The aim of this workshop is to equip EFL teachers with the knowledge and skills necessary to write branching narratives for extensive reading activities using artificial intelligence (AI). The workshop will begin by providing an overview of what branching narratives are and how they can enhance the reading experience of EFL learners. Participants will then learn about the principles behind an AI-trained language model and how it can be used to generate coherent and engaging storylines. The workshop will guide participants through the process of creating their own branching narratives using an AI-trained language model, providing step-by-step instructions and practical tips. By the end of the workshop, participants will have a greater understanding of how to use an AI-trained language model to create immersive and engaging reading experiences for their students.

Recent developments in AI chat are sending shockwaves through the language teaching community, both with short-term challenges of instructing students when and how to use this technology and as a longer-term existential threat to the teaching vocation. On the other hand, this same technology presents an opportunity for the automatic production of compelling input, not only in English but potentially for many other languages. Critical to providing suitable input is determining the level of readability, for example measured in YL (Yomiyasusa Level), which is based on impressions of difficulty by readers in Japan. This presentation reports on research into machine learning techniques used to estimate YL using the Coh-metrix analysis tool, Lasso linear regression and grid search cross-validation. The model predicted YL with a strong correlation of .91, significantly better than the Flesch Reading index. The results suggest that the developed model is a promising tool for predicting YL.

Reports and arguments supporting positive effects of ER tend to highlight gains in reading speed, but the research base on how reading speed improves among L2 readers, both in general and among those that undergo ER activities, is still limited. This presentation reports on an explorative efforts to identify reader variables associated with reading speed gains among participants in an EFL reading course at a Japanese university (n=24). The two-semester course aimed to improve the students’ reading speed and other skills, and utilised an online ER platform, which recorded student access and activity logs and, among other things, produced reading speed estimates for each e-book they completed reading. Employing a data-mining approach, the presenter compared the students’ reading speeds at the outset and end of the course, and looked for variables linked to speed gains. Findings and their implications are shared at the presentation.

This case study explores the affordances of a digital reading platform, XReading, in helping Jasmine excel in reading. Jasmine is a freshman at a state university in Malang. The department where she studies, offered Extensive Reading (ER) course as a compulsory part of the curriculum in the first semester. During the 16-week ER course, Jasmine read more than 1,000,000,- words from the website. The initial target for the 2022 cohorts was 120,000 words in a semester. Thus, it is important to understand why Jasmine read more than the expected target words and what had her kept going. A semi-structured interview was done with Jasmine after the class ended. The findings of the present study help teachers of Extensive Reading (ER) programs to shape their classes in such a way that encourage learner autonomy. This presentation also shows how reading in an electronic age affects students’ motivation in a positive manner.

Extensive Reading (ER) is considered one of the more effective ways to develop reading skills among students as they are exposed to large amounts of meaningful input that is selected by them. The purpose of this study was to investigate students' learning experience, interest, and preference relating to the implementation of a virtual library (VL) within an academic English program. The implementation of the VL was primarily to promote and monitor the ER habits of students. The study involved first-year (N = 137) female students from a university in Japan with an average CEFR scale range of B1 – B2. Participants completed an online survey in the final quarter of the 2022 academic year after actively using the VL for a period of two quarters (14 weeks). The implications of this study’s preliminary findings and the related dynamics regarding the implementation of a VL, more specifically X-Reading (www.xreading.com) will be discussed.

With the development of Gutenberg's printing technology, the number of publications increased in large numbers, and the purpose of reading and the way of reading diversified. Then, with the advent and development of digital technology such as computers, not only paper books but also digital books have increased. In the meantime, the way of reading has become more diverse. Among several reading methods, extensive reading (ER) is still a useful method, but in some cases, it needs to be used properly with other reading methods in the era of big data. Among other types of reading, there is distant reading (DR). DR is a term coined by Franco Moretti, an Italian literary scholar, to describe a methodology of literary analysis that involves the quantitative analysis of large amounts of literary texts. In this presentation, we would like to introduce a teaching method that can properly combine ER and DR for literary texts. For DR, beginner-level computer coding activities are covered in this presentation. The programming language for DR is R. R is well-liked and widely used among professionals who work with data, particularly those who specialize in data science. In this presentation, we also introduce a checklist and materials for the ER-DR classes.

Over the past three years, students hired as “Community Literacy Activists” (CLAs) worked to write graded, young adult multicultural stories based in various Asian countries in both English and Japanese. The processes involved students writing original stories, simplifying them and translating them between English and Japanese. An illustrator team completed illustrations and a team of voice actors created the audio books. Students tagged their work records with project tags. Another team of CLAs were tasked to use Chat GPT and other AI tools to create similar stories for other country settings. Similar tags were used to track the time and cost of creating stories with AI. In the spring of 2023, we hosted an event where university students (including CLAs) were invited to use Chat GPT and other AI tools to create similar stories for other country settings. AI prompts and tools were recorded in the process of creating stories with AI and similar tags were used to track the time on different tasks. CLAs who experienced both human and AI processes were invited to participate in a recorded focus group. The results of this comparison will be the focus of the poster, with Implications drawn for student-authored graded readers, both with and without AI assistance.

English has become one of the most popular languages worldwide. However, many students, especially those who are not English majors, face significant challenges when it comes to reading and comprehension. These challenges may include limited vocabulary, grammatical difficulties, and ineffective learning strategies. As a result, the motivation to improve reading skills among students is often low. Nevertheless, the importance of reading skills cannot be overstated, as they are essential for future career success and personal growth. To address this issue, the researcher plans to use Facebook as an extensive reading tool to increase the reading motivation of non-English major college students. This innovative approach takes advantage of the unprecedented development of social networking applications. The study will employ method triangulation to collect data, including interviews and document analysis of portfolios from 40 to 45 students in two English classes next semester. The findings of this research are expected to gradually facilitate students' reading learning in classes and serve as a reference for other ESL or EFL lecturers to conduct further in-depth research.