Model Of Language Learning Research Articles

Meaningful interaction and affordances for language learning at a Zapotec revitalisation programme

ABSTRACTMany theoretical models of second or additional language learning posit a crucial role for meaningful social interaction in the target language. However, it is not always clear to language educators how to create such opportunities or what counts as meaningful interaction. This can become even more difficult when the target language is an endangered language, as there may not be a real-world social context in which to speak the language. This paper offers an illustration of how educators at a Sierra Juárez Zapotec language revitalisation programme in Oaxaca, Mexico have tried to make teaching more effective by creating new spaces for meaningful interaction and focusing on ‘affordances’ for language learning. Affordances are understood to be moments or opportunities when sociological and cognitive factors come together to catalyse and promote language acquisition. Educators at the Zapotec programme provided affordances for language learning through: (1) meaningful listening, (2) rich and elaborated language, and (3) negotiation for meaning. Through a discussion of these strategies, this paper aims to share with a wider audience the ways that one group of indigenous language teachers have addressed some of the pedagogical challenges they faced.

Developing Intercultural Language Learning (ILL) model to teach writing skills at Indonesian private universities

This study was aimed at developing an intercultural language learning (ILL) model and finding out its effectiveness to increase students’ writing skills. The kind of this study was procedural research (R&D) design. This study was preceded with the development phases and continued by field-testing. The field-testing was conducted by using a quasi-experimental method to know the effectiveness of the developed learning model. The sample included 64 students. The students were divided into two groups and each group consisted of 32 students. One group was the experimental group taught by suing the ILL model and the other group was the control group taught by implementing the conventional learning model. The mean score of students taught by ILL model was 80.34 and those taught by conventional one was 69.97. The data were defined as normal and homogeneous data because the value of sig. was higher than sig. level 0.05. Based on the ANOVA test, the value of sig. (0,000) was lower than the sig. level 0.05. It means there is a significantly different achievement of students taught using an ILL model rather than the conventional learning model. The result informed ILL model was more effective than the conventional one in the teaching of writing skills.

Connecting students and researchers: the secondary school student’s voice in foreign language education research

ABSTRACT The inclusion of student voice in foreign language research often relies mainly on a perspective that includes their voice as a data source, in spite of claims that the perspectives that include students as initiators should be at the fore. In this paper, the authors address the incongruity of this situation, arguing for a revision of current views. They discuss different conceptualisations of student voice in educational research, and argue that combinations of different perspectives on student voice provide unique insights that are necessary to develop our knowledge base. They then provide a detailed account of an empirical study in which an English as a foreign language (EFL) literature teaching and learning model was validated through collaboration and co-construction with secondary school students. They demonstrate the ways in which two different perspectives were combined within the project, resulting in a dialogical process, which then lends multidimensional support to the findings.

ПРОБЛЕМА ФОРМУВАННЯ МОВНОЇ ОСОБИСТОСТІ ШКОЛЯРА: КОМУНІКАТИВНО-ПРАГМАТИЧНИЙ АСПЕКТ

У статті відзначено, що тенденції комплексного підходу до вивчення мовних явищ на ґрунті нових мовознавчих дисциплін детермінують навчально-педагогічний дискурс, зумовлюючи необхідність комунікативно-прагматичної переорієнтації методики навчання мови та внесення коректив до змістового наповнення шкільних підручників з української мови, зорієнтованих переважно на лінгвоцентричну репрезентацію мовних одиниць.

Adapting and evaluating a deep learning language model for clinical why-question answering.

