This paper reports on CATS (2006-2007), a project initiated by the Research Centre Teaching in Multicultural Schools, that addresses language related dropout problems of both native and non-native speakers of Dutch in higher education. The projects main objective is to develop a model for the redesign of the curriculum so as to optimize the development of academic and professional language skills. Key pedagogic strategies are the raising of awareness of personal proficiency levels through diagnostic testing, definition of linguistic demands of curriculum tasks, empowerment of student autonomy and peer feedback procedures. More specifically, this paper deals with two key areas of the project. First, it describes the design and development of web-based corpus software tools, aimed at the enhancement of the autonomy of students academic reading and writing skills. Secondly, it describes the design of three pilots, in which the process of a content and language integrated approach - facilitated by the developed web tools - was applied, and these pilots respective evaluations. The paper concludes with a reflection on the project development and the experiences with the pilot implementations.
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Background to the problem Dutch society demonstrates a development which is apparent in many societies in the 21st century; it is becoming ethnically heterogeneous. This means that children who are secondlanguage speakers of Dutch are learning English, a core curriculum subject, through the medium of the Dutch language. Research questions What are the consequences of this for the individual learner and the class situation?Is a bi-lingual background a help or a hindrance when acquiring further language competences. Does the home situation facilitate or impede the learner? Additionally, how should the TEFL professional respond to this situation in terms of methodology, use of the Dutch language, subject matter and assessment? Method of approach A group of ethnic minority students at Fontys University of Professional Education was interviewed. The interviews were subjected to qualitative analysis. To ensure triangulation lecturers involved in teaching English at F.U.P.E. were asked to fill in a questionnaire on their teaching approach to Dutch second language English learners. Thier response was quantitatively and qualitatively analysed. Findings and conclusions The students encountered surprisingly few problems. Their bi-lingualism and home situation were not a constraint in their English language development. TEFL professionals should bear the heterogeneous classroom in mind when developing courses and lesson material. The introduction to English at primary school level and the assessment of DL2 learners require further research.
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AIM: Little is known about predictive validity of and professionals' adherence to language screening protocols. This study assessed the concurrent and predictive validity of the Dutch well child language screening protocol for two-year-old children and the effects of protocol deviations by professionals.METHODS: A prospective cohort study of 124 children recruited and tested between October 2013 and December 2015. Children were recruited from four well child clinics in urban and rural areas. To validate the screening, we assessed children's language ability with standardized language tests following the two-year screening and one year later. We assessed the concurrent and predictive validity of the screening and of protocol deviations.RESULTS: At two years, the sensitivity and specificity of the language-screening were 0.79 and 0.86, and at three years 0.82 and 0.74, respectively. Protocol deviations by professionals were rare (7%) and did not significantly affect the validity of the screening.CONCLUSION: The language-screening protocol was valid for detecting current and later language problems. Deviations from the protocol by professionals were rare and did not affect the concurrent nor predictive validity of the protocol. The two-year language screening supports professionals working in preventive child health care and deserves wider implementation in well child care.
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The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
-Chatbots are being used at an increasing rate, for instance, for simple Q&A conversations, flight reservations, online shopping and news aggregation. However, users expect to be served as effective and reliable as they were with human-based systems and are unforgiving once the system fails to understand them, engage them or show them human empathy. This problem is more prominent when the technology is used in domains such as health care, where empathy and the ability to give emotional support are most essential during interaction with the person. Empathy, however, is a unique human skill, and conversational agents such as chatbots cannot yet express empathy in nuanced ways to account for its complex nature and quality. This project focuses on designing emotionally supportive conversational agents within the mental health domain. We take a user-centered co-creation approach to focus on the mental health problems of sexual assault victims. This group is chosen specifically, because of the high rate of the sexual assault incidents and its lifetime destructive effects on the victim and the fact that although early intervention and treatment is necessary to prevent future mental health problems, these incidents largely go unreported due to the stigma attached to sexual assault. On the other hand, research shows that people feel more comfortable talking to chatbots about intimate topics since they feel no fear of judgment. We think an emotionally supportive and empathic chatbot specifically designed to encourage self-disclosure among sexual assault victims could help those who remain silent in fear of negative evaluation and empower them to process their experience better and take the necessary steps towards treatment early on.
Psychosocial problems related to social isolation are a growing issue for wellbeing and health and have become a significant societal problem. This is especially relevant for children and adults with chronic illnesses and disabilities, and those spending extended periods in hospitals or permanently living in assisted living facilities. A lack of social relationships, social connectivity, and the inability to travel freely leads to feelings of isolation and loneliness. Loneliness interventions often use mediated environments to improve the feeling of connectedness. It has been proven that the utilization of haptic technologies enhances realism and the sense of presence in both virtual environments and telepresence in physical places by allowing the user to experience interaction through the sense of touch. However, the technology application is mostly limited to the experiences of serious games in professional environments and for-entertainment-gaming. This project aims to explore how haptic technologies can support the storytelling of semi-scripted experiences in VR to improve participants’ sense of presence and, therefore, the feeling of connectedness. By designing and prototyping the experience, the project aims to obtain insights and offer a better understanding of designing haptic-technology-supported storytelling and its potential to improve connectedness and become a useful tool in isolation interventions. The project will be conducted through the process of participants’ co-creation.
