A Critical Examination of Preservice Music Teachers’ Writing on the edTPA Portfolio

The purpose of this study was to examine the relationship between participants’ edTPA writing and edTPA portfolio scores. Specific questions included (a) Is there a relationship between overall word count and total score on the edTPA? (b) Are individual task commentary word counts associated with specific task scores and total edTPA scores? and (c) Is there a relationship between edTPA-specific vocabulary and total score on the edTPA? Written artifacts from 67 music education students who completed the K–12 Performing Arts edTPA Portfolio were collected over a 4-year period. Correlations between word counts and task and total scores were positive and of modest to moderate strength, as was the correlation between edTPA vocabulary word use and total scores. These findings are interpreted in relation to a national K–12 Performing Arts edTPA portfolio average score of 45 and existing edTPA policies affecting music teacher education programs.

Automated Complexity Assessment of English Informational Texts for EFL Pre-service Teachers and Translators

Automated text complexity assessment tools are of enormous practical value in solving the time-consuming task of analyzing English informational texts for their complexity at the pre-reading stage. The present study depicts the application of the automated text analysis system the TextEvaluator as an effective tool that helps analyze texts on eight dimensions of text complexity as follows: syntactic complexity; academic vocabulary; word unfamiliarity; word concreteness; lexical cohesion; interactive style; level of argumentation; degree of narrativity, with further summarizing them with an overall genre-dependent complexity score. This research examines the complexity dimensions of English informational texts of four genres – legal, linguistic, news, and medical – that are used for teaching reading comprehension to EFL (English as a foreign language) pre-service teachers and translators at universities in Ukraine. The data obtained with the help of the TextEvaluator has shown that English legal texts are the most difficult for reading comprehension in comparison to linguistic, news, and medical texts. In contrast, medical texts are the least challenging out of the four genres compared. The TextEvaluator has provided insight into the complexity of English informational texts across their different genres that would be useful for assembling the corpora of reading passages scaled on specific dimensions of text complexity that predict text difficulty to EFL pre-service teachers and translators.

Knowledge-Aware Dialogue Generation via Hierarchical Infobox Accessing and Infobox-Dialogue Interaction Graph Network

Due to limited knowledge carried by queries, traditional dialogue systems often face the dilemma of generating boring responses, leading to poor user experience. To alleviate this issue, this paper proposes a novel infobox knowledge-aware dialogue generation approach, HITA-Graph, with three unique features. First, open-domain infobox tables that describe entities with relevant attributes are adopted as the knowledge source. An order-irrelevance Hierarchical Infobox Table Encoder is proposed to represent an infobox table at three levels of granularity. In addition, an Infobox-Dialogue Interaction Graph Network is built to effectively integrate the infobox context and the dialogue context into a unified infobox representation. Second, a Hierarchical Infobox Attribute Attention mechanism is developed to access the encoded infobox knowledge at different levels of granularity. Last but not least, a Dynamic Mode Fusion strategy is designed to allow the Decoder to select a vocabulary word or copy a word from the given infobox/query. We extract infobox tables from Chinese Wikipedia and construct an infobox knowledge base. Extensive evaluation on an open-released Chinese corpus demonstrates the superior performance of our approach against several representative methods.

Automated Scoring of Tablet-Administered Expressive Language Tests

Speech and language impairments are common pediatric conditions, with as many as 10% of children experiencing one or both at some point during development. Expressive language disorders in particular often go undiagnosed, underscoring the immediate need for assessments of expressive language that can be administered and scored reliably and objectively. In this paper, we present a set of highly accurate computational models for automatically scoring several common expressive language tasks. In our assessment framework, instructions and stimuli are presented to the child on a tablet computer, which records the child's responses in real time, while a clinician controls the pace and presentation of the tasks using a second tablet. The recorded responses for four distinct expressive language tasks (expressive vocabulary, word structure, recalling sentences, and formulated sentences) are then scored using traditional paper-and-pencil scoring and using machine learning methods relying on a deep neural network-based language representation model. All four tasks can be scored automatically from both clean and verbatim speech transcripts with very high accuracy at the item level (83−99%). In addition, these automated scores correlate strongly and significantly (ρ = 0.76–0.99, p < 0.001) with manual item-level, raw, and scaled scores. These results point to the utility and potential of automated computationally-driven methods of both administering and scoring expressive language tasks for pediatric developmental language evaluation.

