Language Learning System Research Articles

Listening strategy use and influential factors in Web‐based computer assisted language learning

AbstractThis study investigates second and foreign language (L2) learners' listening strategy use and factors that influence their strategy use in a Web‐based computer assisted language learning (CALL) system. A strategy inventory, a factor questionnaire and a standardized listening test were used to collect data from a group of 82 Chinese students enrolled in a required course in college English. A descriptive statistical analysis measures the frequency of these learners' use of overall strategies and strategy types. A multiple regression analysis identifies factors and their interactions that influence the learners' use of listening strategies. t‐tests examine the characteristics and proficiency levels that affect the overall listening strategies and strategy types used by these learners. The results show that cognitive and metacognitive strategies are used most frequently. They also reveal that motivation, learning anxiety and learning styles significantly affect the learners' use of various listening strategies. The results of this study provide directions for future research into the listening strategies employed in Web‐based CALL and suggest ways for strategy instruction that may improve listening comprehension for L2 learners with different characteristics in Web‐based CALL.

Designing a mobile language learning system based on lightweight learning objects

This paper investigates the possibilities in the area of application of mobile technologies for language learning. The primary goal is to design a mobile system for learning of the Japanese language with a clear separation of content and presentation, and to leverage the learners' interest in the Japanese language. Both the technical and the language learning perspectives are discussed. A reusable, lightweight model of learning objects with compact content and a reduced metadata set is presented. These objects are stored in a simple learning object repository that can deliver them to any client over the Internet. A mobile application is designed to use the learning object repository as its content provider, while defining its own method of presentation suitable for smaller screens of mobile devices. For the purpose of evaluation, an experiment was conducted within the e-learning system at the Faculty of Organizational Sciences, University of Belgrade. Research findings have indicated that the developed mobile application has a positive effect on the students' interest in the subject matter.

Comulang: towards a collaborative e-learning system that supports student group modeling

This paper describes an e-learning system that is expected to further enhance the educational process in computer-based tutoring systems by incorporating collaboration between students and work in groups. The resulting system is called “Comulang” while as a test bed for its effectiveness a multiple language learning system is used. Collaboration is supported by a user modeling module that is responsible for the initial creation of student clusters, where, as a next step, working groups of students are created. A machine learning clustering algorithm works towards group formatting, so that co-operations between students from different clusters are attained. One of the resulting system’s basic aims is to provide efficient student groups whose limitations and capabilities are well balanced.

Japanese lexical accent recognition for a CALL system by deriving classification equations with perceptual experiments

For non-native learners of Japanese, the pitch accent can be cumbersome to acquire without proper instruction. A Computer Assisted Language Learning (CALL) system could aid these learners in this acquisition provided that it can generate helpful feedback based on automatic analysis of the learner’s utterance. For this, it is necessary to consider that the characteristics of a given learner’s Japanese production will be largely influenced by his or her native tongue. For example, non-natives may produce pitch contours that natives do not produce. A standard approach to carry out recognition for error detection is to use a machine learning algorithm making use of an array composed of a variety of features. However, a method motivated by perceptual analysis may be better for a CALL system. With such a method, it should be possible to better understand the human recognition process and the causal relationships between contour and perception, which could be useful for feedback. Also, since accent recognition is a perceptual process, it may be possible to improve automatic recognition for non-native speech with such a method. Thus, we carry out listening tests making use of experiments using resynthesized speech to construct a method. First, we inspect which variables the probability of a pitch level transition is dependent on, and from this inspection, derive equations to calculate the probability at the disyllable level. Then, to recognize the word-level pattern, the location of each transition was determined from the probabilities for each two syllable pair. This method makes it possible to recognize all pitch patterns and to give more in-depth feedback. We conduct recognition experiments using these functions and achieve results that performed comparably to the inter-labeler agreement rate and outperformed SVM-based methods for non-native speech.

The nature of the semantic scale: Evidence from sign language research

Author(s): Zaremba, Kathryn Davidson | Abstract: A difficult learning problem for both children and artificial language learning systems is knowing what is intended to be conveyed based on what is literally said. For example, adults usually take Some teas contain caffeine to also convey that Not all teas contain caffeine, an inference known as a scalar implicature. The present work investigates the role of language-specific knowledge in such inferences through three studies on scalar implicatures in American Sign Language (ASL). The first study illustrates a new experimental paradigm and compares prototypical scalar implicatures in ASL and English. The second study includes the first investigation of general use coordinators in ASL that can be interpreted as either conjunction (and) or disjunction (or). This provides a test case for the role of language-specific lexical contrast in scalar implicatures, with results showing that lexically non-contrastive scales (i.e., lexical scales whose items differ in meaning but not in form) trigger less scalar implicatures than prototypical lexically contrastive scales, which are based on contrasting lexical items. In the third study, both lexically contrastive and non-contrastive scales are interpreted by deaf native signers and also deaf signers who learned ASL at later ages. Result show that later ASL learners calculated less implicatures than early learning signers, but only on the lexically contrastive scale. Together, these studies support a view that despite their context dependence, scalar implicatures are most likely to be triggered by lexical items which contrast with each other in form to create a context-independent scale, and that there may even be advantages to learning scales early in life. The dissertation concludes with suggestions for incorporating lexical contrast into theories of implicature and for further study of the semantic/ pragmatic interface in sign languages

