Posterpresentatie op Conferentie. Introduction: Classifiers are handshapes (sometimes combined with a specific orientation) that, when combined with the other parameters of movement and location form a ‘verb of motion or location’. There is a limited body of research available on the acquisition of classifiers by children. The available studies have focused on deaf children of deaf (DOD) parents, who are native signers. Results show that classifiers emerge at 3 years and approach an adult like level at the age of 9 (Beal Alvarez & Easterbrooks, 2013). This small study was set out to investigate the production of classifiers in DOH children who acquire Sign Language of the Netherlands. Our expectation was that DOH children produce classifiers, but fail to use them correctly in all instances due to lack of pragmatic control (Slobin et al., 2003). Method: Four children (two girls, two boys) were recruited at a school for the Deaf in The Netherlands (5;10 – 6;8 years). All children were deaf or severely hearing-impaired from birth. Children used (sign supported) Dutch at home and sign language at school and had approximately three years of exposure to sign language. Narratives (Frog-story) were recorded. The recordings were transcribed and analyzed using ELAN-software. Analysis focused on type of classifier (entity and handling) and accuracy in production. Results: The children produced 22 classifiers in total, 20 entity classifiers and 2 handling classifiers. Ten percent of the entity classifiers was incorrect; the handshape to express the entity did not match the handshape frequently selected for that entity. Conclusion: DOH children produce classifiers after three years of exposure to sign language. Errors in classifier production involved errors in handshape selection. This compares to type of errors frequently found for DOD children. Results will be discussed in relation to the iconic and gestural properties of classifiers (Cormier et al., 2012). References: Beal-Alvarez, J.S. & Easterbrooks, S.R. (2013). Increasing children’s ASL classifier production: A multicomponent intervention. American Annals of the Deaf, 158, 311 – 333. Cormier, K., Quinto-Pozos, D., Sevcikova, Z., Schembri, A. (2012). Lexicalisation and de-lexicalisation processes in sign languages: Comparing depicting constructions and viewpoint gestures. Language & Communication, 32, 329 – 348. Slobin, D., Hoiting, N., Kuntze, K., Lindert, R., Weinberg, A. Pyers, J., Anthony, M., Biederman, Y., Thumann, H. (2003). A cognitive/functional perspective on the acquisition of ‘classifiers’. In: Emmorey, K. (Ed.). Perspectives on classifier constructions in sign languages. Lawrence Erlbaum Associates, Mahwah, NJ. Pp 297 – 310.
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Full text met HU account Although people all over the world learn sign languages as a second language (SL2), there is scant literature on sign language acquisition processes to guide professionals in the field. This study focuses on one of the modality-specific phenomena that SL2 learners with a spoken language background encounter that do not exist in their native language (L1): the use of space for grammatical reasons. We analyzed the sign language production data of two learners of Sign Language of the Netherlands (NGT) who we followed for four years. Data comprise interviews that were coded for use of space. Use of space was operationalized by measuring the number of occasions of pointing signs, agreement verbs, classifier verbs, and spatially modified signs from the nominal domain. In addition, we identified examples of typical L2 signing (e.g. errors of overgeneralization, omissions, et cetera). Data show that learners initially produce modified signs that have a gestural counterpart. It might be that they "borrow" signs from the gestural domain, or they produce these highly iconic structures because their gestural inventory has helped them to acquire these structures. Furthermore, the data show that particularly classifier verbs and agreement verbs within a constructed action sequence pose challenges for the learners, and we observed some general error patterns that have been found in L1-learners, such as stacking and reversing the movement path of agreement verbs
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Teacher beliefs have been shown to play a major role in shaping educational practice, especially in the area of grammar teaching―an area of language education that teachers have particularly strong views on. Traditional grammar education is regularly criticized for its focus on rules-of-thumb rather than on insights from modern linguistics, and for its focus on lower order thinking. A growing body of literature on grammar teaching promotes the opposite, arguing for more linguistic conceptual knowledge and reflective or higher order thinking in grammar pedagogy. In the Netherlands, this discussion plays an important role in the national development of a new curriculum. This study explores current Dutch teachers’ beliefs on the use of modern linguistic concepts and reflective judgment in grammar teaching. To this end, we conducted a questionnaire among 110 Dutch language teachers from secondary education and analyzed contemporary school textbooks likely to reflect existing teachers’ beliefs. Results indicate that teachers generally appear to favor stimulating reflective judgement in grammar teaching, although implementing activities aimed at fostering reflective thinking seems to be difficult for two reasons: (1) existing textbooks fail to implement sufficient concepts from modern linguistics, nor do they stimulate reflective thinking; (2) teachers lack sufficient conceptual knowledge from linguistics necessary to adequately address reflective thinking.
