We describe a simple neural language model that relies only on character-level inputs. Predictions are still made at the word-level. Our model employs a convolutional neural network (CNN) and a highway net work over characters, whose output is given to a long short-term memory (LSTM) recurrent neural network language model (RNN-LM). On the English Penn Treebank the model is on par with the existing state-of-the-art despite having 60% fewer parameters. On languages with rich morphology (Arabic, Czech, French, German, Spanish, Russian), the model outperforms word-level/morpheme-level LSTM baselines, again with fewer parameters. The results suggest that on many languages, character inputs are sufficient for language modeling. Analysis of word representations obtained from the character composition part of the model reveals that the model is able to encode, from characters only, both semantic and orthographic information.
We present a data set for evaluating the grammaticality of the predictions of a language model. We automatically construct a large number of minimally different pairs of English sentences, each consisting of a grammatical and an ungrammatical sentence. The sentence pairs represent different variations of structure-sensitive phenomena: subject-verb agreement, reflexive anaphora and negative polarity items. We expect a language model to assign a higher probability to the grammatical sentence than the ungrammatical one. In an experiment using this data set, an LSTM language model performed poorly on many of the constructions. Multi-task training with a syntactic objective (CCG supertagging) improved the LSTM’s accuracy, but a large gap remained between its performance and the accuracy of human participants recruited online. This suggests that there is considerable room for improvement over LSTMs in capturing syntax in a language model.
Kumaravadivelu's book on language teaching aims to illustrate "the pattern that connects the various elements of learning, teaching, and teacher education" in language teaching (p. xiii). As can be deduced from the title, the major theme of the book cites the emergence of a postmethod condition in the literature on teaching second/foreign languages. This emerging postmethod state has been commented on by other writers such as Brown (2002), Richards (2001) and Adamson (2004). However, Kumaravadivelu has what I perceive to be a very personalized vision of language teaching and the "postmethod" state of English language teaching. He illustrates this by first grounding the reader in the concepts of language, language acquisition, and language teaching, as well as a comprehensive discussion of methodology in language teaching.
We explore the use of large pretrained language models as few-shot semantic parsers. The goal in semantic parsing is to generate a structured meaning representation given a natural language input. However, language models are trained to generate natural language. To bridge the gap, we use language models to paraphrase inputs into a controlled sublanguage resembling English that can be automatically mapped to a target meaning representation. Our results demonstrate that with only a small amount of data and very little code to convert into English-like representations, our blueprint for rapidly bootstrapping semantic parsers leads to surprisingly effective performance on multiple community tasks, greatly exceeding baseline methods also trained on the same limited data.
Content- and language-integrated learning (CLIL) has been considered from the perspective of communicative competence development in the context of teaching professionally oriented English language in a technical university. The chapter outlines the main aspects underlying CLIL and describes the experience of teaching English to students majoring in Photonics in the format of “binary” classes involving two teachers: of English and of physics of lasers. Classes have been designed for 3rd- to 4th-year students who had mastered basic linguistic-cultural communicative competences and went on to continue using English in professionally oriented situations. This way of team teaching contributes to the development of communication skills in the students' professional area and facilitates the assimilation of curricular material by students.
The study aimed to find out the influence of Quizizz as a learning media towards student learning motivation in English learning among tenth grade students at MAN 1 Surakarta during the 2023/2024 academic year. A quantitative method was used with a One Group PretestPosttest design, with 26 students selected through random sampling method. Data was collected through pre-test, post-test, and questionnaire. The researcher used a paired sample t-test formula and SPSS 16 application to analyze the data. The results showed a significant influence of Quizizz on student motivation in English learning. The t-test resulted in a tcount value of 37,787, which was greater than the ttable at a 5% significance level of 2,060. Therefore, the null hypothesis (Ho) was rejected and the alternative hypothesis (Ha) was accepted. The study highlights the importance of using Quizizz as a learning media for English learning among tenth grade students. Keywords: Quizizz, Learning Media, Learning Motivation, Learning English.