Non-native perception and learning of the phonemic length contrast in spoken Japanese: training Korean listeners using words with geminate and singleton phonemes

To establish an effective training paradigm for a computer-assisted language learning system that enables non-native learners to exploit native-like perceptual cues for identifying length contrasts, e.g., consonant length, in the Japanese language (hereafter, Japanese length contrast), two experiments were conducted to investigate the identification accuracies of native Korean listeners before and after intensive perceptual training. The first experiment assessed the perceptual characteristics that native Korean listeners show when identifying the length contrast in the face of variation in speaking rate. The results suggested that native Korean listeners identify length contrasts by relying on a fixed-length criterion instead of adapting to changes in speaking rate. Also, Korean listeners showed a noticeable bias toward geminate responses for all speaking rates, with a stronger bias for slower speaking rates. The second experiment was based on these perceptual characteristics of Korean listeners. It investigated the extent to which intensive training helps improve listeners’ ability to identify Japanese length contrast and to examine whether greater stimulus variability during training leads to more robust training effects. The overall results showed that the perceptual training improved Korean listeners’ ability to perceive consonant length contrast. Moreover, misidentification of geminates decreased at post-test. However, the effect of training did not differ greatly between conditions of high stimulus variability during training (training with three speaking rates) and low stimulus variability (training with a single speaking rate). Training also did not generalize to perception of untrained contrast type (vowel length contrast). These results suggest that while perceptual training helps Korean learners learn a new, difficult-to-learn L2 phonemic length contrast, it is still difficult for learners to acquire native-like perceptual criteria.

BAHASA DAN KETIMPANGAN GENDER

Gender inequality not only shows up in the legal, social or purely political, but also gender discrimination in the field of human language which can automatically give birth to living systems which tend to marginalization of women. Gender inequality is in the field of linguistics partly contained in, the assumption of women’s language, mastery of the language gap between men and women, texts and language learning systems, and poor language skills and logic.

Computer-assisted language learning (CALL) in support of (re)-learning native languages: the case of Runyakitara

This study presents the results from a computer-assisted language learning (CALL) system of Runyakitara (RU_CALL). The major objective was to provide an electronic language learning environment that can enable learners with mother tongue deficiencies to enhance their knowledge of grammar and acquire writing skills in Runyakitara. The system currently focuses on nouns and employs natural language processing in order to generate a large base of exercise material without extensive tuning by teachers. Language learners used the system over 10 sessions and their improvements were charted. Besides this empirical evaluation, we also sought the opinions of Runyakitara experts about the system (as a judgmental evaluation). Results from the evaluation study indicate that RU_CALL has the ability to assess users’ knowledge of Runyakitara and to enhance grammar and writing skills in the language. This computational resource can be utilized by other interested learners of Runyakitara, and the idea can be extended to other indigenous languages with emigrant populations who wish to maintain their language skills.

Mastering Overdetection and Underdetection in Learner-Answer Processing

This paper presents a "didactic triangulation" strategy to cope with the problem of reliability of NLP applications for computer-assisted language learning (CALL) systems. It is based on the implementation of basic but well mastered NLP techniques and puts the emphasis on an adapted gearing between computable linguistic clues and didactic features of the evaluated activities. We claim that a correct balance between false positives (i.e., false error detection) and false negatives (i.e., undetected errors) is not only an outcome of NLP techniques, but also of an appropriate didactic integration of what NLP can do well--and what it cannot do well. Based on this approach, ExoGen is a prototype for generating activities such as gap-fill exercises. It integrates a module for error detection and description which checks learners' answers against expected ones. Through the analysis of graphic, orthographic, and morphosyntactic differences, it is able to diagnose problems like spelling errors, lexical mix-ups, agreement errors, conjugation errors, and so on. The first evaluation of ExoGen outputs, based on the FRIDA learner corpus, has yielded very promising results, paving the way for the development of an efficient and general model adaptable to a wide variety of activities.

