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This master thesis focuses on an exploration of digital technologies and systems used for learning interaction, specifically learning of foreign languages (FLA) and second languages acquisition (SLA) and investigates the use of autonomy-based virtual environment systems for knowledge acquisition. The study describes an enhancement of multimodal language learning practices and deployment of teaching material in an autonomous setup operated by language students. The master thesis project culminated with the creation of a language learning virtual reality system called "VR wor(l)ds" supporting oral training and vocabulary acquisition in a contextual learning environment. The VR system is intended to compensate for the loss of equal opportunities among students interacting in the traditional classroom setup. Furthermore, this concept aims to explore new opportunities for knowledge acquisition and opens up an argument for using virtual reality systems for encouraging students to actively engage with oral training and vocabulary acquisition in their language learning process. Last but not least, this project aims to open up a cross discussion between the field of interaction design (IxD) and language learning for possible collaboration on solutions to create playful environments for learning and improve learning outcomes.

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京都大学 / 新制・課程博士 / 博士(人間・環境学) / 甲第25379号 / 人博第1121号 / 新制||人||261(附属図書館) / 京都大学大学院人間・環境学研究科共生人間学専攻 / (主査)准教授 PETERSONMark, 准教授 中森 誉之, 教授 勝又 直也, 教授 Harrison Richard / 学位規則第4条第1項該当 / Doctor of Human and Environmental Studies / Kyoto University / DFAM

Master of Arts / Department of Modern Languages / Douglas K. Benson / This thesis answers the questions: How should the terms interaction, individualization, and personalization be applied to Computer Aided Language Learning (CALL) software? What progress has been made in their implementation? How can CALL software developers better incorporate them in the future? For each of the three terms, I explain how it is applicable to the CALL software environment by defining it, describing the pedagogical research supporting it, and then giving general guidelines for incorporating it into a CALL software program. I measure the progress of the implementation of the three terms in CALL software through compiling and analyzing data from reviews of 44 software titles. The publication dates of the software titles are from 1981 to 2008. I propose through description and a proof-of-concept software program ways to improve the incorporation of the terms in question into CALL software. As a result of answering the three questions, this thesis shows that the current accepted definitions and ways of implementing interaction, individualization, and personalization need to be improved in order to comply with pedagogical research and make full use of current technology. The general guidelines given in the explanation of each term relative to CALL and the attributes under each term in the analysis of the compilation data provide examples of areas on which to focus development. Additionally, I specifically comment on pedagogically supported attributes within each term that have a weak representation in the software compilation and therefore need more development. In addition, this thesis is accompanied by “Mis vacaciones”, a proof-of-concept software program, which demonstrates ways to improve the incorporation of interaction, individualization, and personalization into CALL software. In “Mis vacaciones”, the learner takes a virtual trip to Nuevo Leon, Nicaragua. The multimedia sent to the learner by a previous traveler shows Nicaraguan city people and the La Gigatona festival. After visiting, the learner is asked to describe the Nicaraguans that they saw. If the learner needs help, Structured Input activities lead the learner to develop the third person singular imperfect form. Buttons in the software environment provide access to internet sources. The learner is able to draw and take photos to create a visual prop to aid in the description task.

abstract: Much evidence has shown that first language (L1) plays an important role in the formation of L2 phonological system during second language (L2) learning process. This combines with the fact that different L1s have distinct phonological patterns to indicate the diverse L2 speech learning outcomes for speakers from different L1 backgrounds. This dissertation hypothesizes that phonological distances between accented speech and speakers' L1 speech are also correlated with perceived accentedness, and the correlations are negative for some phonological properties. Moreover, contrastive phonological distinctions between L1s and L2 will manifest themselves in the accented speech produced by speaker from these L1s. To test the hypotheses, this study comes up with a computational model to analyze the accented speech properties in both segmental (short-term speech measurements on short-segment or phoneme level) and suprasegmental (long-term speech measurements on word, long-segment, or sentence level) feature space. The benefit of using a computational model is that it enables quantitative analysis of L1's effect on accent in terms of different phonological properties. The core parts of this computational model are feature extraction schemes to extract pronunciation and prosody representation of accented speech based on existing techniques in speech processing field. Correlation analysis on both segmental and suprasegmental feature space is conducted to look into the relationship between acoustic measurements related to L1s and perceived accentedness across several L1s. Multiple regression analysis is employed to investigate how the L1's effect impacts the perception of foreign accent, and how accented speech produced by speakers from different L1s behaves distinctly on segmental and suprasegmental feature spaces. Results unveil the potential application of the methodology in this study to provide quantitative analysis of accented speech, and extend current studies in L2 speech learning theory to large scale. Practically, this study further shows that the computational model proposed in this study can benefit automatic accentedness evaluation system by adding features related to speakers' L1s. / Dissertation/Thesis / Doctoral Dissertation Speech and Hearing Science 2018

