This first goal of the study described here was to investigate the effectiveness of three types of vocabulary annotations on vocabulary learning for EFL college students in Taiwan: text annotation only, text plus picture, and text plus picture and sound. The second goal of the study was to determine whether learners with certain perceptual learning styles benefited more from a particular type of vocabulary annotations. The perceptual learning styles investigated were auditory, visual-verbal (with text), visualnonverbal (with pictures), and mixed preferences. The results of the study showed that the version with text plus picture was the most effective type of vocabulary annotation. Perceptual learning styles did not seem to have a significant influence on the effectiveness of vocabulary annotations.

Recently, a promising topic in computer-assisted language learning is the application of Automatic Speech Recognition (ASR) technology for assisting learners to engage in meaningful speech interactions. Simulated real-life conversation supported by the application of ASR has been suggested as helpful for speaking. In this study, a web-based conversation environment called CandleTalk, which allows learners to seemingly talk with the computer, was developed to help EFL learners receive explicit speech acts training that leads to better oral competence. CandleTalk is equipped with an ASR engine that judges whether learners provide appropriate input. Six speech acts are presented as the foci of the materials with local cultural information incorporated as the content of the dialogues to enhance student motivation. The materials were put to use on 29 English major and 20 nonEnglish major students in order to investigate their learning outcome and perception in an EFL context. Oral proficiency assessment using the format of the Discourse Completion Test (DCT) given before and after the use of CandleTalk and an evaluation questionnaire were two instruments used for data collection. The results of the study showed that the application of ASR was helpful for the college freshmen in the teaching of speech acts, particularly for the non-English major students. Most learners perceived positively toward the instruction supported with speech recognition.

No abstract

This paper describes the development of an innovative web-based environment for English language learning with advanced data-driven and statistical approaches. The project uses various corpora, including a Chinese-English parallel corpus (Sinorama) and various natural language processing (NLP) tools to construct effective English learning tasks for college learners with adaptive computational scaffolding. It integrates the expertise of a group of researchers in four areas: (a) advances in NLP technologies and applications, (b) construction of a self-access reading environment, (c) exploration of English language learning through written exercises and translations, and (d) use of bilingual corpora for culture-based English learning. In this paper, the conceptualization of the system and its various reference tools (e.g., a bilingual concordancer) for English learning and pilot testing on various modules (e.g., a reading module, Text Grader, and Collocation Practice) are reported.

No abstract