Abstract The aim of this cross-sectional study was to develop a Frailty at Risk Scale (FARS) incorporating ten well-known determinants of frailty: age, sex, marital status, ethnicity, education, income, lifestyle, multimorbidity, life events, and home living environment. In addition, a second aim was to develop an online calculator that can easily support healthcare professionals in determining the risk of frailty among community-dwelling older people. The FARS was developed using data of 373 people aged ≥ 75 years. The Tilburg Frailty Indicator (TFI) was used for assessing frailty. Multivariate logistic regression analysis showed that the determinants multimorbidity, unhealthy lifestyle, and ethnicity (ethnic minority) were the most important predictors. The area under the curve (AUC) of the model was 0.811 (optimism 0.019, 95% bootstrap CI = −0.029; 0.064). The FARS is offered on a Web site, so that it can be easily used by healthcare professionals, allowing quick intervention in promoting quality of life among community-dwelling older people.
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In March 2020 schools in The Netherlands closed to contain the spread of Covid-19 virus. Shortly after, schools took to online education. The condensed setting of the Covid-19 situation provided a background to study which learning activities and tools teachers choose in online education and how they use them to promote interaction. Interaction is quintessential to learning but in online education it is not easy to provide room for interaction. Our central research question therefore is how interaction within online education activities change over time. An online longitudinal survey amongst teachers was conducted. The first four rounds took place in the early stages of the lockdowns and shortly after. In total 179 different secondary school teachers participated of whom 16 responded three rounds or more. Most teachers use tools in online education that can facilitate more interaction than necessary for the Instructional Design. This means that improving interaction in online education is more a pedagogical challenge than a technical one. It was also found that teachers who deploy Instructional Designs that require more interaction use more and different tools. However, only few of these tools seem to facilitate the interactive quality the teachers pursued. Over time we saw the interactive quality of Instructional Design and tools converge. We are in awe of the artful way in which some teachers manage to combine the possibilities of different tools to establish high interactive quality in the online learning processes they conduct.
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The purpose of this paper is to reflect on the experiences of safety and security management students, enrolled in an undergraduate course in the Netherlands, and present quantitative data from an online survey that aimed to explore the factors that have contributed to students’ satisfaction with, and engagement in, online classes during the COVID-19 pandemic. The main findings suggest an interesting paradox of technology, which is worth further exploration in future research. Firstly, students with self perceived higher technological skill levels tend to reject online education more often as they see substantial shortcomings of classes in the way they are administered as compared to the vast available opportunities for real innovation. Secondly, as opposed to democratising education and allowing for custom-made, individualistic education schedules that help less-privileged students, online education can also lead to the displacement of education by income-generating activities altogether. Lastly, as much as technology allowed universities during the COVID-19 pandemic to continue with education, the transition to the environment, which is defined by highly interactive and engaging potential, may in fact be a net contributor to the feelings of social isolation, digital educational inequality and tension around commercialisation in higher education.
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Blended learning, a teaching format in which face-to-face and online learning is integrated, nowadays is an important development in education. Little is known, however, about its affordances for teacher education, and for domain specific didactical courses in particular. To investigate this topic, we carried out a design research project in which teacher educators engaged in a co-design process of developing and field-testing open online learning units for mathematics and science didactics. The preliminary results concern descriptions of the work processes by the design teams, of design heuristics, and of typical ways of collaborating. These findings are illustrated for the case of two of the designed online units on statistics didactics and mathematical thinking, respectively.
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Nowadays, digital tools for mathematics education are sophisticated and widely available. These tools offer important opportunities, but also come with constraints. Some tools are hard to tailor by teachers, educational designers and researchers; their functionality has to be taken for granted. Other tools offer many possible educational applications, which require didactical choices. In both cases, one may experience a tension between a teacher’s didactical goals and the tool’s affordances. From the perspective of Realistic Mathematics Education (RME), this challenge concerns both guided reinvention and didactical phenomenology. In this chapter, this dialectic relationship will be addressed through the description of two particular cases of using digital tools in Dutch mathematics education: the introduction of the graphing calculator (GC), and the evolution of the online Digital Mathematics Environment (DME). From these two case descriptions, my conclusion is that students need to develop new techniques for using digital tools; techniques that interact with conceptual understanding. For teachers, it is important to be able to tailor the digital tool to their didactical intentions. From the perspective of RME, I conclude that its match with using digital technology is not self-evident. Guided reinvention may be challenged by the rigid character of the tools, and the phenomena that form the point of departure of the learning of mathematics may change in a technology-rich classroom.