The concept and phenomenon of a language game, its main functions, types and application in commercial advertising is a way to attract the attention of consumers and promote a product. Examples of phonetic, morphological and syntactic wordplay in the texts of English-language commercial advertising are analyzed. The purpose of the article is to analyze the techniques of a language game and identify their functional features at various levels in an English-language advertising text. In this article, the following methods were used: descriptive-analytical method, interpretation method, search method. When choosing a material for analysis, the method of continuous sampling was used. As the material of the research, we used English-language advertisements in various resources, such as from magazines and newspapers and videos, in which a language game was revealed. Thus, the language game implemented in advertising texts is an important phenomenon, since it contributes to the maximum impact on the consumer, since the recipient, thanks to his techniques and functions, draws attention to this advertisement. In addition, an advertisement in which a language game as present is an indicator of a high level of the consumer’s language competence.
Language. Linguistic theory. Comparative grammar, Semantics
Proficiency in English language depends on the knowledge of its vocabulary possessed by the second and foreign language learners and even the native speakers. Though developing the vocabulary is vital, it poses several problems, especially, to non-native students of English. Students with a low vocabulary knowledge show weak academic performance in different courses related to the language skills, linguistics, literature, and translation at the university level of education. This study, in particular, aims to investigate the problems faced by English majors in learning the vocabulary at Prince Stattam bin Abdulaziz University (PSAU) in Saudi Arabia. It also puts forward some vocabulary-learning strategies to minimize the potential problems. The data consist of the responses of 100 student-participants (undergraduates) randomly picked up from five different levels (four, five, six, seven, and eight) of 4-Year BA English Program at PSAU. This quantitative study uses an online questionnaire, as an instrument, to collect the data. The results reveal that the English majors at PSAU face several problems in learning the vocabulary such as knowing the meanings of new words, pronouncing new words, using new words correctly, memorizing and spelling new vocabulary and so on. To its contribution, this study emphasizes the importance of learning the English vocabulary, draws students’ attention towards it, highlights the problems encountered by students, and raises their awareness of the vocabulary. Future research may explore teachers’ perspectives on students’ vocabulary-learning problems and instructional methods implemented to teach the vocabulary in English language classrooms.
Aleyda Jasmin Alfonso Vargas, Paola Ximena Romero Molina
The use of authentic materials in foreign language teaching has been a growing practice over the last few decades. With the emergence of technology, these materials are more accessible, particularly in digital formats. Despite being primarily designed for non-pedagogical uses, these materials have become valuable resources for English language learning. However, using them effectively for teaching and learning purposes requires a systematic structure. This article examines the use of authentic materials in relation to various language skills, with a particular focus on listening comprehension framed within a pre-, while-, and post-stage cycle at both local and international levels, with the latter referring to the Colombian context. A review of scholarship shows that the use of authentic materials is a seemingly frequent practice among teacher-researchers, but not among a larger audience of practitioners. Additionally, studies do not provide guidance on how to prepare practitioners to design appropriate activities that complement authentic materials. Therefore, after examining studies and based on our teaching-research experience, we aim to contribute to the implementation of a pedagogical strategy that combines the systematic use of authentic materials with listening comprehension and a task design that provides a balance of challenge and support.