ObjectivesTo adapt and evaluate a deep learning language model for answering why-questions based on patient-specific clinical text.Materials and MethodsBidirectional encoder representations from transformers (BERT) models were trained with varying data sources to perform SQuAD 2.0 style why-question answering (why-QA) on clinical notes. The evaluation focused on: (1) comparing the merits from different training data and (2) error analysis.ResultsThe best model achieved an accuracy of 0.707 (or 0.760 by partial match). Training toward customization for the clinical language helped increase 6% in accuracy.DiscussionThe error analysis suggested that the model did not really perform deep reasoning and that clinical why-QA might warrant more sophisticated solutions.ConclusionThe BERT model achieved moderate accuracy in clinical why-QA and should benefit from the rapidly evolving technology. Despite the identified limitations, it could serve as a competent proxy for question-driven clinical information extraction.

Control and Ownership of Neuroprosthetic Speech

Implantable brain-computer interfaces (BCIs) are being developed to restore speech capacity for those who are unable to speak. Patients with locked-in syndrome or amyotrophic lateral sclerosis could be able to use covert speech – vividly imagining saying something without actual vocalisation – to trigger neural controlled systems capable of synthesising speech. User control has been identified as particularly pressing for this type of BCI. The incorporation of machine learning and statistical language models into the decoding process introduces a contribution to (or ‘shaping of’) the output that is beyond the user’s control. Whilst this type of ‘shared control’ of BCI action is not unique to speech BCIs, the automated shaping of what a user ‘says’ has a particularly acute ethical dimension, which may differ from parallel concerns surrounding automation in movement BCIs. This paper provides an analysis of the control afforded to the user of a speech BCI of the sort under development, as well as the relationships between accuracy, control, and the user’s ownership of the speech produced. Through comparing speech BCIs with BCIs for movement, we argue that, whilst goal selection is the more significant locus of control for the user of a movement BCI, control over process will be more significant for the user of the speech BCI. The design of the speech BCI may therefore have to trade off some possible efficiency gains afforded by automation in order to preserve sufficient guidance control necessary for users to express themselves in ways they prefer. We consider the implications for the speech BCI user’s responsibility for produced outputs and their ownership of token outputs. We argue that these are distinct assessments. Ownership of synthetic speech concerns whether the content of the output sufficiently represents the user, rather than their morally relevant, causal role in producing that output.

A Comparison of Methods in Political Science Text Classification: Transfer Learning Language Models for Politics

Automated text classification has rapidly become an important tool for political analysis.Recent advancements in NLP enabled by advances in deep learning now achieve state of the art results in many standard tasks for the field. However, these methods require large amounts of both computing power and text data to learn the characteristics of the language, resources which are not always accessible to political scientists. One solution is a transfer learning approach, where knowledge learned in one area or source task is transferred to another area or a target task. A class of models that embody this approach are language models, which demonstrate extremely high levels of performance. We investigate the performance of these models in the political science by comparing multiple text classification methods. We find RoBERTa and XLNet, language models that rely on theTransformer, require fewer computing resources and less training data to perform on par with – or outperform – several political science text classification methods. Moreover, we find that the increase in accuracy is especially significant in the case of small labeled data, highlighting the potential for reducing the data-labeling cost of supervised methods for political scientists via the use of pretrained language models.

IMPLEMENTASI E-EDITION MODERN STANDARD ARABIC (MSA) DALAM PEMBELAJARAN BAHASA ARAB

The Language Development Center (P2B) is one of the institutions under management of UIN Sunan Ampel Surabaya. This program has responsibility in strengthening Arabic language competence for all students. The standardization of Arabic language competencies is an Arabic language learning intensification program that is managed by P2B. P2B has made various efforts in improving student competence in Arabic, one of it is by reformulating the Arabic Language learning model, namely by implementing online learning using the E-edition Modern Standard Arabic (MSA) program. The Intensive Arabic Language learning program is done twice a week which are divided into two study groups based on the language competency classifications students. All Intensive Arabic Instructors have different learning strategies, adjusting the characteristics and competencies of their students in each class. As a final test is conducted using an online test called Final Online Test (FOT), It means to measure the results of the Arabic language learning that has been done. The type of this research is a qualitative descriptive analysis research, with deep interview, documentation, group discussion forum as data collection technique.