Automated Complexity Assessment of English Informational Texts for EFL Pre-service Teachers and Translators

Automated text complexity assessment tools are of enormous practical value in solving the time-consuming task of analyzing English informational texts for their complexity at the pre-reading stage. The present study depicts the application of the automated text analysis system the TextEvaluator as an effective tool that helps analyze texts on eight dimensions of text complexity as follows: syntactic complexity; academic vocabulary; word unfamiliarity; word concreteness; lexical cohesion; interactive style; level of argumentation; degree of narrativity, with further summarizing them with an overall genre-dependent complexity score. This research examines the complexity dimensions of English informational texts of four genres – legal, linguistic, news, and medical – that are used for teaching reading comprehension to EFL (English as a foreign language) pre-service teachers and translators at universities in Ukraine. The data obtained with the help of the TextEvaluator has shown that English legal texts are the most difficult for reading comprehension in comparison to linguistic, news, and medical texts. In contrast, medical texts are the least challenging out of the four genres compared. The TextEvaluator has provided insight into the complexity of English informational texts across their different genres that would be useful for assembling the corpora of reading passages scaled on specific dimensions of text complexity that predict text difficulty to EFL pre-service teachers and translators.

A Comparative Between British English And American English: Vocabulary Analysis

This research paper aims to analyze the comparative between British English and American English, because many language learners or English users still confuse to differentiate both of them, especially in the countries where English is foreign language. Sometimes, it cause misunderstanding in communication. The research paper use qualitative research design with characteristic of content analysis. It uses observation and documentation in collecting the data. The obtained data is vocabulary in Oxford Advanced Learner’s Dictionary 9th edition which published in 2015. The researcher took 150 words to be analyzed. Based on the data analysis there are three differences in Vocabulary of British English and American English. The researchers divide the differences into three categories they are differences in Vocabulary (word using), spelling, and pronunciation. The researcher found 50 different words in vocabulary (word using), 50 different words in spelling and 50 words which have differences in pronunciation. Based on findings of this research, it is significant for language learners or English user to know the differences of British English and American English and improve their vocabulary of British and American English in order to decrease misunderstanding in communication. The researchers hope language learners or English user can decide which English varieties that will they use and the can use one of English varieties consistently.

The effects of dialogic reading on the expressive vocabulary of pre-school aged children with moderate to severely impaired expressive language skills

The purpose of this study was to investigate the effects of dialogic reading on the expressive vocabulary skills of children with moderate to severe expressive impairments. Previous research has shown positive effects of dialogic reading on the language skills of children who are typically developing and on children who are at-risk for language delays. However, there is limited research indicating the effectiveness of dialogic reading on children with moderate to severely delayed language skills. The participants in this single-case, multiple baseline across participants designed study received four weeks of individual dialogic reading intervention which was intended to increase their expressive vocabulary skills of a near-transfer vocabulary word list. The results revealed that all three participants demonstrated a significant increase in expressive vocabulary of the near-transfer vocabulary list.