Analysis of and Feedback for Free-Form Answers in English and Romanized Japanese

This paper describes a powerful answer analysis system which solves the difficult problems of recognizing student reproductions of spoken Japanese sentences. It allows all reasonable Roman spellings of Japanese words, while at the same time detecting mishearings, and distinguishing between important and unimportant spacing errors. The system can handle combinations of these errors while detecting incorrect word orders and missing sentence parts, and determining the semantic category into which the student answer falls. For each Computer Assisted Language Learning (CALL) system it is used with, the specification of answer categories and requests for error checks are contained in a database separate from the program. The system has been used successfully for answer analysis in listening comprehension exercises.

DaRT: A CALL System to Help Students Practice and Develop Reasoning Skills in Choosing English Articles

DaRT is a Computer Assisted Language Learning (CALL) system for helping English as a Second/Foreign Language students master English articles. The system uses a diagrammatic reasoning tool described in previous studies (Yoshii, 1997, 1998) to present communicative contexts for exercises in choosing appropriate articles. These diagrams make explicit the "intent-assumption" factors involved in article choice for many situations and permit students and teachers to discuss these factors without relying on English language explanations which depend on concepts foreign to most Asian students. DaRT can generate numerous exercise sentences, provide help based on student interactions, and choose the next exercise based on student performance. DaRT functions, therefore, as a tutorial to help students acquire the skills necessary for analyzing and applying the "intent-assumption" factors in choosing English articles. This article describes the major stages of the project, provides details of the system components, and concludes with the results of an evaluation of the system by Japanese students.

Error Analysis in Japanese Writing and Its Implementation in a Computer Assisted Language Learning System on the World Wide Web

This article deals with the implementation of error analysis for a Computer Assisted Language Learning (CALL) program using Natural Language Processing (NLP) techniques. This program can be used for learning the passive voice in Japanese on any World Wide Web (WWW) browser. To estimate the range of possible types of errors in Japanese passive constructions, a survey of errors made by foreign students was conducted. The software uses standard NLP tools such as morpheme and syntax analyzers, plus newly developed error analysis and feedback processing components. The program enables learners to type in sentences freely, detects their errors, and displays appropriate feedback messages to guide learners to correct their errors themselves. Evaluation of the program showed that it can obtain a high degree of accuracy and instructional effectiveness.

Integration of Situated Learning and Context Awareness System for Learning Basic Chinese

Chinese has become the world’s strongest language, and that has also set off a learning trend. It is critical to know how to improve teaching methods and strategies to effectively help non-native speakers to overcome the language barrier. With the Internet’s and e-Learning’s popularity, learning technologies have led both learning activities and the environment into a multi-dimensional world. Recently a new trend has emerged, called context-aware technology, for developing a ubiquitous learning environment with features that emphasize real life learning situations and problem solving practices. This study has integrated situated learning strategies and context awareness technology to develop a basic Chinese language learning system for exchange students at a large university in northern Taiwan. The pilot test results show that these students are highly satisfied with the system and their learning attitude was also positive, while using this system.

Using Learning Analytics to Understand the Design of an Intelligent Language Tutor – Chatbot Lucy

the goal of this article is to explore how learning analytics can be used to predict and advise the design of an intelligent language tutor, chatbot Lucy. With its focus on using student-produced data to understand the design of Lucy to assist English language learning, this research can be a valuable component for language-learning designers to improve second language acquisition. In this article, we present students’ learning journey and data trails, the chatting log architecture and resultant applications to the design of language learning systems.

Japanese Learning Support Systems: Hinoki Project Report

In this report, we introduce the Hinoki project, which set out to develop web-based Computer-Assisted Language Learning (CALL) systems for Japanese language learners more than a decade ago. Utilizing Natural Language Processing technologies and other linguistic resources, the project has come to encompass three systems, two corpora and many other resources. Beginning with the reading assistance system Asunaro, we describe the construction of Asunaro's multilingual dictionary and it's dependency grammar-based approach to reading assistance. The second system, Natsume, is a writing assistance system that uses large-scale corpora to provide an easy to use collocation search feature that is interesting for it's inclusion of the concept of genre. The final system, Nutmeg, is an extension of Natsume and the Natane learner corpus. It provides automatic correction of learners errors in compositions by using Natsume for its large corpus and genre-aware collocation data and Natane for its data on learner errors.

자동 추출된 지식에 기반한 한국어 학습 지원 시스템

Computer aided language learning has become popular. But the level of automation of constructing a Korean learning assistant system is not so high because a practical language learning system needs large scale knowledge resources, which is very hard to acquire. In this paper, we propose a Korean learning assistant system that utilizes easily obtainable knowledge resources like a corpus, web documents and a lexicon. Our system has three modules - problem solving, pronunciation marker and writing assistant. Automatic problem generator uses a corpus and a lexicon to make problems with one correct answer and three distracters, then verifies their suitability by utilizing frequency information from web documents. We analyze pronunciation rules for a pronunciation marker and recommend appropriate words and sentences in real-time by using data extracted from a corpus. In experiment, we evaluate 400 automatically generated problems, which show 89.9% problem suitability and 64.9% example suitability.