THE MODEL OF FORMATION OF SELF-DIRECTED LANGUAGE LEARNING OF UNIVERSITY STUDENTS IN A UNIFIED HIGHER EDUCATION AREA

Purpose of the study: The article aims to analyze the problem of modeling self-directed language learning of university students in a Unified Higher Education Area. Methodology: Our study is based on the theoretical research method – the analysis of foreign and national philosophical, pedagogical literature on a problem; analysis and generalization of modern pedagogical experience; theoretical modeling; empirical – research and analysis of pedagogical experience; observation, interviews with teachers and students. Results: Modeling of self-directed language learning of university students is considered by the author in terms of systemic, student-centered and competence-based approaches. The model of self-directed language learning is represented as an integrative construct, which includes the target, content, technological and productive blocks. The main components of the model are the goal, tasks, components of self-directed learning, modern technologies, methods, forms, criteria, and indicators. Applications of this study: The materials of this research can be used by teachers to develop special courses of lectures and seminars on the organization of self-directed language learning of university students. Novelty/Originality of this study: In this research, the model of Formation of Self-Directed Language Learning of University Students in a Unified Higher Education Area is presented in a comprehensive and complete manner.

The Challenges of Existing Syntactic Models for English Language Teaching and Learning in Nigeria

A recent survey of existing syntactic models shows that none accurately describes the syntax of the English languagethat people actually use and that they inhibit rather than promote knowledge of natural language by creating a gapbetween what should be taught and learned and what obtains. To demonstrate this gap, this paper critically examinesfour recommended senior secondary school English course books to determine the extent to which they reflectexisting syntactic models’ descriptive inadequacies, and highlights the implications for language education inNigeria. Using the emerging Natural Language Linguistics (NLL) model as analytical tool, each book was carefullyexamined to identify topics on the syntactic units: sentence, clause and group. These were then critically studied,paying great attention to definitions, descriptive statements, models, and examples, and noting common features anddifferences. The bits of information pieced together constitute the data. Findings show inconsistency in modelapplication, no uniformity in, and consensus on, the number and nomenclature of syntactic units, terminologicalconfusion, descriptive inaccuracies, typological inexactness, incorrect definitions, wrong and inappropriate examples,and confusion between constituents and elements of structure. The absence of a clear-cut distinction between phraseand clause and between clause and sentence in existing syntactic models, which reflected in the books, explains theshortcomings that potentially limit learners’ knowledge and use ability. Only a syntactic model that accuratelymirrors natural language structure can positively promote language education in the Nigerian context where coursebooks are the most important English teaching-learning resource.

Model Pembelajaran Bahasa Berbasis Riset melalui Analisis Framing

This study aims to apply a number of language learning models in research-based tertiary institutions through framing analysis. Experimental learning models such as discovery learning, inquiry learning, dan problem based. The results of the teaching and learning process were responded well by a numbe r of students. The response, for example, is demonstrated through research (linguistic) using framing analysis for the final project preparation (thesis). Meanwhile, in the context of research: the methods used include: consider, record, with data analysis using framing analysis. The result: in framing both (Jokowi and Prabowo) there are similarities in terms of (1) protruding at the syntactic level, namely on the headline, (2) protruding on the script aspect, ie focusing on reporting, (3) highlighting on the aspect of the theme, namely in paragraphs, and (4) protruding on the rhetorical aspect, i.e. the photos displayed. In addition, there is a negative image of Prabowo more visible than in Jokowi.

Teaching English for young learners at primary school based on the environmental approach

This study aims to create an English language learning model for children who are concerned about the environment in elementary schools. This research is a qualitative descriptive study that aims to create a conceptual model of learning English based on environmental love. This research was conducted at SD 1 Bone-Bone, Baubau City, Southeast Sulawesi, in May. The data in this study are primary data, among others, the results of observations as long as researchers make observations, the results of interviews with English teachers. Secondary data include documentation about student name data, documentation on English language teaching materials based on Environmental Education, banners, photos, and other available data as research supporting data. The data analysis technique in this study uses Miles and Huberman’s interactive data analysis method which includes three stages, namely data reduction, data presentation, and conclusion/verification. The researcher analyzed the data obtained from the observations and the results of interviews with the principal, English teacher and student.

