This article explores ways to assess interactional performance, and reports on the use of a test format that standardizes the interlocutor’s linguistic and interactional contributions to the exchange. It describes the construction and administration of six scripted speech tasks (instruction-, advice-, and sales tasks) with pre-vocational learners (n=34), and reports on the extent to which these tasks can be used to assess L2 speakers’ interactional performance in a reliable and valid manner. The high agreement found between three independent raters on both holistic- and analytical measurements of interactional performance, indicate that this construct can be measured reliably with these tasks. Means and standard deviations demonstrate that tasks differentiate between speakers’ interactional performance. Holistic ratings of linguistic accuracy and interactional ability correlate highly between tasks that focus on different language functions, and are situated in different interactional domains. Furthermore, positive correlations are found between both holistic and analytic ratings of oral performance and vocabulary size. Positive within-task correlations between analytical ratings of specific interactional strategies and holistic ratings of overall interactional ability show that analytic ratings of Meaning Negotiation and Correcting Misinterpretation provide additional information about speakers’ interactional ability that is not captured by holistic assessment alone. It is concluded that these tasks are a useful diagnostic tool for practitioners to support their learners’ interactional abilities at a sub-skill level.
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Graphs are ubiquitous. Many graphs, including histograms, bar charts, and stacked dotplots, have proven tricky to interpret. Students’ gaze data can indicate students’ interpretation strategies on these graphs. We therefore explore the question: In what way can machine learning quantify differences in students’ gaze data when interpreting two near-identical histograms with graph tasks in between? Our work provides evidence that using machine learning in conjunction with gaze data can provide insight into how students analyze and interpret graphs. This approach also sheds light on the ways in which students may better understand a graph after first being presented with other graph types, including dotplots. We conclude with a model that can accurately differentiate between the first and second time a student solved near-identical histogram tasks.
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Historical empathy can be helpful when learning history. However, we do not know what students do when completing an empathy-task or how they perceive this type of task. In the explorative study presented in this article, we recognized different types of empathy-tasks, we saw students showing cognitive as well as affective elements in their responses on an empathy task, and we learned that students think that empathy-tasks are mainly useful to remember facts. Students also mentioned comparing the past with the present and imagining other people’s lives as goals of empathy-tasks.
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Teachers have a crucial role in bringing about the extensive social changes that are needed in the building of a sustainable future. In the EduSTA project, we focus on sustainability competences of teachers. We strengthen the European dimension of teacher education via Digital Open Badges as means of performing, acknowledging, documenting, and transferring the competencies as micro-credentials. EduSTA starts by mapping the contextual possibilities and restrictions for transformative learning on sustainability and by operationalising skills. The development of competence-based learning modules and open digital badge-driven pathways will proceed hand in hand and will be realised as learning modules in the partnering Higher Education Institutes and badge applications open for all teachers in Europe.Societal Issue: Teachers’ capabilities to act as active facilitators of change in the ecological transition and to educate citizens and workforce to meet the future challenges is key to a profound transformation in the green transition.Teachers’ sustainability competences have been researched widely, but a gap remains between research and the teachers’ practise. There is a need to operationalise sustainability competences: to describe direct links with everyday tasks, such as curriculum development, pedagogical design, and assessment. This need calls for an urgent operationalisation of educators’ sustainability competences – to support the goals with sustainability actions and to transfer this understanding to their students.Benefit to society: EduSTA builds a community, “Academy of Educators for Sustainable Future”, and creates open digital badge-driven learning pathways for teachers’ sustainability competences supported by multimodal learning modules. The aim is to achieve close cooperation with training schools to actively engage in-service teachers.Our consortium is a catalyst for leading and empowering profound change in the present and for the future to educate teachers ready to meet the challenges and act as active change agents for sustainable future. Emphasizing teachers’ essential role as a part of the green transition also adds to the attractiveness of teachers’ work.
