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
The present study investigated whether text structure inference skill (i.e., the ability to infer overall text structure) has unique predictive value for expository text comprehension on top of the variance accounted for by sentence reading fluency, linguistic knowledge and metacognitive knowledge. Furthermore, it was examined whether the unique predictive value of text structure inference skill differs between monolingual and bilingual Dutch students or students who vary in reading proficiency, reading fluency or linguistic knowledge levels. One hundred fifty-one eighth graders took tests that tapped into their expository text comprehension, sentence reading fluency, linguistic knowledge, metacognitive knowledge, and text structure inference skill. Multilevel regression analyses revealed that text structure inference skill has no unique predictive value for eighth graders’ expository text comprehension controlling for reading fluency, linguistic knowledge and metacognitive knowledge. However, text structure inference skill has unique predictive value for expository text comprehension in models that do not include both knowledge of connectives and metacognitive knowledge as control variables, stressing the importance of these two cognitions for text structure inference skill. Moreover, the predictive value of text structure inference skill does not depend on readers’ language backgrounds or on their reading proficiency, reading fluency or vocabulary knowledge levels. We conclude our paper with the limitations of our study as well as the research and practical implications.
Research into automatic text simplification aims to promote access to information for all members of society. To facilitate generalizability, simplification research often abstracts away from specific use cases, and targets a prototypical reader and an underspecified content creator. In this paper, we consider a real-world use case – simplification technology for use in Dutch municipalities – and identify the needs of the content creators and the target audiences in this scenario. The stakeholders envision a system that (a) assists the human writer without taking over the task; (b) provides diverse outputs, tailored for specific target audiences; and (c) explains the suggestions that it outputs. These requirements call for technology that is characterized by modularity, explainability, and variability. We argue that these are important research directions that require further exploration
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During the coronavirus pandemic, the use of eHealth tools became increasingly demanded by patients and encouraged by the Dutch government. Yet, HBO health professionals demand clarity on what they can do, must do, and cannot do with the patients’ data when using digital healthcare provision and support. They often perceive the EU GDPR and its national application as obstacles to the use of eHealth due to strict health data processing requirements. They highlight the difficulty of keeping up with the changing rules and understanding how to apply them. Dutch initiatives to clarify the eHealth rules include the 2021 proposal of the wet Elektronische Gegevensuitwisseling in de Zorg and the establishment of eHealth information and communication platforms for healthcare practitioners. The research explores whether these initiatives serve the needs of HBO health professionals. The following questions will be explored: - Do the currently applicable rules and the proposed wet Elektronische Gegevensuitwisseling in de Zorg clarify what HBO health practitioners can do, must do, and cannot do with patients’ data? - Does the proposed wet Elektronische Gegevensuitwisseling in de Zorg provide better clarity on the stakeholders who may access patients’ data? Does it ensure appropriate safeguards against the unauthorized use of such data? - Does the proposed wet Elektronische Gegevensuitwisseling in de Zorg clarify the EU GDPR requirements for HBO health professionals? - Do the eHealth information and communication platforms set up for healthcare professionals provide the information that HBO professionals need on data protection and privacy requirements stemming from the EU GDPR and from national law? How could such platforms be better adjusted to the HBO professionals’ information and communication needs? Methodology: Practice-oriented legal research, semi-structured interviews and focus group discussions will be conducted. Results will be translated to solutions for HBO health professionals.