The Effectiveness of Using Dramatic Problematizer Language Learning Model (DPLLM) in Developing EFL Prospective Teachers' Critical Reading Skills and Reading Habits

The purpose of the research is to investigate the effectiveness of using dramatic problematizer language learning model (DPLLM) in developing EFL prospective teachers' critical reading skills and reading habits. The design of the research was a mixed research methodology. It combined both quantitative and qualitative methods of inquiry. The participants of the research consisted of sixty students (N=60). They were chosen from third students enrolled in English section at Benha Faculty of Education, Egypt. They were divided into two groups; an experimental group (N=30) and control group (N= 30). The experimental group was taught through using Dramatic Problematizer Language Learning Model (DPLLM), while the control group was taught by the regular method. Both groups were tested before and after the intervention. The instruments of the research included an EFL critical reading skills test, reading habits scale and semi-structured interview. Results of the research revealed a statistically significant difference between the mean scores of the control group and experimental group students in the pre and post administration of the EFL critical reading skills and reading habits in favor of the experimental group. These results were ascribed to using dramatic problematizer language learning model.

The effects of Gamification-based Artificial Intelligence Chatbot activities on elementary English learners’ speaking performance and affective domains.

This study aims to investigate the effects of Gamification-based artificial intelligence chatbot activities on elementary English learners’ speaking performance and affective domain. To accomplish the purpose, Gamification-based AI chatbot activities were designed and implemented in experimental lessons with the experimental group. The participants were 15 students of grade 6 who performed 3 speaking practice activities and 3 speaking usage activities during experimental lessons. Their performance was, then compared to that of the control group learners. The learners’ speaking performances were recorded and analyzed quantitatively and qualitatively. Their speaking pre/post-test score, and each score of speaking performance during the experimental class were collected and analyzed. Affective aspects were analyzed through survey to assess any differences between the groups or if any changes within the group occurred during the lesson. Semi-structured interview data was also presented to reveal the effects of Gamification-based AI chatbot activity in terms of English speaking, interest, attitude, and confidence. It was found that the Gamification-based AI chatbot activity is effective as English speaking practice and usage to all level learners. Specifically, AI technology seemed to help learners have linguistic awareness and Gamification strategy made learners engaged during tasks. The findings of this study suggest designing classroom-based AI assisted language learning model. Also, more empirical evidence is required through classroom-based action research.

The Subject–Object Asymmetry Revisited: Experimental and Computational Approaches to the Role of Information Structure in Children’s Argument Omissions

In two studies, we investigated the relation between information structure and argument omission in German child language in order to quantify to what extent the subject–object hypothesis (i.e., subjects are omitted more often than objects) is influenced by discourse pragmatics. Twenty four children took part in an elicited production study in which they produced transitive subject–verb–object and object–verb–subject sentences. Both constructions are instances of a topic-comment information structure. The results showed that 3;6 year-old children omitted subjects and objects alike when the arguments assumed topics status and were placed in utterance-initial position. In a second study, we then assessed whether a model of language learning implemented with a recency bias (resulting in learning from the end of utterances) would produce similar omission rates of initial arguments. The model was found to be sensitive to the frequency with which both word orders occurred in the input: initial objects were omitted more often than initial subjects, the pattern found in German caregiver speech. The results suggest that argument omission is heavily influenced by information structure and that a subject–object asymmetry per se does not exist.