Everyone has the right to participate in society to the best of their ability. This right also applies to people with a visual impairment, in combination with a severe or profound intellectual and possibly motor disability (VISPIMD). However, due to their limitations, for their participation these people are often highly dependent on those around them, such as family members andhealthcare professionals. They determine how people with VISPIMD participate and to what extent. To optimize this support, they must have a good understanding of what people with disabilities can still do with their remaining vision.It is currently difficult to gain insight into the visual abilities of people with disabilities, especially those with VISPIMD. As a professional said, "Everything we can think of or develop to assess the functional vision of this vulnerable group will help improve our understanding and thus our ability to support them. Now, we are more or less guessing about what they can see.Moreover, what little we know about their vision is hard to communicate to other professionals”. Therefore, there is a need for methods that can provide insight into the functional vision of people with VISPIMD, in order to predict their options in daily life situations. This is crucial knowledge to ensure that these people can participate in society to their fullest extent.What makes it so difficult to get this insight at the moment? Visual impairments can be caused by a range of eye or brain disorders and can manifest in various ways. While we understand fairly well how low vision affects a person's abilities on relatively simple visual tasks, it is much more difficult to predict this in more complex dynamic everyday situations such asfinding your way or moving around during daily activities. This is because, among other things, conventional ophthalmic tests provide little information about what people can do with their remaining vision in everyday life (i.e., their functional vision).An additional problem in assessing vision in people with intellectual disabilities is that many conventional tests are difficult to perform or are too fatiguing, resulting in either no or the wrong information. In addition to their visual impairment, there is also a very serious intellectual disability (possibly combined with a motor impairment), which makes it even more complex to assesstheir functional vision. Due to the interplay between their visual, intellectual, and motor disabilities, it is almost impossible to determine whether persons are unable to perform an activity because they do not see it, do not notice it, do not understand it, cannot communicate about it, or are not able to move their head towards the stimulus due to motor disabilities.Although an expert professional can make a reasonable estimate of the functional possibilities through long-term and careful observation, the time and correct measurement data are usually lacking to find out the required information. So far, it is insufficiently clear what people with VZEVMB provoke to see and what they see exactly.Our goal with this project is to improve the understanding of the visual capabilities of people with VISPIMD. This then makes it possible to also improve the support for participation of the target group. We want to achieve this goal by developing and, in pilot form, testing a new combination of measurement and analysis methods - primarily based on eye movement registration -to determine the functional vision of people with VISPIMD. Our goal is to systematically determine what someone is responding to (“what”), where it may be (“where”), and how much time that response will take (“when”). When developing methods, we take the possibilities and preferences of the person in question as a starting point in relation to the technological possibilities.Because existing technological methods were originally developed for a different purpose, this partly requires adaptation to the possibilities of the target group.The concrete end product of our pilot will be a manual with an overview of available technological methods (as well as the methods themselves) for assessing functional vision, linked to the specific characteristics of the target group in the cognitive, motor area: 'Given that a client has this (estimated) combination of limitations (cognitive, motor and attention, time in whichsomeone can concentrate), the order of assessments is as follows:' followed by a description of the methods. We will also report on our findings in a workshop for professionals, a Dutch-language article and at least two scientific articles. This project is executed in the line: “I am seen; with all my strengths and limitations”. During the project, we closely collaborate with relevant stakeholders, i.e. the professionals with specific expertise working with the target group, family members of the persons with VISPIMD, and persons experiencing a visual impairment (‘experience experts’).
The focus of the research is 'Automated Analysis of Human Performance Data'. The three interconnected main components are (i)Human Performance (ii) Monitoring Human Performance and (iii) Automated Data Analysis . Human Performance is both the process and result of the person interacting with context to engage in tasks, whereas the performance range is determined by the interaction between the person and the context. Cheap and reliable wearable sensors allow for gathering large amounts of data, which is very useful for understanding, and possibly predicting, the performance of the user. Given the amount of data generated by such sensors, manual analysis becomes infeasible; tools should be devised for performing automated analysis looking for patterns, features, and anomalies. Such tools can help transform wearable sensors into reliable high resolution devices and help experts analyse wearable sensor data in the context of human performance, and use it for diagnosis and intervention purposes. Shyr and Spisic describe Automated Data Analysis as follows: Automated data analysis provides a systematic process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions and supporting decision making for further analysis. Their philosophy is to do the tedious part of the work automatically, and allow experts to focus on performing their research and applying their domain knowledge. However, automated data analysis means that the system has to teach itself to interpret interim results and do iterations. Knuth stated: Science is knowledge which we understand so well that we can teach it to a computer; and if we don't fully understand something, it is an art to deal with it.[Knuth, 1974]. The knowledge on Human Performance and its Monitoring is to be 'taught' to the system. To be able to construct automated analysis systems, an overview of the essential processes and components of these systems is needed.Knuth Since the notion of an algorithm or a computer program provides us with an extremely useful test for the depth of our knowledge about any given subject, the process of going from an art to a science means that we learn how to automate something.
