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"Language Patterns"
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Family language patterns in bilingual families and relationships with children’s language outcomes
Past research shows that family language patterns (i.e., which languages are spoken in the family and by whom) are associated with bilingual children’s language use. However, it is unclear how input properties such as input quantity, parental proficiency, and language mixing may differ across family language patterns. It is also unclear whether the effects of family language patterns on children’s language proficiency remain when differences in input properties are controlled. We investigated (i) which family language patterns occurred in bilingual families in the Netherlands (n = 136), (ii) whether input properties differed across patterns, and (iii) how patterns related to children’s proficiency, once input properties were controlled. Home language situations were assessed through a questionnaire, children’s proficiency in Dutch and the minority language through vocabulary tests and parent ratings. Three language patterns were found: one-parent-one-language, both parents mixed languages or used the minority language. The results showed differences in input properties across all patterns, as well as effects of these patterns on children’s proficiency in Dutch and the minority language that disappeared once input properties were controlled. These findings do not provide robust evidence that family language patterns predict children’s proficiency, but rather, that input quantity is crucial.
Journal Article
Developing Strategies to Improve Textbook Design Using Synergy of Native and Learner Corpora
The research aims to enhance the handling of modal verbs (MVs) in EFL textbooks by leveraging perspectives from corpora that include both native speakers’ language data and the language data of individuals who are learning the language. To assess the authenticity of language in textbooks, an analysis between the native corpus and a collection of language data compiled from textbook is conducted. The research delves into the developmental patterns of MV usage among learners through a stratified analysis of student essays (Grades 7, 8, 9). Comparisons between learner patterns and a graded textbook series are made to ascertain potential correlations. A novel aspect of the examination explores how the salience and complexity of L2 forms and functions shape the impact of EFL textbooks on learner production. Findings reveal significant differences in the use of MVs between EFL textbooks and the British National Corpus (BNC). Moreover, analysis of student essays indicates a substantial influence of textbooks on learners’ MV usage. The study proposes strategies to enhance EFL textbook design, advocating for authenticity and learner-centric approaches. Utilizing native and learner corpora facilitates targeted instruction, addressing common errors and challenges. The incorporation of authentic language examples from the native corpus is recommended to expose learners to real-world language use. This research underscores the significance of integrating native and learner corpora insights in EFL textbook design, ultimately fostering more effective language learning outcomes.
Journal Article
Design patterns in modern C++ : reusable approaches for object-oriented software design
Apply modern C++17 to the implementations of classic design patterns. As well as covering traditional design patterns, this book fleshes out new patterns and approaches that will be useful to C++ developers. The author presents concepts as a fun investigation of how problems can be solved in different ways, along the way using varying degrees of technical sophistication and explaining different sorts of trade-offs. \"Design patterns in modern C++\" also provides a technology demo for modern C++, showcasing how some of its latest features (e.g., coroutines) make difficult problems a lot easier to solve. The examples in this book are all suitable for putting into production, with only a few simplifications made in order to aid readability. You will: Apply design patterns to modern C++ programming ; Use creational patterns of builder, factories, prototype and singleton ; Implement structural patterns such as adapter, bridge, decorator, facade and more ; Work with the behavioral patterns such as chain of responsibility, command, iterator, mediator and more ; Apply functional design patterns such as Monad and more.
Book
The use of a second language enhances the neural efficiency of inhibitory control: An ERP study
This study investigated how natural language use influences inhibition in language-unbalanced bilinguals. We experimentally induced natural patterns of language use (as proposed by the Adaptive Control Hypothesis) and assessed their cognitive after-effects in a group of 32 Polish–English bilinguals. Each participant took part in a series of three language games involving real conversation. Each game was followed by two inhibition tasks (stop-signal task and Stroop task). The manipulation of language use in the form of language games did not affect the behavioural measures, but it did affect ERPs. Performance of the inhibition tasks was accompanied by a reduction of P3 and the N450 amplitude differences after games involving the use of L2. The ERP modulations suggest that for bilinguals living in an L1 context the use of L2 enhances neural mechanisms related to inhibition. The study provides the first evidence for a direct influence of natural language use on inhibition.
