非英語母語話者のためのインタラクティブな書き換え

Tohoku University博士（情報科学）thesi

Machine Scoring of Student Essays: Truth and Consequences

The current trend toward machine-scoring of student work, Ericsson and Haswell argue, has created an emerging issue with implications for higher education across the disciplines, but with particular importance for those in English departments and in administration. The academic community has been silent on the issue—some would say excluded from it—while the commercial entities who develop essay-scoring software have been very active. Machine Scoring of Student Essays is the first volume to seriously consider the educational mechanisms and consequences of this trend, and it offers important discussions from some of the leading scholars in writing assessment.https://digitalcommons.usu.edu/usupress_pubs/1138/thumbnail.jp

Investigating language corpora as a grammar development resource

The digital era has brought new concepts and transformations into language development and has given rise to technology-based approaches to learner autonomy. It has shifted the focus from deductive to inductive learning, where the concept of ‘noticing’ (Schmidt, 1990) language forms is promoted. Literature suggests that this type of student-centered self-discovery of lexico-grammatical patterns can be greatly aided by corpus linguistics methods, specifically ‘Data-Driven Learning’ (DDL) (Johns, 1986; Braun, 2005; O’Keeffe et al, 2007). It reports on the valuable potential of DDL for developing learners’ multi-literacies and cognitive strategies, particularly raising their awareness of lexico-grammatical patterning (O’Keeffe and Farr, 2003). However, insights from corpus-based studies have not been widely applied in teaching practices (Reppen, 2022; Zareva, 2017). It has also been proposed that DDL enhances accurate representation of language, raises cultural understanding, provides learners with the freedom to explore and discover the language, and fosters learner autonomy, thus making them more effective language learners (Flowerdew, 2015). This affordance led to the design of a longitudinal experimental study which aimed to provide useful skills and processes in the use of language corpora as a grammar development resource in the pre-intermediate EFL classroom in an Armenain context outside of higher education. The evaluation data included pre-, post-, progress-, delayed post-test data, and Learner Autonomy Profile (LAP) form, the statistical analysis of which revealed the beneficial impact of the computer-based inductive approach of DDL on the learners’ grammar competency, independent learning skills, as well as the contribution of cognitive strategies to proceduralization of knowledge. It also included semi-structured interview data, which uncovered the learners’ increased engagement in the learning process, the positive change in their attitudes towards their own learning, and the ways of demonstrating autonomous abilities in working with concordances. These data also brought to light some of the fears and challenges of using DDL, as well discussing its theoretical and pedagogical underpinnings aligned with psychological processes of learning. The findings will serve all the participants of this hugely important ELT sector - researchers, language educators and learners. They will gain insights as to what is necessary to tap learners’ implicit long-term knowledge, to prepare them both psychologically and practically for independence so that they can be armed with confidence, interest in discovering the language, knowledge about their own learning, and understanding of how to make use of their learning styles and strategies. Keywords: conventional/technology-enhanced EFL classroom, corpus linguistics, data-driven learning (DDL), inductive/deductive grammar learning, direct/indirect written feedback, explicit/implicit knowledge, language awareness, learner autonomy.N

Empirical modelling of translation and interpreting

"Empirical research is carried out in a cyclic way: approaching a research area bottom-up, data lead to interpretations and ideally to the abstraction of laws, on the basis of which a theory can be derived. Deductive research is based on a theory, on the basis of which hypotheses can be formulated and tested against the background of empirical data. Looking at the state-of-the-art in translation studies, either theories as well as models are designed or empirical data are collected and interpreted. However, the final step is still lacking: so far, empirical data has not lead to the formulation of theories or models, whereas existing theories and models have not yet been comprehensively tested with empirical methods. This publication addresses these issues from several perspectives: multi-method product- as well as process-based research may gain insights into translation as well as interpreting phenomena. These phenomena may include cognitive and organizational processes, procedures and strategies, competence and performance, translation properties and universals, etc. Empirical findings about the deeper structures of translation and interpreting will reduce the gap between translation and interpreting practice and model and theory building. Furthermore, the availability of more large-scale empirical testing triggers the development of models and theories concerning translation and interpreting phenomena and behavior based on quantifiable, replicable and transparent data.

Linguistic complexity of arabic language: a semantic analysis of antonymous homonyms in the holy Qur'ān

Homonymy, is one of the two main sub-divisions of lexical ambiguity that represents the complex nature of form and context of the Qur'anic Arabic which presents a challenge in the translation process. Since Qur'anic discourse abounds with homonymic expressions whose meaning is derived from the context, the translators of the Qur'an should undertake a demanding task decoding the intended meanings. The present paper aims at clarifying some linguistic complexities in some verses of the Qur'ān which may pose difficulty to translators of the holy book most especially those who are not familiar with antonymous homonyms in Arabic language. The reason is that antonymous homonyms are special features of the Qurʾanic Arabic language. It may be viewed as one of the stylistic feature of the Qur'an. Therefore, classification of these linguistic complexity is offered and the samples of these classifications from the Holy Qur'ān are mentioned in relation to antonymous homonyms. Samples of translated Qur'an are compared in order to ascertain the qualities of translations and English translation strategies of the stated verses

Proceedings of the 17th Annual Conference of the European Association for Machine Translation

Proceedings of the 17th Annual Conference of the European Association for Machine Translation (EAMT

Modeling second language learners' interlanguage and its variability: a computer-based dynamic assessment approach to distinguishing between errors and mistakes

Despite a long history, interlanguage variability research is a debatable topic as most paradigms do not distinguish between competence and performance. While interlanguage performance has been proven to be variable, determining whether interlanguage competence is exposed to random and/or systematic variations is complex, given the fact that distinction between competence-dependent errors and performance-related mistakes should be established to best represent the interlanguage competence. This thesis suggests a dynamic assessment model grounded in sociocultural theory to distinguish between errors and mistakes in texts written by learners of French, to then investigate the extent to which interlanguage competence varies across time, text types, and students. The key outcomes include: 1. An expanded model based on dynamic assessment principles to distinguish between errors and mistakes, which also provides the structure to create and observe learners’ zone of proximal development; 2. A method to increase the accuracy of the part-of-speech tagging procedure whose reliability correlates with the number of incorrect words contained in learners’ texts; 3. A sociocultural insight into interlanguage variability research. Results demonstrate that interlanguage competence is as variable as performance. The main finding shows that knowledge over time is subject to not only systematic, but also unsystematic variations

Document-level sentiment analysis of email data

Sisi Liu investigated machine learning methods for Email document sentiment analysis. She developed a systematic framework that has been qualitatively and quantitatively proved to be effective and efficient in identifying sentiment from massive amount of Email data. Analytical results obtained from the document-level Email sentiment analysis framework are beneficial for better decision making in various business settings