Investigating the Differences Between Prepared and Spontaneous Speech Characteristics: Descriptive Approach

In the modern EFL paradigm, pre-task planning time is viewed as a norm. Pre-task planning time is one of the central concerns of teachers, test-developers, as well as researchers. Pre-task planning is planning a speech before performing a task, and it also involves rehearsal and strategic planning. The paper addresses the problem of pre-task planning advisability for A2 Russian EFL speakers. The research presented in this paper examines the structure, breakdown, repair, syntactic complexity, lexical diversity as well as the accuracy of the discourse produced by 145 Russian participants of the English language competition held in Kazan, Russia, in January 2020. The discourse analysis revealed that the pre-task time is used by A2 EFL speakers not only to focus on a dialog but also to elicit a topic text from memory, thus focusing on form rather than meaning. Hence, in A2 tests prioritizing meaning over form and measuring the ability for spontaneous speech, the one-minute pre-task planning time is viewed as questionable

Discourse complexity: driving forces of the new paradigm

In the article, the authors investigate what makes the text difficult for a certain category of readers, thereby expanding the object of research from " text" to "text and reader", or, more specifically, "alignment of text and reader". Texts are examined for complexity, i.e. features of the text that affect its understandin

Lexical and syntactic features of academic Russian texts: a discriminant analysis

This article presents three mathematical models to differentiate academic texts from three subject discourses written in Russian (i.e., Philological, Mathematical, and Natural Sciences) which further enable design and automated profiling of corresponding typologie

Lexical density as a complexity predictor: the case of Science and Social Studies textbooks

The presented study aims to study the lexical density, interpreted by the authors as an effective predictor of text complexity and calculated by the ratio of words of significant parts of speech to the common the number of words in the text. The study also aims to study the dynamics and correlations of the Flesch-Kincaid index (readability) with the lexical density in the texts of 12 textbooks on natural and social sciences, taught in grades 7-12 in American school

АНАЛИЗ РАЗВИТИЯ УЧРЕЖДЕНИЙ ДОПОЛНИТЕЛЬНОГО ОБРАЗОВАНИЯ ДЕТЕЙ В ГОРОДЕ КОМСОМОЛЬСКЕ-НА-АМУРЕ

In work the basic problems of development of additional formation of children are formulated. The analysis of activity of establishments of additional formation in a is presented in the city Komsomolsk-on-Amur. Results of the analysis are partially compared to development of establishments of additional formation of children on the country as a whole.В работе сформулированы основные проблемы развития дополнительного образования детей. Представлен анализ деятельности учреждений дополнительного образования в г. Комсомольске-на-Амуре. Результаты анализа частично сопоставлены с развитием учреждений дополнительного образования детей по стране в целом

Computing syntactic parameters for automated text complexity assessment

Copyright © 2019 for this paper by its authors. The article focuses on identifying, extracting and evaluating syntactic parameters influencing the complexity of Russian academic texts. Our ultimate goal is to select a set of text features effectively measuring text complexity and build an automatic tool able to rank Russian academic texts according to grade levels. models based on the most promising features by using machine learning methods The innovative algorithm of designing a predictive model of text complexity is based on a training text corpus and a set of previously proposed and new syntactic features (average sentence length, average number of syllables per word, the number of adjectives, average number of participial constructions, average number of coordinating chains, path number, i.e. average number of sub-trees). Our best model achieves an MSE of 1.15. Our experiments indicate that by adding the abovementioned syntactic features, namely the average number of participial constructions, average number of coordinating chains, and the average number of sub-trees, the text complexity model performance will increase substantially

