A workshop for hosts and presenters at online and hybrid sessions at PanSIG2022

You can test the Zoom link for F32 here. (The room camera is not switched on yet)

Meet online participants and some of the conference team.

When purchasing new graded readers for a university library, as well as making a varied collection, it is important to consider whether the books will be “popular” or “highly rated” by the students who use the library. The factors that make a book popular may be different for books that are intended to improve English skills. Therefore, using the lending history of books held by a university library, we analyze the factors that make a book popular and derive the criteria for predicting popularity in graded readers. By using these criteria, we can predict the popularity of the books we plan to purchase and so purchase the graded readers most likely to meet the needs of the library’s users. In this study, we use data extracted from an online system which stores the lending history and evaluations of graded readers in a university library, to identify the most popular graded readers and the factors related to their popularity. On the basis of these factors, we estimate an order of priority by performing statistical analysis in order to determine whether the books which the library is planning to purchase will meet the specific needs of the readers who use the library.

Extensive reading (ER) entails starting with simple books (graded readers) and gradually expanding the range of reading to include progressively more difficult books. In Japan, ER programmes often make use of “Yomiyasusa Level” (YL), which indicates a book’s difficulty performed by the subjectivity of Japanese people who have already done a lot of ER. One of the principles of ER is that learners should use the YL scale to choose books at an appropriate reading level. Even after learners have progressed from graded readers, they will still benefit from being able to choose books on the basis of YL, but relatively few non-graded readers appear in YL databases. The goal of this research is to estimate the YL of general English books to which a YL has not yet been assigned. This will also be useful for determining the YL scores of new graded readers and for checking the validity of previously assigned YL. First, we examine the parameters which contribute to YL using a corpus tool called Coh-Metrix, which quantitatively evaluates the linguistic characteristics of a text. Then, we perform a regression analysis using these parameters and estimate the YL of general English books.

When practiced correctly, Extensive Reading (ER) should enable learners to become more proficient users of a foreign language. The method is only effective, however, if learners read books of an appropriate level, i.e. books which they can enjoy reading without needing to consult a dictionary. Therefore, the Extensive Reading Foundation Placement Test (ERFPT) was developed to measure the reading level of learners. The test employs comprehension questions which have been created by teachers who have volunteered their time to help develop the test. More texts and test items will improve the test; therefore, we propose a system that automatically generates questions and so reduces the burden on those making the test items. The question generation method is based on the way that the test item maker actually creates questions for the ERFPT, in other words through a process of ‘abstraction’. We use a summary created by PEGASAS, which is a transformer model for abstractive text summarization. This presentation will investigate the suitability of this method for generating questions for ERFPT. If successful this method may be used for creation of a variety of comprehension tests beyond ER.