Putting learning back into learning analytics: actions for policy makers, researchers, and practitioners

This paper is based on (a) a literature review focussing on the impact of learning analytics on supporting learning and teaching, (b) a Delphi study involving international expert discussion on current opportunities and challenges of learning analytics as well as (c) outlining a research agenda for closing identified research gaps. Issues and challenges facing educators linked to learning analytics and current research gaps were organised into four themes, the further development of which by the expert panel, led to six strategy and action areas. The four themes are 1. development of data literacy in all stakeholders, 2. updating of guiding principles and policies of educational data, 3. standards needed for ethical practices with data quality assurance, and 4. flexible user-centred design for a variety of users of analytics, starting with learners and ensuring that learners and learning is not harmed. The strategies and actions are outcomes of the expert panel discussion and are offered as provocations to organise and focus the researcher, policymaker and practitioner dialogs needed to make progress in the field

Does the exotic equal pollution? Landscape methods for solving the dilemma of using native versus non‐native plant species in drylands

There is a need to resolve methods to determine the merits of native versus nonnative plant use in drylands and indeed in more temperate areas around the world. This is because whilst plant introductions may have positive objectives, they can have significant negative landscape and environmental impacts. A key discussion on this issue focuses on whether the use of non-native plant species can be considered to be pollution and pollutive based on the concept that pollution can be regarded as ‘matter out of place’. The consequences of putting the wrong plant species in the wrong place can be extremely detrimental to the landscape character, quality and value of the land, let alone the effects on ecosystem structure and functioning as well as on biodiversity. These effects can also affect human communities who may rely on the landscape, for example, for tourism. It is thus necessary that the discussion on how decisions are made in determining plant choice evolves so that the right decisions are made when planting is necessary, for the land, for nature and for the people. This discussion has been initiated through COST Action ES1104, which focused on the restoration of degraded dry and arid lands. This article discusses a number of landscape methods based on sustainability principles to determine when and where native and non-native plants could and should be used.info:eu-repo/semantics/publishedVersio

Thematic Working Group 5: Formative assessment supported by technology.

The future of assessment faces major challenges including the use of IT to facilitate formative assessment that is important for improving learners’ development, motivation and engagement in learning. In many countries, in recent years, a renewed focus on assessments to support learning has been pushing against the burgeoning of testing for accountability, which in some countries, renders effective formative assessment practices almost impossible. Moreover, a systematic review by Harlen and Deakin Crick (2002) revealed that a strong focus on summative assessment for accountability can reduce motivation and disengage many learners. At the same time use of IT‐enabled assessments has been increasing rapidly, as they offer promise of cheaper ways of delivering and marking assessments as well as access to vast amounts of assessment data from which a wide range of judgements might be made about students, teachers, schools and education systems (Gibson & Webb, 2015). These opportunities also extend to assessment of complex collaborative work (Webb & Gibson, 2015). Current opportunities for using IT, including for harnessing the data that is being collected automatically, for formative assessment are underexplored and less well understood than those for summative assessments. Opportunities for learning with IT and perhaps with less teacher input are increasing but this depends on students developing as autonomous or independent learners. Research in formative assessment including effective feedback has emphasised the value of peer assessment practices for developing self‐assessment capabilities and hence independent learners (Black, Harrison, Lee, Marshall, & William, 2003). At previous EDUsummITs the possibilities and challenges for IT‐enabled assessments to support simultaneously both formative and summative purposes were analysed (Webb, Gibson, & Forkosh‐Baruch, 2013). While these challenges remain, at EDUsummIT 2017 we focused on the opportunities and challenges of IT supporting formative assessment because effective formative assessment is known to be extremely important for learning.RETHINKING LEARNING IN A DIGITAL AGE, EDUsummIT 2017 Summary Reports 18-20 september, Bulgari

Clinical use of biomarkers of survival in pulmonary fibrosis

<p>Abstract</p> <p>Background</p> <p>Biologic predictors or biomarkers of survival in pulmonary fibrosis with a worse prognosis, more specifically in idiopathic pulmonary fibrosis would help the clinician in deciding whether or not to treat since treatment carries a potential risk for adverse events. These decisions are made easier if accurate and objective measurements of the patients' clinical status can predict the risk of progression to death.</p> <p>Method</p> <p>A literature review is given on different biomarkers of survival in interstitial lung disease, mainly in IPF, since this disease has the worst prognosis.</p> <p>Conclusion</p> <p>Serum biomarkers, and markers measured by medical imaging as HRCT, pertechnegas, DTPA en FDG-PET are not ready for clinical use to predict mortality in different forms of ILD. A baseline FVC, a change of FVC of more than 10%, and change in 6MWD are clinically helpful predictors of survival.</p

Pharmaceutical Formulation Facilities as Sources of Opioids and Other Pharmaceuticals to Wastewater Treatment Plant Effluents

