An ERP study on L2 syntax processing: When do learners fail?
TL;DR: The results confirm the persistent problems of Romance learners of Dutch with online gender processing and show that they cannot be overcome by reducing task demands related to the modality of stimulus presentation.
Abstract: Event-related brain potentials (ERPs) can reveal online processing differences between native speakers and second language (L2) learners during language comprehension. Using the P600 as a measure of native-likeness, we investigated processing of grammatical gender agreement in highly proficient immersed Romance L2 learners of Dutch. We demonstrate that these late learners consistently fail to show native-like sensitivity to gender violations. This appears to be due to a combination of differences from the gender marking in their L1 and the relatively opaque Dutch gender system. We find that L2 use predicts the effect magnitude of non-finite verb violations, a relatively regular and transparent construction, but not that of gender agreement violations. There were no effects of age of acquisition, length of residence, proficiency or offline gender knowledge. Additionally, a within-subject comparison of stimulus modalities (written vs. auditory) shows that immersed learners may show some of the effects only in the auditory modality; in non-finite verb violations, an early native-like N400 was only present for auditory stimuli. However, modality failed to influence the response to gender. Taken together, the results confirm the persistent problems of Romance learners of Dutch with online gender processing and show that they cannot be overcome by reducing task demands related to the modality of stimulus presentation.
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TL;DR: The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models to enable researchers and students alike to reproduce the analyses and learn by doing.
Abstract: The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this
1,679 citations
TL;DR: It is shown how an effort account of pupil dilation can provide an explanation of these findings and future directions to further corroborate this account are discussed in the context of recent theories on cognitive control and effort and their potential neurobiological substrates.
Abstract: Pupillometry research has experienced an enormous revival in the last two decades. Here we briefly review the surge of recent studies on task-evoked pupil dilation in the context of cognitive control tasks with the primary aim being to evaluate the feasibility of using pupil dilation as an index of effort exertion, rather than task demand or difficulty. Our review shows that across the three cognitive control domains of updating, switching, and inhibition, increases in task demands typically leads to increases in pupil dilation. Studies show a diverging pattern with respect to the relationship between pupil dilation and performance and we show how an effort account of pupil dilation can provide an explanation of these findings. We also discuss future directions to further corroborate this account in the context of recent theories on cognitive control and effort and their potential neurobiological substrates.
371 citations
TL;DR: The School Barometer, a fast survey that was conducted in Germany, Austria and Switzerland during the early weeks of the school lockdown to assess and evaluate the current school situation caused by COVID-19, is presented and discussed.
Abstract: The crisis caused by the COVID-19 virus has far-reaching effects in the field of education, as schools were closed in March 2020 in many countries around the world. In this article, we present and discuss the School Barometer, a fast survey (in terms of reaction time, time to answer and dissemination time) that was conducted in Germany, Austria and Switzerland during the early weeks of the school lockdown to assess and evaluate the current school situation caused by COVID-19. Later, the School Barometer was extended to an international survey, and some countries conducted the survey in their own languages. In Germany, Austria and Switzerland, 7116 persons participated in the German language version: 2222 parents, 2152 students, 1949 school staff, 655 school leaders, 58 school authority and 80 members of the school support system. The aim was to gather, analyse and present data in an exploratory way to inform policy, practice and further research. In this article, we present some exemplary first results and possible implications for policy, practice and research. Furthermore, we reflect on the strengths and limitations of the School Barometer and fast surveys as well as the methodological options for data collection and analysis when using a short monitoring survey approach. Specifically, we discuss the methodological challenges associated with survey data of this kind, including challenges related to hypothesis testing, the testing of causal effects and approaches to ensure reliability and validity. By doing this, we reflect on issues of assessment, evaluation and accountability in times of crisis.
268 citations
Temple University1, King Abdulaziz University2, Brock University3, University of California, Los Angeles4, Seconda Università degli Studi di Napoli5, University of Macau6, University of Delhi7, Duke University8, University of Cyprus9, Maseno University10, University College West11, Chiang Mai University12, Ateneo de Manila University13, Hashemite University14
TL;DR: Testing in an international sample of more than 5000 individuals between ages 10 and 30 years from 11 countries in Africa, Asia, Europe and the Americas finds that sensation seeking increased between preadolescence and late adolescence, peaked at age 19, and declined thereafter, whereas self-regulation increased steadily from preadolescentence into young adulthood, reaching a plateau between ages 23 and 26.