Validating a Motivational Process Model for Mobile-Assisted Language Learning

This study examined the causal relationships among goal orientations, implementation intentions, and self-regulated learning behavior in relation to mobile-assisted language learning. The hypothetical relations among the three domain constructs were formulated in accordance with the theorizing of the Rubicon model of motivational phases (Achtziger and Gollwitzer 2008). The results showed that the instigation of implementation intentions was largely conditioned upon learners’ awareness of integrativeness and a sense of mastery in light of their reasons for or goals of learning English. The study further showed that self-regulated learning could be significantly predicted by implementation intentions. The outcome model showed that self-regulated learning behavior is the most important factor in predicting linguistic outcomes. The results of the study helped understand the different motivation phases of mobile-assisted language learning.

Positioning Spanish-Language and African American Language (AAL) Speakers as Knowledgeable and Valuable Contributors in the Language Arts Classroom

We utilize positioning theory to analyze language use within two different language program models in elementary language arts classrooms. We explore how the positioning of minoritized languages as valuable facilitates the use of students’ home languages in classrooms and allows us to examine the connections between language, identity, and power. Additionally, through the use of positioning theory alongside language learning theory, we recognize the importance of supporting students’ heritage language use, including nonstandard language varieties, in classroom settings. In the dual language (DL) classroom, we see how the teacher positions the Spanish language as valuable and worthy of learning. In the English as a Second Language (ESL) classroom, the teacher positions African American Language (AAL) as worthy of study and inclusion in the curriculum and promotes the use of AAL within the poetry unit. Finally, we identify tensions that can emerge for teachers in different sociopolitical contexts within each of these language learning models.

Model Pembelajaran Program Ekstrakurikuler Bahasa Arab dan Implementasinya di Madrasah Aliyah Pesantren

Pesantren based madrasah makes the Arabic language as one of the essential things to be mastered by their students. Madrasah runs several Arabic programs to improve students attention and proficiency of Arabic language through extracurricular activities outside the classroom that aim to enrich knowledge and channel students interest and talents. However, among these various activities, many of it do not operate well because of lack of skills. The purpose of this study is to describe the implementation of extracurricular programs in MA Pesantren Nurul Ulum and the language learning models used. The research used the descriptive qualitative method. The data sources of this research are the instructors in the Arabic extracurricular program, the location, files and photos of activities that carried out by interview, observation, and documentation. The results of this study are the implementation of extracurricular programs in MA Pesantren Nurul Ulum by using various language learning models following the objectives of the activities; cooperative models in Arabic Olympics extracurricular, Taqdimul Qishshah, and Khithabah, communicative-eclectic and quantum models in quiz extracurricular. Diverse learning models make the learning process more varied for teachers and students while train student competencies. Then it should be realized as a whole in Arabic language education.

Science in Silence: How Educators of the Deaf and Hard-of-Hearing Teach Science

Science learning is inextricably tied to two aspects of students’ lives: literacy and culture. While English Learners (ELs) who speak a non-English native language are typically the focus in this line of scholarly inquiry, deaf and hard-of-hearing (DHH) students occupy a distinct space in this conversation. For DHH learners, literacy levels can be hindered by an early dependence on a more survival-based language learning model that postpones basic scientific inquiry. The vocabulary for curiosity is limited, which in turn affects the educational culture. DHH learners have a unique culture that demands an appropriate science curriculum, which thus far has not been explored or attempted for either DHH learners or their educators. Data collected consisted of interviews with teachers of DHH students, as well as observational data collected from a high-minority urban K-8 school for DHH students. The analysis revealed that, first, many of the teachers had limited preparation to teach science content. Second, DHH teachers used inconsistent instructional strategies ranging from drawing pictures to building models. Third, the modifications provided to DHH science learners were mostly limited to visual support and repetition. Implications for teacher education programs include instruction focused on specific supports for DHH students and co-teaching methods, and deeper investigation of inquiry-based science practices. Implications for classroom practices include providing hands-on, inquiry-based instruction, working closely with parents, and developing students’ and teachers’ understanding of scientific inquiry.

Understanding the topic evolution of scientific literatures like an evolving city: Using Google Word2Vec model and spatial autocorrelation analysis

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.