graphical displays
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2021 ◽  
Author(s):  
Anouschka Van Leeuwen ◽  
Pengcheng An

Teachers in higher education are tasked with the demanding job of providing support tailored to each individual student’s need. To provide tailored support, teachers need to accurately monitor students’ activities and decide on appropriate support interventions. Learning analytics applications have the potential to aid teachers to maintain an overview of their students’ activities. However, those applications are often designed as centralized graphical displays, taking teachers’ attention away from the classroom and sometimes overburdening teachers. Therefore, we investigate whether ambient LA displays offer a solution to complement traditional LA applications, as these systems are designed as objects that integrate seamlessly into the classroom context. We conducted an exploratory study in Higher Education to investigate teachers’ needs for information and their perception of ambient LA displays in relation to their teaching practice. We formulate three key findings and a set of design opportunities that flow from these findings to inform future work of supporting the HE context with ambient LA displays.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18612-e18612
Author(s):  
Gillian Gresham ◽  
Gina L. Mazza ◽  
Blake Langlais ◽  
Bellinda King-Kallimanis ◽  
Lauren J. Rogak ◽  
...  

e18612 Background: Effective communication of treatment tolerability data is essential for clinical decision making and improved patient outcomes, yet standardized approaches to the analysis and visualization of tolerability data in cancer clinical trials are currently limited. To address this need, the Standardization Working Group (SWG) was established within the NCI Cancer Moonshot Tolerability Consortium. This abstract describes the SWG’s initiative to develop a publicly accessible online toolkit with a comprehensive set of guidelines, references, and resources for graphical displays of tolerability data. Methods: A multidisciplinary group of PRO researchers including biostatisticians, clinicians, epidemiologists, and representatives from the NCI and FDA convened monthly to discuss toolkit development and content. Considerations for standardization of graphical displays of tolerability data included (1) types of graphical displays, (2) incorporation of missing data, (3) labeling and color schemes, and (4) software to produce graphical displays. For consistency, considerations of tolerability relied on the Patient-Reported Outcomes version of the CTCAE (PRO-CTCAE), which includes 124 items assessing the frequency, severity, interference, and/or presence of 78 symptomatic adverse events. Graphical displays were generated using simulated PRO-CTCAE data and summarized by composite score (range 0-3).Color schemes that were Section 508 compliant and color blindness accessible were created. Surveys were distributed to 68 consortium members to assess preferences and interpretability of the graphical displays. Results: The SWG created graphical displays for PRO-CTCAE data, including bar charts, butterfly plots, and Sankey diagrams and compiled SAS macros and R functions to do so. Graphical displays made available in the toolkit maximize the use of PRO-CTCAE data, incorporate missingness, support between-arm comparisons, and present data longitudinally over treatment cycles or study timepoints. Survey results for labeling and color schemes were summarized and informed a list of short labels for PRO-CTCAE items (e.g., “radiation burns” for “skin burns from radiation”) and standardized color schemes for use in graphical displays. Survey results were also summarized to provide insight into PRO researchers’ ability to accurately interpret the graphical displays. Conclusions: Standardizinggraphical displays is important for improving the communication and interpretation of tolerability data. The type of graphical display used depends on the purpose of the analysis and should be tailored to the intended audience, including patients. This toolkit will provide a comprehensive resource with best practice recommendations.


2021 ◽  
pp. 109467052110124
Author(s):  
Sarah Köcher ◽  
Sören Köcher

In this article, the authors demonstrate a tendency among consumers to use the arithmetic mode as a heuristic basis when drawing inferences from graphical displays of online rating distributions in such a way that service evaluations inferred from rating distributions systematically vary by the location of the mode. The rationale underlying this phenomenon is that the mode (i.e., the most frequent rating which is represented by the tallest bar in a graphical display) attracts consumers’ attention because of its visual salience and is thus disproportionately weighted when they draw conclusions. Across a series of eight studies, the authors provide strong empirical evidence for the existence of the mode heuristic, shed light on this phenomenon at the process level, and demonstrate how consumers’ inferences based on the mode heuristic depend on the visual salience of the mode. Together, the findings of these studies contribute to a better understanding of how service customers process and interpret graphical illustrations of online rating distributions and provide companies with a new key figure that—aside from rating volume, average ratings, and rating dispersion—should be incorporated in the monitoring, analyzing, and evaluating of review data.