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The security of online assessments is a major concern due to widespread cheating. One common form of cheating is impersonation, where students invite unauthorized persons to take assessments on their behalf. Several techniques exist to handle impersonation. Some researchers recommend use of integrity policy, but communicating the policy effectively to the students is a challenge. Others propose authentication methods like, password and fingerprint; they offer initial authentication but are vulnerable thereafter. Face recognition offers post-login authentication but necessitates additional hardware. Keystroke Dynamics (KD) has been used to provide post-login authentication without any additional hardware, but its use is limited to subjective assessment. In this work, we address impersonation in assessments with Multiple Choice Questions (MCQ). Our approach combines two key strategies: reinforcement of integrity policy for prevention, and keystroke-based random authentication for detection of impersonation. To the best of our knowledge, it is the first attempt to use keystroke dynamics for post-login authentication in the context of MCQ. We improve an online quiz tool for the data collection suited to our needs and use feature engineering to address the challenge of high-dimensional keystroke datasets. Using machine learning classifiers, we identify the best-performing model for authenticating the students. The results indicate that the highest accuracy (83%) is achieved by the Isolation Forest classifier. Furthermore, to validate the results, the approach is applied to Carnegie Mellon University (CMU) benchmark dataset, thereby achieving an improved accuracy of 94%. Though we also used mouse dynamics for authentication, but its subpar performance leads us to not consider it for our approach.
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This doctoral thesis describes three case studies of service engineers participating in organizational change, interacting with managers and consultants. The study investigates the role of differences in professional discourse and culture when these three professional groups interact in organizational change, and how this affects the change result. We bring together two scientific fields, first change management and second, linguistics. The intersection represents the overlapping field of professional discourse and culture. The research design was an explorative multiple case study using qualitative linguistic analyses. The study found that successful organizational change is the result of interaction between professional culture, the organizational culture and the organization/change context. The differences between the professional cultures and discourses can hamper the change process. The practical contribution of this study might be the increased awareness among professionals about their own professional, and often implicit, assumptions. Managers, consultants and service engineers have to be aware of the group dynamics and the specific role of their own typical professional discourse and culture in a change project setting.
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The aim of this dissertation is to examine how adult learners with a spoken language background who are acquiring a signed language, learn how to use the space in front of the body to express grammatical and topographical relations. Moreover, it aims at investigating the effectiveness of different types of instruction, in particular instruction that focuses the learner's attention on the agreement verb paradigm. To that end, existing data from a learner corpus (Boers-Visker, Hammer, Deijn, Kielstra & Van den Bogaerde, 2016) were analyzed, and two novel experimental studies were designed and carried out. These studies are described in detail in Chapters 3–6. Each chapter has been submitted to a scientific journal, and accordingly, can be read independently.1 Yet, the order of the chapters follows the chronological order in which the studies were carried out, and the reader will notice that each study served as a basis to inform the next study. As such, some overlap in the sections describing the theoretical background of each study was unavoidable.