Facilities involved in the manufacture of pharmaceutical products are an under-investigated source of pharmaceuticals to the environment. Between 2004 and 2009, 35 to 38 effluent samples were collected from each of three wastewater treatment plants (WWTPs) in New York and analyzed for seven pharmaceuticals including opioids and muscle relaxants. Two WWTPs (NY2 and NY3) receive substantial flows (>20% of plant flow) from pharmaceutical formulation facilities (PFF) and one (NY1) receives no PFF flow. Samples of effluents from 23 WWTPs across the United States were analyzed once for these pharmaceuticals as part of a national survey. Maximum pharmaceutical effluent concentrations for the national survey and NY1 effluent samples were generally <1 μg/L. Four pharmaceuticals (methadone, oxycodone, butalbital, and metaxalone) in samples of NY3 effluent had median concentrations ranging from 3.4 to >400 μg/L. Maximum concentrations of oxycodone (1700 μg/L) and metaxalone (3800 μg/L) in samples from NY3 effluent exceeded 1000 μg/L. Three pharmaceuticals (butalbital, carisoprodol, and oxycodone) in samples of NY2 effluent had median concentrations ranging from 2 to 11 μg/L. These findings suggest that current manufacturing practices at these PFFs can result in pharmaceuticals concentrations from 10 to 1000 times higher than those typically found in WWTP effluents

Granulomatous-lymphocytic interstitial lung disease: an international research prioritisation

The first ever research prioritisation exercise in GLILD: this survey identified areas of interest in the diagnosis, treatment and management of GLILD, which can be used as a roadmap for future research

Granulomatous-lymphocytic interstitial lung disease: an international research prioritisation

The first ever research prioritisation exercise in GLILD: this survey identified areas of interest in the diagnosis, treatment and management of GLILD, which can be used as a roadmap for future research

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome

Pathway-Based Evaluation in Early Onset Colorectal Cancer Suggests Focal Adhesion and Immunosuppression along with Epithelial-Mesenchymal Transition

Colorectal cancer (CRC) has one of the highest incidences among all cancers. The majority of CRCs are sporadic cancers that occur in individuals without family histories of CRC or inherited mutations. Unfortunately, whole-genome expression studies of sporadic CRCs are limited. A recent study used microarray techniques to identify a predictor gene set indicative of susceptibility to early-onset CRC. However, the molecular mechanisms of the predictor gene set were not fully investigated in the previous study. To understand the functional roles of the predictor gene set, in the present study we applied a subpathway-based statistical model to the microarray data from the previous study and identified mechanisms that are reasonably associated with the predictor gene set. Interestingly, significant subpathways belonging to 2 KEGG pathways (focal adhesion; natural killer cell-mediated cytotoxicity) were found to be involved in the early-onset CRC patients. We also showed that the 2 pathways were functionally involved in the predictor gene set using a text-mining technique. Entry of a single member of the predictor gene set triggered a focal adhesion pathway, which confers anti-apoptosis in the early-onset CRC patients. Furthermore, intensive inspection of the predictor gene set in terms of the 2 pathways suggested that some entries of the predictor gene set were implicated in immunosuppression along with epithelial-mesenchymal transition (EMT) in the early-onset CRC patients. In addition, we compared our subpathway-based statistical model with a gene set-based statistical model, MIT Gene Set Enrichment Analysis (GSEA). Our method showed better performance than GSEA in the sense that our method was more consistent with a well-known cancer-related pathway set. Thus, the biological suggestion generated by our subpathway-based approach seems quite reasonable and warrants a further experimental study on early-onset CRC in terms of dedifferentiation or differentiation, which is underscored in EMT and immunosuppression

A Micro RNA Processing Defect in Rapidly Progressing Idiopathic Pulmonary Fibrosis

BACKGROUND: Idiopathic pulmonary fibrosis exhibits differential progression from the time of diagnosis but the molecular basis for varying progression rates is poorly understood. The aim of the present study was to ascertain whether differential miRNA expression might provide one explanation for rapidly versus slowly progressing forms of IPF. METHODOLOGY AND PRINCIPAL FINDINGS: miRNA and mRNA were isolated from surgical lung biopsies from IPF patients with a clinically documented rapid or slow course of disease over the first year after diagnosis. A quantitative PCR miRNA array containing 88 of the most abundant miRNA in the human genome was used to profile lung biopsies from 9 patients with rapidly progressing IPF, 6 patients with slowly progressing IPF, and 10 normal lung biopsies. Using this approach, 11 miRNA were significantly increased and 36 were significantly decreased in rapid biopsies compared with normal biopsies. Slowly progressive biopsies exhibited 4 significantly increased miRNA and 36 significantly decreased miRNA compared with normal lung. Among the miRNA present in IPF with validated mRNA targets were those with regulatory effects on epithelial-mesenchymal transition (EMT). Five miRNA (miR-302c, miR-423-5p, miR-210, miR-376c, and miR-185) were significantly increased in rapid compared with slow IPF lung biopsies. Additional analyses of rapid biopsies and fibroblasts grown from the same biopsies revealed that the expression of AGO1 and AGO2 (essential components of the miRNA processing RISC complex) were lower compared with either slow or normal lung biopsies and fibroblasts. CONCLUSION: These findings suggest that the development and/or clinical progression of IPF might be the consequence of aberrant miRNA processing