2021 ◽  
pp. 1-29
Author(s):  
Cameron Brick ◽  
Alexandra L.J. Freeman

Abstract Policy decisions have vast consequences, but there is little empirical research on how best to communicate underlying evidence to decision-makers. Groups in diverse fields (e.g., education, medicine, crime) use brief, graphical displays to list policy options, expected outcomes and evidence quality in order to make such evidence easy to assess. However, the understanding of these representations is rarely studied. We surveyed experts and non-experts on what information they wanted and tested their objective comprehension of commonly used graphics. A total of 252 UK residents from Prolific and 452 UK What Works Centre users interpreted the meaning of graphics shown without labels. Comprehension was low (often below 50%). The best-performing graphics combined unambiguous metaphorical shapes with color cues and indications of quantity. The participants also reported what types of evidence they wanted and in what detail (e.g., subgroups, different outcomes). Users particularly wanted to see intervention effectiveness and quality, and policymakers also wanted to know the financial costs and negative consequences. Comprehension and preferences were remarkably consistent between the two samples. Groups communicating evidence about policy options can use these results to design summaries, toolkits and reports for expert and non-expert audiences.


BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e041861
Author(s):  
Zephanie Tyack ◽  
Megan Simons ◽  
Steven M McPhail ◽  
Gillian Harvey ◽  
Tania Zappala ◽  
...  

IntroductionUsing patient-reported outcome measures (PROMs) with children have been described as ‘giving a voice to the child’. Few studies have examined the routine use of these measures as potentially therapeutic interventions. This study aims to investigate: (1) the effectiveness of feedback using graphical displays of information from electronic PROMs (ePROMs) that target health-related quality of life, to improve health outcomes, referrals and treatment satisfaction and (2) the implementation of ePROMs and graphical displays by assessing acceptability, sustainability, cost, fidelity and context of the intervention and study processes.Methods and analysisA hybrid II effectiveness-implementation study will be conducted from February 2020 with children with life-altering skin conditions attending two outpatient clinics at a specialist paediatric children’s hospital. A pragmatic randomised controlled trial and mixed methods process evaluation will be completed. Randomisation will occur at the child participant level. Children or parent proxies completing baseline ePROMs will be randomised to: (1) completion of ePROMs plus graphical displays of ePROM results to treating clinicians in consultations, versus (2) completion of ePROMs without graphical display of ePROM results. The primary outcome of the effectiveness trial will be overall health-related quality of life of children. Secondary outcomes will include other health-related quality of life outcomes (eg, child psychosocial and physical health, parent psychosocial health), referrals and treatment satisfaction. Trial data will be primarily analysed using linear mixed-effects models; and implementation data using inductive thematic analysis of interviews, meeting minutes, observational field notes and study communication mapped to the Consolidated Framework for Implementation Research.Ethics and disseminationEthical approval was obtained from Children’s Health Queensland Human Research Ethics Committee (HREC/2019/QCHQ/56290), The University of Queensland (2019002233) and Queensland University of Technology (1900000847). Dissemination will occur through stakeholder groups, scientific meetings and peer-reviewed publications.Trial registration numberAustralian New Zealand Clinical Trials Registry (ACTRN12620000174987).


2021 ◽  
Vol 132 ◽  
pp. 34-45
Author(s):  
Konstantinos I. Bougioukas ◽  
Elpida Vounzoulaki ◽  
Chrysanthi D. Mantsiou ◽  
Eliophotos D. Savvides ◽  
Christina Karakosta ◽  
...  

2021 ◽  
Author(s):  
Indrajeet Patil

Graphical displays can reveal problems in a statistical model that might not be apparent from purely numerical summaries. Such visualizations can also be helpful for the reader to evaluate validity of a model if the said analysis is reported in a scholarly publication/report. But, given the onerous costs involved, researchers can avoid preparing information-rich graphics and exploring several statistical approaches/tests available. The `ggstatsplot` package in R programming language provides a one-line syntax to create densely informative `ggplot2`-based visualizations with the results from statistical analysis embedded in the visualization itself. In doing so, the package helps researchers adopt a rigorous, reliable, and robust data exploratory and reporting workflow.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ye Emma Zohner ◽  
Jeffrey S. Morris