What can Head‐Final Languages Tell us about Syntactic Priming (and vice versa)?

AbstractSyntactic priming, a phenomenon that previous exposure to a particular syntactic structure makes the structure more accessible in subsequent utterances, has widely been observed in both language production and comprehension. Previous research using this paradigm revealed a great deal about processing and representations of syntactic structures. Based on previous findings, it is recently proposed that priming plays a central role in the language processing and learning system. Such a claim often presumes that syntactic priming occurs in the same way across languages. Increasing evidence demonstrates priming in many different languages but what is challenging is to establish that syntactic priming is underlain by the same mechanism across languages. Perhaps the strongest test of such a common mechanism account is to examine the phenomenon in languages that are typologically different from English and other Germanic languages on which the majority of previous studies were conducted. To address this issue, this article reviews the previous studies conducted in head‐final languages. Finding that syntactic priming occurs in a similar way between head‐final languages and head‐initial languages would provide strong support to the common mechanism of priming across languages. Although evidence is still limited, previous studies support that syntactic priming occurs in head‐final languages in a similar way and possibly by the same mechanism as in head‐initial languages. I also discuss implications of the results of those studies for the syntactic representations and processing in head‐final languages.

Discriminative Training for Native Chinese Speakers' Pronunciation Proficiency Evaluation

Most computer assisted language learning (CALL) systems use acoustic models trained by MLE (Maximum Likelihood Estimation) for pronunciation proficiency evaluation. However, MLE ignores information of other phones during training stage and cant distinguish confusing phones well. This paper introduced discriminative measures of minimum phone/word error to refine acoustic models to deal with the problem. This paper analyzed discriminative trained acoustic models on Putonghua proficiency test in detail and found that: 1) They are much more distinguishable than MLE ones; 2) Even though the training and test are mismatch, they still perform significantly better than MLE-trained models under the same phone boundaries. The final system performance has approximately 4.5% relative improvement.

Towards new roles for learners and teachers in a language learning system?

In a flexible language learning system, developed at a French university and gradually improved through Action Research, different elements are combined: individual work on a virtual learning environment (VLE), pair-work and counselling appointments. One of the objectives of the system is to help the students involved progress towards autonomy – defined as “the ability to take charge of one’s own learning” (Holec 1981: 3) or “as the capacity to take control over one’s own learning” (Benson 2001: 2) – in their learning of English. The implementation of the system involves a new conception of the different actors’ roles. Teachers become tutors, or counsellors, as defined by CRAPEL (Gremmo, 1995; Ciekanski, 2005) with new specific pedagogical goals (Bertin, Gravé & Narcy-Combes, 2010) and the learners have a new role to play. The introduction of two new guidance tools over the last years – a logbook, and specific sections in the existing forum of the VLE – were meant to help the students develop a reflexive approach and thus enhance autonomization, or developing learners’ capacity to learn (Holec 1990: 77), and, in a second time, to promote the development of collaborative learning strategies and encourage the students to use strategies which they would not primarily have thought of. The guidance tools used in this specific language learning environment such as the counselling appointments, the logbook, and the forum, may influence the roles played by the different actors, but also the representations they have of their own roles, which may have an impact on their motivation and thus on the autonomization process (Dickinson, 1995). From the creation of the flexible system five years ago, the research has studied a population of 610 students through quantitative and qualitative analyses (Chateau, 2008; Chateau & Zumbihl, 2010). Focusing on the results obtained with the last population of students, the paper discusses the differences between them and the previous populations, and in particular whether the evolution of the roles played by the different actors, as compared with traditional language teaching/learning situations, has been enhanced.

Learners' perceptions of the pedagogical relations in a flexible language learning system

The flexible language learning system we have devised at our university combines different elements: individual work on a virtual learning environment, pair-work and counseling sessions. The implementation of the system involves a new conception of the different “actors’’ roles. Teachers become tutors or counselors with new specific pedagogical goals, and learners have a new role to play too. From the creation of the system five years ago, our research has studied a cohort of 610 students. The article focuses on the last two cohorts of students, for whom two important changes in the guidance elements present in the system were introduced. It discusses students’ perceptions of the roles played by the different actors in the system, as compared with traditional language teaching/learning situations. Possible implications for future cohorts of students at our university, as well as for other students working in learning systems of the same kind, are drawn.