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ABSTRACT Purpose: This short paper describes the dashboard design process for online hate speech monitoring for multiple languages and platforms. Methodology/approach: A case study approach was adopted in which the authors followed a research & development project for a multilingual and multiplatform online dashboard monitoring online hate speech. The case under study is the project for the European Observatory of Online Hate (EOOH). Results: We outline the process taken for design and prototype development for which a design thinking approach was followed, including multiple potential user groups of the dashboard. The paper presents this process's outcome and the dashboard's initial use. The identified issues, such as obfuscation of the context or identity of user accounts of social media posts limiting the dashboard's usability while providing a trade-off in privacy protection, may contribute to the discourse on privacy and data protection in (big data) social media analysis for practitioners. Research limitations/implications: The results are from a single case study. Still, they may be relevant for other online hate speech detection and monitoring projects involving big data analysis and human annotation. Practical implications: The study emphasises the need to involve diverse user groups and a multidisciplinary team in developing a dashboard for online hate speech. The context in which potential online hate is disseminated and the network of accounts distributing or interacting with that hate speech seems relevant for analysis by a part of the user groups of the dashboard. International Information Management Association
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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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Retail industry consists of the establishment of selling consumer goods (i.e. technology, pharmaceuticals, food and beverages, apparels and accessories, home improvement etc.) and services (i.e. specialty and movies) to customers through multiple channels of distribution including both the traditional brickand-mortar and online retailing. Managing corporate reputation of retail companies is crucial as it has many advantages, for instance, it has been proven to impact generated revenues (Wang et al., 2016). But, in order to be able to manage corporate reputation, one has to be able to measure it, or, nowadays even better, listen to relevant social signals that are out there on the public web. One of the most extensive and widely used frameworks for measuring corporate reputation is through conducting elaborated surveys with respective stakeholders (Fombrun et al., 2015). This approach is valuable but deemed to be laborious and resource-heavy and will not allow to generate automatic alerts and quick and live insights that are extremely needed in this era of internet. For these purposes a social listening approach is needed that can be tailored to online data such as consumer reviews as the main data source. Online review datasets are a form of electronic Word-of-Mouth (WOM) that, when a data source is picked that is relevant to retail, commonly contain relevant information about customers’ perceptions regarding products (Pookulangara, 2011) and that are massively available. The algorithm that we have built in our application provides retailers with reputation scores for all variables that are deemed to be relevant to retail in the model of Fombrun et al. (2015). Examples of such variables for products and services are high quality, good value, stands behind, and meets customer needs. We propose a new set of subvariables with which these variables can be operationalized for retail in particular. Scores are being calculated using proportions of positive opinion pairs such as <fast, delivery> or <rude, staff> that have been designed per variable. With these important insights extracted, companies can act accordingly and proceed to improve their corporate reputation. It is important to emphasize that, once the design is complete and implemented, all processing can be performed completely automatic and unsupervised. The application makes use of a state of the art aspect-based sentiment analysis (ABSA) framework because of ABSA’s ability to generate sentiment scores for all relevant variables and aspects. Since most online data is in open form and we deliberately want to avoid labelling any data by human experts, the unsupervised aspectator algorithm has been picked. It employs a lexicon to calculate sentiment scores and uses syntactic dependency paths to discover candidate aspects (Bancken et al., 2014). We have applied our approach to a large number of online review datasets that we sampled from a list of 50 top global retailers according to National Retail Federation (2020), including both offline and online operation, and that we scraped from trustpilot, a public website that is well-known to retailers. The algorithm has carefully been evaluated by manually annotating a randomly sampled subset of the datasets for validation purposes by two independent annotators. The Kappa’s score on this subset was 80%.
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Background: Online contacts with a health professional have the potential to support family caregivers of people with dementia. Objective: The goal of the research was to study the effects of an online self-management support intervention in helping family caregivers deal with behavior changes of a relative with dementia. The intervention—involving among others personal email contacts with a dementia nurse—was compared with online interventions without these email contacts. Methods: A randomized controlled trial was conducted with 81 family caregivers of people with dementia who live at home. Participants were randomly assigned to a (1) major self-management support intervention consisting of personal email contacts with a specialist dementia nurse, online videos, and e-bulletins; (2) medium intervention consisting only of online videos and e-bulletins; or (3) minor intervention consisting of only the e-bulletins. The primary outcome was family caregivers’ self-efficacy in dealing with behavior changes of the relative with dementia. Secondary outcomes were family caregivers’ reports of behavior problems in the people with dementia and the quality of the relationship between the family caregiver and the person with dementia. Measurements were performed at the baseline and at 6 (T1) and 12 weeks (T2) after the baseline. A mixed-model analysis was conducted to compare the outcomes of the 3 intervention arms. Results: Family caregivers participating in the major intervention involving email contacts showed no statistically significant differences in self-efficacy after the intervention compared with the minor intervention involving only e-bulletins (difference –0.02, P=.99). In the adjusted analysis, the medium intervention (involving videos and e-bulletins) showed a negative trend over http://www.jmir.org/2020/2/e13001/ J Med Internet Res 2020 | vol. 22 | iss. 2 | e13001 | p. 1 (page number not for citation purposes) JOURNAL OF MEDICAL INTERNET RESEARCH Huis in het Veld et al XSL•FO RenderX time (difference –4.21, P=.09) and at T1 (difference –4.71, P=.07) compared with the minor intervention involving only e-bulletins. No statistical differences were found between the intervention arms in terms of the reported behavior problems and the quality of the relationship between the family caregiver and the person with dementia. Conclusions: The expectation that an online self-management support intervention involving email contacts would lead to positive effects and be more effective than online interventions without personal email contacts was not borne out. One explanation might be related to the fact that not all family caregivers who were assigned to that intervention actually made use of the opportunity for personal email contact. The online videos were also not always viewed. To obtain more definite conclusions, future research involving extra efforts to reach higher use rates is required.
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In this study we measured the effect of COIL on intercultural competence development using a quasi-experimental design. Our sample consisted of 108 undergraduate students from two universities, one located in the Netherlands (NL) and one in the United States (US). Students’ self-reported intercultural competence was measured using a pre-post survey which included the Cultural Intelligence Scale (CQS) and Multicultural Personality Questionnaire (MPQ). Qualitative data were collected to complement our quantitative findings and to give a deeper insight into the student experience. The data showed a significantly bigger increase in intercultural competence for the US experimental group compared to the US control group, supporting our hypothesis that COIL develops intercultural competence. This difference was not observed for the NL students, possibly due to the NL control group being exposed to other international input during the course.
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