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In this paper we describe our work in progress on the development of a set of criteria to predict text difficulty in Sign Language of the Netherlands (NGT). These texts are used in a four year bachelor program, which is being brought in line with the Common European Framework of Reference for Languages (Council of Europe, 2001). Production and interaction proficiency are assessed through the NGT Functional Assessment instrument, adapted from the Sign Language Proficiency Interview (Caccamise & Samar, 2009). With this test we were able to determine that after one year of NGT-study students produce NGT at CEFR-level A2, after two years they sign at level B1, and after four years they are proficient in NGT on CEFR-level B2. As a result of that we were able to identify NGT texts that were matched to the level of students at certain stages in their studies with a CEFR-level. These texts were then analysed for sign familiarity, morpheme-sign rate, use of space and use of non-manual signals. All of these elements appear to be relevant for the determination of a good alignment between the difficulty of NGT signed texts and the targeted CEFR level, although only the morpheme-sign rate appears to be a decisive indicator
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From the introduction: "There are two variants of fronto-temporal dementia: a behavioral variant (behavioral FTD, bvFTD, Neary et al. (1998)), which causes changes in behavior and personality but leaves syntax, phonology and semantics relatively intact, and a variant that causes impairments in the language processing system (Primary Progessive Aphasia, PPA (Gorno-Tempini et al., 2004). PPA can be subdivided into subtypes fluent (fluent but empty speech, comprehension of word meaning is affected / `semantic dementia') and non-fluent (agrammatism, hesitant or labored speech, word finding problems). Some identify logopenic aphasia as a FTD-variant: fluent aphasia with anomia but intact object recognition and underlying word meaning."
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ion of verb agreement by hearing learners of a sign language. During a 2-year period, 14 novel learners of Sign Language of the Netherlands (NGT) with a spoken language background performed an elicitation task 15 times. Seven deaf native signers and NGT teachers performed the same task to serve as a benchmark group. The results obtained show that for some learners, the verb agreement system of NGT was difficult to master, despite numerous examples in the input. As compared to the benchmark group, learners tended to omit agreement markers on verbs that could be modified, did not always correctly use established locations associated with discourse referents, and made characteristic errors with respect to properties that are important in the expression of agreement (movement and orientation). The outcomes of the study are of value to practitioners in the field, as they are informative with regard to the nature of the learning process during the first stages of learning a sign language.
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Objective:Acknowledging study limitations in a scientific publication is a crucial element in scientific transparency and progress. However, limitation reporting is often inadequate. Natural language processing (NLP) methods could support automated reporting checks, improving research transparency. In this study, our objective was to develop a dataset and NLP methods to detect and categorize self-acknowledged limitations (e.g., sample size, blinding) reported in randomized controlled trial (RCT) publications.Methods:We created a data model of limitation types in RCT studies and annotated a corpus of 200 full-text RCT publications using this data model. We fine-tuned BERT-based sentence classification models to recognize the limitation sentences and their types. To address the small size of the annotated corpus, we experimented with data augmentation approaches, including Easy Data Augmentation (EDA) and Prompt-Based Data Augmentation (PromDA). We applied the best-performing model to a set of about 12K RCT publications to characterize self-acknowledged limitations at larger scale.Results:Our data model consists of 15 categories and 24 sub-categories (e.g., Population and its sub-category DiagnosticCriteria). We annotated 1090 instances of limitation types in 952 sentences (4.8 limitation sentences and 5.5 limitation types per article). A fine-tuned PubMedBERT model for limitation sentence classification improved upon our earlier model by about 1.5 absolute percentage points in F1 score (0.821 vs. 0.8) with statistical significance (). Our best-performing limitation type classification model, PubMedBERT fine-tuning with PromDA (Output View), achieved an F1 score of 0.7, improving upon the vanilla PubMedBERT model by 2.7 percentage points, with statistical significance ().Conclusion:The model could support automated screening tools which can be used by journals to draw the authors’ attention to reporting issues. Automatic extraction of limitations from RCT publications could benefit peer review and evidence synthesis, and support advanced methods to search and aggregate the evidence from the clinical trial literature.
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