SYSTEM-FUNCTIONAL PECULIARITIES OF THE ENGLISH PANDEMIC LEXICAL CLUSTER

The article aims at analyzing the topical English pandemic (coronavirus) vocabulary from the perspective of system-functional approach. This envisages performing following tasks: 1) to identify the pandemic (coronavirus) lexical cluster, 2) to describe the word-building peculiarities of the English coronavirus vocabulary and 3) to interpret the functioning of this vocabulary within the political, every day, and Internet discourses.Methods. The methodological framework used in the study features: 1) generalization for establishing basic theoretical principles of the research; 2) structure-semantic analysis for studying the word-building specifics of the pandemic vocabulary; 3) statistical method for defining calculate the frequency and the productivity of certain word-building models within the pandemic lexical cluster; 4) the elements of discourse analysis to highlight the functional peculiarities of coronavirus vocabulary.Results. Coronacrisis, that we have experienced till the present, has become a crucial factor catalyzing nomination processes of the novel concepts, thus influencing the lexical system of the English language. We consider pandemic lexicon (coronavirus vocabulary) the novelist group of neologisms in the English language since it comprises innovative words and phrases which have been coined since the start of COVID-19 pandemic and relate to its impact on the modern life. Among the most common for coronavirus vocabulary word-building models are derivation, compounding, shortening, loan and substitution; alongside, the statistical analysis has proved blending to be the most productive word-building model. The study of functional peculiarities of the pandemic lexicon within various types of discourses shows that its biggest part has entered the usus. The use of pandemic vocabulary within the Internet discourse is marked by the development of a number of thematic groups of language units referring to: 1) routine activities and events; 2) changes in learn and work modes; 3) excess weight; 4) alcohol and 5) verbal aggressiveness.Conclusions. The study enabled categorizing the units of the English pandemic (coronavirus) vocabulary as a separate lexical cluster, which has predominantly developed with the help of the already existing language resources. The units of this innovative cluster perform nominative function by naming new concepts and realia of life, reflect social moods, for instance, the feelings of worry, fear, anguish, and hopelessness, or facilitate the humorous effect in communication. Prospects for future research lie within the expansion of discursive analysis of pandemic innovations for revealing functional of some neological units on different stages of the COVID-19 pandemic, as well as conducting a comparative study of pandemic innovations in distant languages.Key words: word-building, lexical innovation, pandemic vocabulary, discourse. Метою пропонованого дослідження є висвітлення актуального пандемійного (коронавірусного) вокабуляру англійської мови з позицій системно-функціонального підходу. Досягненню мети сприяє виконання таких завдань: 1) ідентифікувати пандемійний (коронавірусний) лексичний кластер; 2) охарактеризувати словотвірні особливості коронавокабуляра англійської мови та 3) проінтерпретувати особливості функціонування коронавокабуляра в політичному, повсякденному та інтернет-дискурсах.Методи. Для досягнення поставленої мети застосовувалися: 1) метод узагальнення для ідентифікації базових теоретич-них положень; 2) метод структурно-семантичного аналізу для вивчення особливостей словотвору пандемійного вокабуляра; 3) статистичний метод для вирахування частотності та продуктивності словотворення пандемійного лексичного кластера за конкретними моделями; 4) елементи дискурс-аналізу для вивчення функціональних особливостей короновокабуляра.Результати. Коронакриза, що триває нині, є центральним фактором впливу на лексикографічну систему англійської мови, оскільки актуалізувала проблему номінації нових реалій. Найактуальнішою неологічною групою англійської мови нині є пандемійна лексика (коронавірусний вокабуляр), до складу якого, зокрема, входять інноваційні слова та вирази, що виникли з початку пандемії COVID-19 та пов’язані з її впливом на сучасне життя. Елементи коронавокабуляра утворюються за низкою дериваційних моделей, до числа яких відносимо деривацію, основоскладання, скорочення, запозичення, субституцію, проте найпродуктивнішою моделлю за результатами статистичного аналізу є телескопія. Дослідження особливостей функціонуван-ня коронавірусного вокабуляра в різних типах дискурсу дає змогу констатувати превалювання узуальної лексики та тісні між-дискурсивні зв’язки, зокрема між політичним дискурсом та дискурсом повсякденності. Використання пандемійної лексики на просторах інтернет-дискурсу відзначається формуванням низки лексико-семантичних груп на позначення: 1) рутинних занять та подій; 2) змін у звичному розпорядку навчальної та робочої діяльності; 3) зайвої ваги; 4) алкоголю та 5) мовної агресії.Висновки. Проведене дослідження уможливило виокремлення англомовного пандемійного (коронавірусного) вокабуляра як окремого лексичного кластера, основу якого становить загальновживана лексика. Одиниці цього інноваційного кластера виконують номінативну функцію через іменування нових реалій та концептів життя, а також рефлектують настрої суспільства, зокрема відчуття занепокоєння, остраху, туги та безнадійності, або ж сприяють реалізації гумористичного ефекту комунікації.Ключові слова: словотворення, лексична інновація, пандемійний вокабуляр, дискурс.

Sambandhar - A Cognoscente in the Field of Fine-Arts

Thirugnana Sambandhar is a multifaceted personality. He is a Saint, Poet, Philosopher, Composer, Scientist, Mathematician, Musician of the 7th century. He has no parallels in the poetic world. Indian poetry has its root dating back to the Vedic times. His poetry for decades has reflected diverse spiritual traditions within India and in many Foreign Countries. He had penned down amazing poetic structures through his mystical experience. His vision, lyrical skills, technical expertise, command over Language, Vocabulary, word-play, meters, Imagery, attitude, love towards his mother tongue are uncomparable. Ultimately he is the Epitome of Tamil Literature.