Using Learning Analytics to Devise Interactive Personalised Nudges for Active Video Watching

Videos can be a powerful medium for acquiring soft skills, where learning requires contextualisation in personal experience and ability to see different perspectives. However, to learn effectively while watching videos, students need to actively engage with video content. We implemented interactive notetaking during video watching in an active video watching system (AVW) as a means to encourage engagement. This paper proposes a systematic approach to utilise learning analytics for the introduction of adaptive intervention - a choice architecture for personalised nudges in the AVW to extend learning. A user study was conducted and used as an illustration. By characterising clusters derived from user profiles, we identify different styles of engagement, such as parochial learning, habitual video watching, and self-regulated learning (which is the target ideal behaviour). To find opportunities for interventions, interaction traces in the AVW were used to identify video intervals with high user interest and relevant behaviour patterns that indicate when nudges may be triggered. A prediction model was developed to identify comments that are likely to have high social value, and can be used as examples in nudges. A framework for interactive personalised nudges was then conceptualised for the case study

Perspectives of people in Mali toward genetically-modified mosquitoes for malaria control

Background: Genetically-modified (GM) mosquitoes have been proposed as part of an integrated vector control strategy for malaria control. Public acceptance is essential prior to field trials, particularly since mosquitoes are a vector of human disease and genetically modified organisms (GMOs) face strong scepticism in developed and developing nations. Despite this, in sub-Saharan Africa, where the GM mosquito effort is primarily directed, very little data is available on perspectives to GMOs. Here, results are presented of a qualitative survey of public attitudes to GM mosquitoes for malaria control in rural and urban areas of Mali, West Africa between the months of October 2008 and June 2009. Methods: The sample consisted of 80 individuals - 30 living in rural communities, 30 living in urban suburbs of Bamako, and 20 Western-trained and traditional health professionals working in Bamako and Bandiagara. Questions were asked about the cause of malaria, heredity and selective breeding. This led to questions about genetic alterations, and acceptable conditions for a release of pest-resistant GM corn and malaria-refractory GM mosquitoes. Finally, participants were asked about the decision-making process in their community. Interviews were transcribed and responses were categorized according to general themes. Results: Most participants cited mosquitoes as one of several causes of malaria. The concept of the gene was not widely understood; however selective breeding was understood, allowing limited communication of the concept of genetic modification. Participants were open to a release of pest-resistant GM corn, often wanting to conduct a trial themselves. The concept of a trial was reapplied to GM mosquitoes, although less frequently. Participants wanted to see evidence that GM mosquitoes can reduce malaria prevalence without negative consequences for human health and the environment. For several participants, a mosquito control programme was preferred; however a transgenic release that satisfied certain requirements was usually acceptable. Conclusions: Although there were some dissenters, the majority of participants were pragmatic towards a release of GM mosquitoes. An array of social and cultural issues associated with malaria, mosquitoes and genetic engineering became apparent. If these can be successfully addressed, then social acceptance among the populations surveyed seems promising

Public Narratives and the Construction of Memory Among European Muslims

This chapter draws on group and individual interviews with 735 European Muslims in 5 European countries and explores some key aspects of the politics of memory that form an inextricable component of European Muslim self-definitions, discourses and narratives deployed in the attempt to negotiate their inclusion in European societies

Towards Effective Extraction and Linking of Software Mentions from User-Generated Support Tickets

Software support tickets contain short and noisy text from the customers. Software products are often represented by various surface forms and informal abbreviations. Automatically identifying software mentions from support tickets and determining the official names and versions are helpful for many downstream applications, \eg routing the support tickets to the right expert groups for support. In this work, we study the problem ofsoftware product name extraction andlinking from support tickets. We first annotate and analyze sampled tickets to understand the language patterns. Next, we design features using local, contextual, and external information sources, for extraction and linking models. In experiments, we show that linear models with the proposed features are able to deliver better and more consistent results, compared with the state-of-the-art baseline models, even on dataset with sparse labels

Hierarchical Anatomical Brain Networks for MCI Prediction: Revisiting Volumetric Measures

Owning to its clinical accessibility, T1-weighted MRI (Magnetic Resonance Imaging) has been extensively studied in the past decades for prediction of Alzheimer's disease (AD) and mild cognitive impairment (MCI). The volumes of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) are the most commonly used measurements, resulting in many successful applications. It has been widely observed that disease-induced structural changes may not occur at isolated spots, but in several inter-related regions. Therefore, for better characterization of brain pathology, we propose in this paper a means to extract inter-regional correlation based features from local volumetric measurements. Specifically, our approach involves constructing an anatomical brain network for each subject, with each node representing a Region of Interest (ROI) and each edge representing Pearson correlation of tissue volumetric measurements between ROI pairs. As second order volumetric measurements, network features are more descriptive but also more sensitive to noise. To overcome this limitation, a hierarchy of ROIs is used to suppress noise at different scales. Pairwise interactions are considered not only for ROIs with the same scale in the same layer of the hierarchy, but also for ROIs across different scales in different layers. To address the high dimensionality problem resulting from the large number of network features, a supervised dimensionality reduction method is further employed to embed a selected subset of features into a low dimensional feature space, while at the same time preserving discriminative information. We demonstrate with experimental results the efficacy of this embedding strategy in comparison with some other commonly used approaches. In addition, although the proposed method can be easily generalized to incorporate other metrics of regional similarities, the benefits of using Pearson correlation in our application are reinforced by the experimental results. Without requiring new sources of information, our proposed approach improves the accuracy of MCI prediction from (of conventional volumetric features) to (of hierarchical network features), evaluated using data sets randomly drawn from the ADNI (Alzheimer's Disease Neuroimaging Initiative) dataset

Effect of exploitation and exploration on the innovative as outcomes in entrepreneurial firms

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Towards a greater dialogue on disability between Muslims and Christians

Attitudes to disability and disabled people by Muslims – focusing on attitudes in the Middle East and North Africa - and Christians – focusing on the West (here taken to mean Europe, North America and Australasia) - were examined through a grounded theory literature search, with the study being divided into three phases of reading and analysis. The aims of study were to develop a dialogue on disability between the two cultures, to inform an understanding of the attitudes to disability in the two cultures, and to inform cultural practice in promoting support and equality in both cultures. The study finds that Islam and Christianity have much in common and are a force for good in promoting and developing disability equality in both Muslim and Christian cultures

‘Friends call me racist’: Experiences of repercussions from writing comments on newspaper websites

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