Prediction of reading difficulty in Russian academic texts

© 2019 - IOS Press and the authors. All rights reserved. Education policy makers viewmeasuring academic texts readability and profiling classroom textbooks as a primary task of education management aimed at sustaining quality of reading programs. As Russian readability metrics, i.e. "objective" features of texts determining its complexity for readers, are still a research niche, we undertook a comparative analysis of academic texts features exemplified in textbooks on Social Science and examination texts of Russian as a foreign language. Experiments for 7 classifiers and 4 methods of linear regression on Russian Readability corpus demonstrated that ranking textbooks for native speakers is a much more difficult task than ranking examination texts written (or designed) for foreign students. The authors see a possible reason for this in differences between two processes: Acquiring a native language on the one hand and learning a foreign language on the other. The results of the current study are extremely relevant in modern Russia which is joining the Bologna Process and needs to provide profiled texts for all types of learners and testees. Based on a qualitative and quantitative analysis of a text, the research offers a guide for education managers to help build consensus on selecting a reading material when educators have differing views

Computing syntactic parameters for automated text complexity assessment

Copyright © 2019 for this paper by its authors. The article focuses on identifying, extracting and evaluating syntactic parameters influencing the complexity of Russian academic texts. Our ultimate goal is to select a set of text features effectively measuring text complexity and build an automatic tool able to rank Russian academic texts according to grade levels. models based on the most promising features by using machine learning methods The innovative algorithm of designing a predictive model of text complexity is based on a training text corpus and a set of previously proposed and new syntactic features (average sentence length, average number of syllables per word, the number of adjectives, average number of participial constructions, average number of coordinating chains, path number, i.e. average number of sub-trees). Our best model achieves an MSE of 1.15. Our experiments indicate that by adding the abovementioned syntactic features, namely the average number of participial constructions, average number of coordinating chains, and the average number of sub-trees, the text complexity model performance will increase substantially

Hypnotherapy for borderline psychic disorders in a multidisciplinary hospital

The increase in the number of patients with mental disorders in general hospitals with the shorter patient length of stay there requires diagnostic and therapeutic measures as soon as possible. Group hypnotic suggestive psychotherapy (HSPT) is an effective psychotherapeutic technique that is capable of covering a large number of patients in a short time.Objective: to evaluate the efficiency of short-term group HSPT in multidisciplinary hospital patients with borderline psychic disorders accompanying the underlying disease and to determine the impact of a single session of such therapy on the patients' condition.Patients and methods. A study group consisted of 78 patients who received HSPT; a control group included 37 patients who did not have such therapy. Treatment-induced changes in their mental state were evaluated using the Symptom Checklist-90-Revised questionnaire; the patients' current state was rated with the Mood and Feelings (health, activity, and mood) questionnaire, and the situational anxiety subtest of the integrative anxiety test (IAT-st).Results and discussion. The study group showed a more pronounced reduction in mental disorders, especially the symptoms of anxiety and depression, than that in the control group. A single HSPT session was shown to have a positive impact on the current state of patients, considerably improving their well-being and reducing the  manifestations of anxiety. Improving both the somatic and mental state of patients immediately before their discharge from a hospital seems to be an important therapeutic and social factor also for successful outpatient treatment.Conclusion. It is necessary to conduct a follow-up study to clarify how long the impact of short-term intervention using HSPT can persist. The latter can be effective in multidisciplinary hospital patients

Prediction of reading difficulty in Russian academic texts

© 2019 - IOS Press and the authors. All rights reserved. Education policy makers viewmeasuring academic texts readability and profiling classroom textbooks as a primary task of education management aimed at sustaining quality of reading programs. As Russian readability metrics, i.e. "objective" features of texts determining its complexity for readers, are still a research niche, we undertook a comparative analysis of academic texts features exemplified in textbooks on Social Science and examination texts of Russian as a foreign language. Experiments for 7 classifiers and 4 methods of linear regression on Russian Readability corpus demonstrated that ranking textbooks for native speakers is a much more difficult task than ranking examination texts written (or designed) for foreign students. The authors see a possible reason for this in differences between two processes: Acquiring a native language on the one hand and learning a foreign language on the other. The results of the current study are extremely relevant in modern Russia which is joining the Bologna Process and needs to provide profiled texts for all types of learners and testees. Based on a qualitative and quantitative analysis of a text, the research offers a guide for education managers to help build consensus on selecting a reading material when educators have differing views