Abstract: The dual systems model of adolescent risk-taking portrays the period as one characterized by a combination of heightened sensation seeking and still-maturing self-regulation, but most tests of this model have been conducted in the United States or Western Europe. In the present study, these propositions are tested in an international sample of more than 5000 individuals between ages 10 and 30 years from 11 countries in Africa, Asia, Europe and the Americas, using a multi-method test battery that includes both self-report and performance-based measures of both constructs. Consistent with the dual systems model, sensation seeking increased between preadolescence and late adolescence, peaked at age 19, and declined thereafter, whereas self-regulation increased steadily from preadolescence into young adulthood, reaching a plateau between ages 23 and 26. Although there were some variations in the magnitude of the observed age trends, the developmental patterns were largely similar across countries.
264 citations
TL;DR: This survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress.
Abstract: In this paper we present a broad overview of the last 40 years of research on cognitive architectures To date, the number of existing architectures has reached several hundred, but most of the existing surveys do not reflect this growth and instead focus on a handful of well-established architectures In this survey we aim to provide a more inclusive and high-level overview of the research on cognitive architectures Our final set of 84 architectures includes 49 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, action selection, memory, learning, reasoning and metareasoning In order to assess the breadth of practical applications of cognitive architectures we present information on over 900 practical projects implemented using the cognitive architectures in our list We use various visualization techniques to highlight the overall trends in the development of the field In addition to summarizing the current state-of-the-art in the cognitive architecture research, this survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress
259 citations
References
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Journal Article•
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
272,030 citations
"An ERP study on L2 syntax processin..." refers methods in this paper
...For grand mean analyses, ANOVAs were calculated within each time window and sentence structure (non-finite verb, grammatical gender) separately, using the ezANOVA function of the ez package (version 4.2.2: Lawrence, 2013), implemented in R (version 3.1.0: R Core Team, 2014)....
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TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Abstract: SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
83,420 citations
"An ERP study on L2 syntax processin..." refers methods in this paper
...False discovery rate correction (Benjamini and Hochberg, 1995) was applied for follow-up tests to control for Type 1 error....
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TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Abstract: The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum information theoretical criterion (AIC) estimate (MAICE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the MAICE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of AIC defined by AIC = (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAICE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utility of MAICE in time series analysis is demonstrated with some numerical examples.
47,133 citations
"An ERP study on L2 syntax processin..." refers background or methods in this paper
...The significance of predictors was evaluated by means of the t-test for the coefficients, in addition to model comparison using AIC (Akaike Information Criterion; Akaike, 1974)....
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...REFERENCES Akaike, H. (1974). A new look at the statistical model identification....
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01 Jan 2011
TL;DR: In this paper, the authors reviewed the history of statistical hypothesis testing in time series analysis and pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification.
Abstract: The history of the development of statistical hypothesis testing in time series analysis is reviewed briefty and it is pointed out that the hypothesis testing procedure i. not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum informatioD theoretical criterion (AlC) estimate (MAleE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the M.AleE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of Ale defined by Ale ~ (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAleE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utllity of MAIeE in time series analysis is demonstrated with some numerical
4,406 citations
Book•
29 Jun 2005TL;DR: In this paper, a taxonomy of individual differences is presented, including personality, temperament, and mood, and self-motivation, self-regulation, and language learning strategies.
Abstract: Contents: Preface. Introduction: Definition, Brief History, and Taxonomy of Individual Differences. Personality, Temperament, and Mood. Language Aptitude. Motivation and "Self-Motivation." Learning Styles and Cognitive Styles. Language Learning Strategies and Student Self-Regulation. Other Learner Characteristics. Conclusion.
3,175 citations
"An ERP study on L2 syntax processin..." refers background in this paper
...Other potential explanatory factors involve the language experience of the learner, such as age of acquisition (Weber-Fox and Neville, 1996; Kotz et al., 2008) and exposure to and use of the L2 (Gardner et al., 1997; Flege et al., 1999; Dörnyei, 2005; Tanner et al., 2014)....
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