Background. Chinese medical entities have not been organized comprehensively due to the lack of well-developed terminology systems, which poses a challenge to processing Chinese medical texts for fine-grained medical knowledge representation. To unify Chinese medical terminologies, mapping Chinese medical entities to their English counterparts in the Unified Medical Language System (UMLS) is an efficient solution. However, their mappings have not been investigated sufficiently in former research. In this study, we explore strategies for mapping Chinese medical entities to the UMLS and systematically evaluate the mapping performance. Methods. First, Chinese medical entities are translated to English using multiple web-based translation engines. Then, 3 mapping strategies are investigated: (a) string-based, (b) semantic-based, and (c) string and semantic similarity combined. In addition, cross-lingual pretrained language models are applied to map Chinese medical entities to UMLS concepts without translation. All of these strategies are evaluated on the ICD10-CN, Chinese Human Phenotype Ontology (CHPO), and RealWorld datasets. Results. The linear combination method based on the SapBERT and term frequency-inverse document frequency bag-of-words models perform the best on all evaluation datasets, with 91.85%, 82.44%, and 78.43% of the top 5 accuracies on the ICD10-CN, CHPO, and RealWorld datasets, respectively. Conclusions. In our study, we explore strategies for mapping Chinese medical entities to the UMLS and identify a satisfactory linear combination method. Our investigation will facilitate Chinese medical entity normalization and inspire research that focuses on Chinese medical ontology development.
Computer applications to medicine. Medical informatics
Abstract Background Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite the paucity of evidence, various complementary, alternative and integrative medicines (CAIMs) have been being touted as both preventative and curative. We conducted sentiment and emotion analysis with the intent of understanding CAIM content related to COVID-19 being generated on Twitter across 9 months. Methods Tweets relating to CAIM and COVID-19 were extracted from the George Washington University Libraries Dataverse Coronavirus tweets dataset from March 03 to November 30, 2020. We trained and tested a machine learning classifier using a large, pre-labelled Twitter dataset, which was applied to predict the sentiment of each CAIM-related tweet, and we used a natural language processing package to identify the emotions based on the words contained in the tweets. Results Our dataset included 28 713 English-language Tweets. The number of CAIM-related tweets during the study period peaked in May 2020, then dropped off sharply over the subsequent three months; the fewest CAIM-related tweets were collected during August 2020 and remained low for the remainder of the collection period. Most tweets (n = 15 612, 54%) were classified as positive, 31% were neutral (n = 8803) and 15% were classified as negative (n = 4298). The most frequent emotions expressed across tweets were trust, followed by fear, while surprise and disgust were the least frequent. Though volume of tweets decreased over the 9 months of the study, the expressed sentiments and emotions remained constant. Conclusion The results of this sentiment analysis enabled us to establish key CAIMs being discussed at the intersection of COVID-19 across a 9-month period on Twitter. Overall, the majority of our subset of tweets were positive, as were the emotions associated with the words found within them. This may be interpreted as public support for CAIM, however, further qualitative investigation is warranted. Such future directions may be used to combat misinformation and improve public health strategies surrounding the use of social media information.
Writing anxiety and academic procrastination are said to be interconnected and have a substantial impact on students’ thesis completion. Self-regulation, on the other hand, is what allows students to make progress while writing their thesis. The goal of this research is to find out how writing anxiety and academic procrastination influence students' thesis writing and how they self-regulate themselves to write their thesis. A quantitative study utilizing descriptive statistics was used to conduct this research. Twelve students in a thesis class expressed their consent to participate in the research. The data was gathered by keeping track of the students' thesis writing progress based on word count development on their research drafts, assigning them to write a standardized weekly journal, and delivering two adapted questionnaires from the self-regulation learning strategy survey. The results suggest that the students had a high level of anxiety, with a score of 65.25, with avoidance behaviour being the highest. They also procrastinate on academic revision and review. Goal planning and requesting help, on the other hand, involve their self-regulation the most, whereas task methods and time management engage in the least. Future researchers are urged to do a further in-depth study on this issue since it is worth researching. Lecturers are also urged to introduce students to different reading and writing techniques.
This article is a mixed method study which examines how a group of six elementary students who study English as a foreign language manage their emotional intelligence while taking their speaking exams. Data were collected through both quantitative and qualitative instruments such as an emotional intelligence test, non-participant observations, surveys, and individual interviews with open-ended questions. The results provide further insight into the students’ emotional intelligence and the coping mechanisms/strategies used to manage their emotional intelligence while taking two different speaking exams.