable insights into effective pedagogical practices and policy recommendations to sustain the advancements made during the pandemic. Through providing a concise overview of the collective insights…

Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…

Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…

In this study, we held a 12-hour workshop focused on training the Data-Driven Learning (DDL) approach for in-service Chinese teachers aiming to implement this pedagogy in Mandarin Chinese classrooms in the future. We analyzed data from a postworkshop questionnaire to understand how the individual-level traits of Chinese teachers (such as their…

This study proposed and implemented a blended self-directed learning program for English-as-a-Foreign-Language (EFL) college students beyond the classroom. Adopting a case study-mixed methods design, the study aimed to investigate (1) learners' engagement in the program, (2) the effects of the program, and (3) learners' perceptions of the…

College transfer students are those who follow a different trajectory in their higher education journeys than traditional students, completing a sub-degree before pursuing a bachelor's degree at a university. While the possibility of transferring makes higher education accessible to these students, previous studies have found that they face…

In this article we investigate the effectiveness of learning analytics for identifying at-risk students in higher education institutions using data output from an in-situ learning analytics platform. Amongst other things, the platform generates 'no-engagement' alerts if students have not engaged with any of the data sources measured for 14…

This study presents several Latin American research initiatives in the field of learning analytics (LA). The study's purpose is to enhance awareness and understanding of LA among researchers, practitioners and decision makers, and to highlight the importance of supporting research on LA. We analyzed case studies of LA research conducted at four…

In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…

How can we best facilitate students most in need of learning support, entering a challenging quantitative methods module at the start of their bachelor programme? In this empirical study into blended learning and the role of assessment for and as learning, we investigate learning processes of students with different learning profiles.…