Quality Prediction of Open Educational Resources A Metadata-based Approach

In the recent decade, online learning environments have accumulated millions of Open Educational Resources (OERs). However, for learners, finding relevant and high quality OERs is a complicated and time-consuming activity. Furthermore, metadata play a key role in offering high quality services such as recommendation and search. Metadata can also be used for automatic OER quality control as, in the light of the continuously increasing number of OERs, manual quality control is getting more and more difficult. In this work, we collected the metadata of 8,887 OERs to perform an exploratory data analysis to observe the effect of quality control on metadata quality. Subsequently, we propose an OER metadata scoring model, and build a metadata-based prediction model to anticipate the quality of OERs. Based on our data and model, we were able to detect high-quality OERs with the F1 score of 94.6%. © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Metadata analysis of open educational resources

Open Educational Resources (OERs) are openly licensed educational materials that are widely used for learning. Nowadays, many online learning repositories provide millions of OERs. Therefore, it is exceedingly difficult for learners to find the most appropriate OER among these resources. Subsequently, the precise OER metadata is critical for providing high-quality services such as search and recommendation. Moreover, metadata facilitates the process of automatic OER quality control as the continuously increasing number of OERs makes manual quality control extremely difficult. This work uses the metadata of 8,887 OERs to perform an exploratory data analysis on OER metadata. Accordingly, this work proposes metadata-based scoring and prediction models to anticipate the quality of OERs. Based on the results, our analysis demonstrated that OER metadata and OER content qualities are closely related, as we could detect high-quality OERs with an accuracy of 94.6%. Our model was also evaluated on 884 educational videos from Youtube to show its applicability on other educational repositories

An OER Recommender System Supporting Accessibility Requirements

Open Educational Resources are becoming a significant source of learning that are widely used for various educational purposes and levels. Learners have diverse backgrounds and needs, especially when it comes to learners with accessibility requirements. Persons with disabilities have significantly lower employment rates partly due to the lack of access to education and vocational rehabilitation and training. It is not surprising therefore, that providing high quality OERs that facilitate the self-development towards specific jobs and skills on the labor market in the light of special preferences of learners with disabilities is difficult. In this paper, we introduce a personalized OER recommeder system that considers skills, occupations, and accessibility properties of learners to retrieve the most adequate and high-quality OERs. This is done by: 1) describing the profile of learners with disabilities, 2) collecting and analysing more than 1,500 OERs, 3) filtering OERs based on their accessibility features and predicted quality, and 4) providing personalised OER recommendations for learners according to their accessibility needs. As a result, the OERs retrieved by our method proved to satisfy more accessibility checks than other OERs. Moreover, we evaluated our results with five experts in educating people with visual and cognitive impairments. The evaluation showed that our recommendations are potentially helpful for learners with accessibility needs

Quality evaluation of open educational resources

Open Educational Resources (OER) are free and open-licensed educational materials widely used for learning. OER quality assessment has become essential to support learners and teachers in finding high-quality OERs, and to enable online learning repositories to improve their OERs. In this work, we establish a set of evaluation metrics that assess OER quality in OER authoring tools. These metrics provide guidance to OER content authors to create high-quality content. The metrics were implemented and evaluated within SlideWiki, a collaborative OpenCourseWare platform that provides educational materials in presentation slides format. To evaluate the relevance of the metrics, a questionnaire is conducted among OER expert users. The evaluation results indicate that the metrics address relevant quality aspects and can be used to determine the overall OER quality

CT Image Segmentation Using FEM with Optimized Boundary Condition

The authors propose a CT image segmentation method using structural analysis that is useful for objects with structural dynamic characteristics. Motivation of our research is from the area of genetic activity. In order to reveal the roles of genes, it is necessary to create mutant mice and measure differences among them by scanning their skeletons with an X-ray CT scanner. The CT image needs to be manually segmented into pieces of the bones. It is a very time consuming to manually segment many mutant mouse models in order to reveal the roles of genes. It is desirable to make this segmentation procedure automatic. Although numerous papers in the past have proposed segmentation techniques, no general segmentation method for skeletons of living creatures has been established. Against this background, the authors propose a segmentation method based on the concept of destruction analogy. To realize this concept, structural analysis is performed using the finite element method (FEM), as structurally weak areas can be expected to break under conditions of stress. The contribution of the method is its novelty, as no studies have so far used structural analysis for image segmentation. The method's implementation involves three steps. First, finite elements are created directly from the pixels of a CT image, and then candidates are also selected in areas where segmentation is thought to be appropriate. The second step involves destruction analogy to find a single candidate with high strain chosen as the segmentation target. The boundary conditions for FEM are also set automatically. Then, destruction analogy is implemented by replacing pixels with high strain as background ones, and this process is iterated until object is decomposed into two parts. Here, CT image segmentation is demonstrated using various types of CT imagery

Understanding the impact of haemodialysis on UK NHS patients’ wellbeing: a qualitative investigation