Journal Article
A comparative analysis of selected recommendations of the feng shui school of form, Alexander et al.’s pattern language, and findings of environmental psychology
Feng shui is a traditional Chinese art of creating a supportive living environment. Despite many research contributions on feng shui, very few verify (comparatively or experimentally) the actual effectiveness of feng shui recommendations. Even the architectural profession has never clearly denied its opinion on feng shui. is comparative analysis seeks to determine whether 118 selected feng shui school of form recommendations are consistent with the recommendations of Alexander et al.’s pattern language and with selected findings in environmental psychology. The results support this, showing that 34% of the recommendations (or forty recommendations out of 118 in total) are consistent with pattern language and that 45% (or fifty-three recommendations) are fully or partially consistent with the findings of environmental psychology. Altogether, more than half of the recommendations (57%, or sixty-seven recommendations) are consistent (indirectly confirmed) by one or the other knowledge system, which means that it is very likely that these recommendations will actually have the promised impact on users of physical space. Twenty-seven feng shui recommendations (or 23% out of the 118) are doubly consistent, of which most are related to the five-animals feng shui model, the importance of the presence of water and natural light in the living environment, and the importance of the main entrance. The bulk of the recommendations, which remain unaddressed, relate to the Chinese concept of living energy, or qi.
Journal Article
A resource-rational model of human processing of recursive linguistic structure
A major goal of psycholinguistic theory is to account for the cognitive constraints limiting the speed and ease of language comprehension and production. Wide-ranging evidence demonstrates a key role for linguistic expectations: A word’s predictability, as measured by the information-theoretic quantity of surprisal, is a major determinant of processing difficulty. But surprisal, under standard theories, fails to predict the difficulty profile of an important class of linguistic patterns: the nested hierarchical structures made possible by recursion in human language. These nested structures are better accounted for by psycholinguistic theories of constrained working memory capacity. However, progress on theory unifying expectation-based and memory-based accounts has been limited. Here we present a unified theory of a rational trade-off between precision of memory representations with ease of prediction, a scaled-up computational implementation using contemporary machine learning methods, and experimental evidence in support of the theory’s distinctive predictions. We show that the theory makes nuanced and distinctive predictions for difficulty patterns in nested recursive structures predicted by neither expectation-based nor memory-based theories alone. These predictions are confirmed 1) in two language comprehension experiments in English, and 2) in sentence completions in English, Spanish, and German. More generally, our framework offers computationally explicit theory and methods for understanding how memory constraints and prediction interact in human language comprehension and production.
Journal Article
Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and BERT-NLI
Supervised machine learning is an increasingly popular tool for analyzing large political text corpora. The main disadvantage of supervised machine learning is the need for thousands of manually annotated training data points. This issue is particularly important in the social sciences where most new research questions require new training data for a new task tailored to the specific research question. This paper analyses how deep transfer learning can help address this challenge by accumulating “prior knowledge” in language models. Models like BERT can learn statistical language patterns through pre-training (“language knowledge”), and reliance on task-specific data can be reduced by training on universal tasks like natural language inference (NLI; “task knowledge”). We demonstrate the benefits of transfer learning on a wide range of eight tasks. Across these eight tasks, our BERT-NLI model fine-tuned on 100 to 2,500 texts performs on average 10.7 to 18.3 percentage points better than classical models without transfer learning. Our study indicates that BERT-NLI fine-tuned on 500 texts achieves similar performance as classical models trained on around 5,000 texts. Moreover, we show that transfer learning works particularly well on imbalanced data. We conclude by discussing limitations of transfer learning and by outlining new opportunities for political science research.
Journal Article