Students using self-directed learning platforms, such as Duolingo, cannot be adequately assessed relying solely on responses to standard learning exercises due to a lack of control over learners' choices in how to utilize the platform: for example, how learners choose to sequence their studying and how much they choose to revisit old material. To…

This paper represents a summary and discussion of the three studies presented at the morning session of the Fall 2022 JALT Vocabulary SIG. The papers, which were written by Ali Al-Hoorie, Masaki Eguchi, Derek Canning, Stuart McLean, Christopher Nicklin, and Joseph Vitta, represent a range of topics and study designs that are common in recent…

The National College English Test Band 4 (CET-4) is a key test to assess the English language ability of Chinese university students, and the success rate of the test is important to improve the quality of their English learning. Artificial intelligence technology can be used to predict and explore the factors influencing the success rate. This…

One of the biggest challenges for EFL (English as Foreign Language) students to learn English is the lack of practicing environments. Although language researchers have attempted to conduct flipped classrooms to increase the practicing time in class, EFL students generally have difficulties interacting with peers and teachers in English in class.…

The purpose of this study is two-fold: 1) to investigate the effects of Data-Driven Learning (DDL) framed within the Involvement Load Hypothesis (ILH) on Thai learners' use of academic collocations and 2) to examine how Thai learners utilized the involvement load (IL) components (need, search, and evaluation) to master academic collocations. It is…

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…

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…

In today's environment of growing class sizes due to the prevalence of online and e-learning systems, providing one-to-one instruction and feedback has become a challenging task for teachers. Anyhow, the dialectical integration of instruction and assessment into a seamless and dynamic activity can provide a continuous flow of assessment…

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…

Violations of normality and homogeneity are common in educational data. When this occurs, the use of parametric statistics may be inappropriate. A generalized form of nonparametric analyses based on the Puri and Sen L statistic provides an alternative approach. Using a chi-square distribution, this technique is easy to apply and has significant…

Issues of intelligibility may arise amongst English learners when acquiring new words and phrases in North American academic settings, perhaps in part due to limited linguistic data available to the learner for understanding language use patterns. To this end, this paper examines the effects of Data-Driven Learning for Pronunciation (DDLfP) on…

This paper studies the use of Reinforcement Learning (RL) policies for optimizing the sequencing of online learning materials to students. Our approach provides an end to end pipeline for automatically deriving and evaluating robust representations of students' interactions and policies for content sequencing in online educational settings. We…

The purpose of the present study was to investigate if following data-driven learning (DDL) to raise the learners' awareness of discourse organizers through concordancing improves their comprehension of English academic lectures. To address this issue, the current study adopted a quasi-experimental (comparison group, pretest-posttest) design. 96…

Word frequency has a long history of being considered the most important predictor of word difficulty and has served as a guideline for several aspects of second language vocabulary teaching, learning, and assessment. However, recent empirical research has challenged the supremacy of frequency as a predictor of word difficulty. Accordingly,…