Aims and Objectives: While haemodialysis (HD) is an effective treatment for end-stage renal disease (ESRD), the requirements and restrictions it imposes on patients can be onerous. The aim of the current study was to obtain UK National Health Service (NHS) patients’ perspectives on the challenges arising from HD with the intention of identifying potential improvements. Background: Depression rates are particularly high in those with ESRD, however, there is limited insight into the range of stressors associated with HD treatment within the NHS contributing to such high rates, particularly those of a cognitive or psychological nature. Design: A qualitative approach was used to obtain rich, patient-focused data; one-to-one semi-structured interviews were conducted with twenty ESRD at a UK NHS-centre. Methods: Patients were interviewed during a typical HD session. Thematic analysis was used to systematically interpret the data. Codes were created in an inductive and cyclical process using a constant comparative approach. Results: Three themes emerged from the data: 1) fluctuations in cognitive/physical wellbeing across the HD cycle, 2) restrictions arising from the HD treatment schedule, 3) Emotional impact of HD on the self and others. The findings are limited to predominantly white, older patients (median = 74 years) within an NHS setting. Conclusions: Several of the experiences reported by patients as challenging and distressing have so far been overlooked in the literature. A holistic-based approach to treatment, acknowledging all aspects of a patient’s wellbeing, is essential if optimal quality of life is to be achieved by healthcare providers. Relevance to clinical practice: The findings can be used to inform future interventions and guidelines aimed at improving patients’ treatment adherence and outcomes, for example, improved reliable access to mental health specialists

Endovascular Stroke Treatment and Risk of Intracranial Hemorrhage in Anticoagulated Patients.

Background and Purpose- We aimed to determine the safety and mortality after mechanical thrombectomy in patients taking vitamin K antagonists (VKAs) or direct oral anticoagulants (DOACs). Methods- In a multicenter observational cohort study, we used multiple logistic regression analysis to evaluate associations of symptomatic intracranial hemorrhage (sICH) with VKA or DOAC prescription before thrombectomy as compared with no anticoagulation. The primary outcomes were the rate of sICH and all-cause mortality at 90 days, incorporating sensitivity analysis regarding confirmed therapeutic anticoagulation. Additionally, we performed a systematic review and meta-analysis of literature on this topic. Results- Altogether, 1932 patients were included (VKA, n=222; DOAC, n=98; no anticoagulation, n=1612); median age, 74 years (interquartile range, 62-82); 49.6% women. VKA prescription was associated with increased odds for sICH and mortality (adjusted odds ratio [aOR], 2.55 [95% CI, 1.35-4.84] and 1.64 [95% CI, 1.09-2.47]) as compared with the control group, whereas no association with DOAC intake was observed (aOR, 0.98 [95% CI, 0.29-3.35] and 1.35 [95% CI, 0.72-2.53]). Sensitivity analyses considering only patients within the confirmed therapeutic anticoagulation range did not alter the findings. A study-level meta-analysis incorporating data from 7462 patients (855 VKAs, 318 DOACs, and 6289 controls) from 15 observational cohorts corroborated these observations, yielding an increased rate of sICH in VKA patients (aOR, 1.62 [95% CI, 1.22-2.17]) but not in DOAC patients (aOR, 1.03 [95% CI, 0.60-1.80]). Conclusions- Patients taking VKA have an increased risk of sICH and mortality after mechanical thrombectomy. The lower risk of sICH associated with DOAC may also be noticeable in the acute setting. Improved selection might be advisable in VKA-treated patients. Registration- URL: https://www.clinicaltrials.gov. Unique identifier: NCT03496064. Systematic Review and Meta-Analysis: CRD42019127464

Increased Basal Activity Is a Key Determinant in the Severity of Human Skeletal Dysplasia Caused by TRPV4 Mutations

TRPV4 is a mechanically activated Ca2+-passing channel implicated in the sensing of forces, including those acting on bones. To date, 33 mutations are known to affect human bone development to different extents. The spectrum of these skeletal dysplasias (SD) ranges from dominantly inherited mild brachylomia (BO) to neonatal lethal forms of metatropic dysplasia (MD). Complexities of the results from fluorescence and electrophysiological studies have led to questions on whether channel activity is a good predictor of disease severity. Here we report on a systematic examination of 14 TRPV4 mutant alleles covering the entire SD spectrum. Expressed in Xenopus oocyte and without any stimulation, the wild-type channel had a ∼1% open probability (Po) while those of most of the lethal MD channels approached 100%. All mutant channels had higher basal open probabilities, which limited their further increase by agonist or hypotonicity. The magnitude of this limitation revealed a clear correlation between the degree of over-activity (the molecular phenotype) and the severity of the disease over the entire spectrum (the biological phenotype). Thus, while other factors are at play, our results are consistent with the increased TRPV4 basal activity being a critical determinant of the severity of skeletal dysplasia. We discuss how the channel over-activity may lead to the “gain-of-function” phenotype and speculate that the function of wild-type TRPV4 may be secondary in normal bone development but crucial in an acute process such as fracture repair in the adult

Fifth European Dirofilaria and Angiostrongylus Days (FiEDAD) 2016

Peer reviewe