本研究針對我國學生學習日語發音進行相似度指標發展之初探，貢獻為針對目前日語發音提供一個相似度的指標可以和老師語音進行比較分析，找出分析日語發音相似度之模式。 研究從聲音數位化的角度切入，有別於過去研究使用語音辨識的方式來進行，聲音數位化後為數值的方式，因此使用指標來計算相似的程度。研究提出一套對應的聲音相似度指標，以電腦分析輔助日語學習者的發音練習。 指標建立過程由聲音取樣、正規化、端點偵測，到實際的運算，使用所蒐集的聲音資料來測試指標的穩定度與有效性，研究結果說明在以日語為母語者間的指標都很靠近，而不同日語腔調間會有一定的指標差異，對於一定日語程度的對象而言，指標落點很靠近，惟本研究此次蒐集到的聲音資料，其應用指標運算結果的分佈太過集中，如果能有更多樣化的聲音資料來測試指標應能有較漂亮的分佈圖形。 / This research includes developing a similarity index applies to the evaluation of Taiwan students learning Japanese pronunciation. The contribution of this research is that it provides a similarity index to the Japanese pronunciation comparing to the teacher’s pronunciation, finding the model of how to analysis the similarity of Japanese pronunciation. This research uses the digital audio processing to begin with, which is different from the other research that uses the speech recognition to evaluate the pronunciation. The audio will turn into numerical format after digitalize, so this research uses an index to calculate the similarity. By using this similarity index, the computer can become an assistant role that helps to analysis while learning Japanese pronunciation. The developing of index starts from audio sampling, audio normalizing, and end-point detection to the calculation of similarity index. This research collects audio data to test the stability and the validity of the similarity index. The result indicates that the similarity index of native Japanese speakers is very close；and the similarity index contains certain difference between different accents. For those Taiwan students who qualify with Japanese, their similarity index is close. Nevertheless, the result of the similarity index is too centralized, it would be better if there are more audio data to test the similarity index.

Computer assisted language learning (CALL) comprises a wide range of information technologies that aim to broaden the context of teaching by getting advantages of IT. For example, a few efforts have been put on including a combination of voice and its visual representation for language learning, and some studies are reporting positive outcomes. However, more research is needed in order to assess the impact caused by specific visualization styles such as: highlighting syllables and/or wave of sound. In order to explore this issue, we focused at measuring the potential impact that two distinct visualization styles and its combination can have on teaching children the pronunciation of English as a second language. We built a prototype which was designed to assist students while learning pronunciation of syllables. This system was employing two different real-time interactive visualization styles. One of these visualization styles utilizes audio capturing and processing, using a recent technology development: Web Audio API.We evaluated the effect of our prototype with an experiment with children aged from 9 to 11years old. We followed an experimental approach with a control group and three experimental groups. We tested our hypothesis that states that the use of a combined visualization style can have greater impact at learning pronunciation in comparison with traditional learning approach.Initial descriptive analyses were suggesting promising results for the group that used the combined visualization prototype. However, additional statistical analyses were carried out in order to measure the effect of prototype as accurately as possible within the constraints of our study. Further analyses provided evidence that our combined visualizations prototype has positively affected the learning of pronunciation. Nonetheless, the difference was not big comparing to the system that employed only wave of sound visualization. Ability to perceive visual information differs among individuals. Therefore, further research with different sample division is needed to determine whether is the combination of visualizations that does the effect, or is the wave in itself. Slitting groups based on this characteristic and perform the testing will be considered for the future research.Eventually, we can be confident to continue exploring further the possibility of integrating our proposed combination of two visualization styles in teaching practices of second language learning, due to positive outcomes that our current research outlined. In addition, from a technological perspective, our work is at the forefront of exploring the use of tools such as Web Audio API for CALL.