Abstract Background The COVID-19 pandemic has caused major health and socio-economic disruptions worldwide. Accurate investigation of emerging data is crucial to inform policy makers as they construct viral mitigation strategies. Complications such as variable testing rates and time lags in counting cases, hospitalizations and deaths make it challenging to accurately track and identify true infectious surges from available data, and requires a multi-modal approach that simultaneously considers testing, incidence, hospitalizations, and deaths. Although many websites and applications report a subset of these data, none of them provide graphical displays capable of comparing different states or countries on all these measures as well as various useful quantities derived from them. Here we introduce a freely available dynamic representation tool, COVID-TRACK, that allows the user to simultaneously assess time trends in these measures and compare various states or countries, equipping them with a tool to investigate the potential effects of the different mitigation strategies and timelines used by various jurisdictions. Findings COVID-TRACK is a Python based web-application that provides a platform for tracking testing, incidence, hospitalizations, and deaths related to COVID-19 along with various derived quantities. Our application makes the comparison across states in the USA and countries in the world easy to explore, with useful transformation options including per capita, log scale, and/or moving averages. We illustrate its use by assessing various viral trends in the USA and Europe. Conclusion The COVID-TRACK web-application is a user-friendly analytical tool to compare data and trends related to the COVID-19 pandemic across areas in the United States and worldwide. Our tracking tool provides a unique platform where trends can be monitored across geographical areas in the coming months to watch how the pandemic waxes and wanes over time at different locations around the USA and the globe.


2020 ◽  
Vol 5 (1) ◽  
pp. 1-14
Author(s):  
Yasmeen Ali Ameen ◽  
◽  
Khaled Bahnasy ◽  
Adel Elmahdy ◽  
◽  
...  

Background: Early event detection, monitor, and response can significantly decrease the impact of disasters. Lately, the usage of social media for detecting events has displayed hopeful results. Objectives: for event detection and mapping; the tweets will locate and monitor them on a map. This new approach uses grouped geoparsing then scoring for each tweet based on three spatial indicators. Method/Approach: Our approach uses a geoparsing technique to match a location in tweets to geographic locations of multiple-events tweets in Egypt country, administrative subdivision. Thus, additional geographic information acquired from the tweet itself to detect the actual locations that the user mentioned in the tweet. Results: The approach was developed from a large pool of tweets related to various crisis events over one year. Only all (very specific) tweets that were plotted on a crisis map to monitor these events. The tweets were analyzed through predefined geo-graphical displays, message content filters (damage, casualties). Conclusion: A method was implemented to predict the effective start of any crisis event and an inequity condition is applied to determine the end of the event. Results indicate that our automated filtering of information provides valuable information for operational response and crisis communication


2020 ◽  

This report outlines in detail the situation of rural Youths Neither in Employment, nor in Education or Training (NEET) aged between 15 and 34 years old, over the last decade (2009-2019) in Spain. To do this, the report utilised indicators of: youth population; youth employment and unemployment; education; and, NEETs distribution. The characterisation of all indicators adopted the degree of urbanisation as a central criterion, enabling propor-tional comparisons between rural areas, towns and suburbs, cities and the whole country. These analyses are further divided into age subgroups and, where possible, into sex groups for greater detail.The statistical procedures adopted across the different selected dimensions involve: des-criptive longitudinal analysis; using graphical displays (e.g., overlay line charts); and, the calculation of proportional absolute and relative changes between 2009 and 2013, 2013 and 2019, and finally 2009 and 2019. These time ranges were chosen to capture the in-dicators evolution before and after the economic crisis which hit European countries. All data was extracted from Eurostat public datasets.In the last ten years (2009 - 2019) a significant portion of the Spanish youth population has migrated from rural areas to cities and towns. This migration trend could be explained by the economic crisis which impacted upon Spain from 2008 onwards. Data shown in this report makes visible the vulnerability of rural NEET youth to these downturns from 2009 to 2013. In line with this, Early-school leaving (ESLET) and unemployment rates in rural areas were more pronounced in 2013 and the following years for rural youth in comparison with youth living in urban areas and towns. However, in the last two years (2017-2019) there has been a sharp decrease in these indicators placing youth living rural areas, on average, in line with the rest (i.e., an average NEET youth rate in Spain 15% versus 16% for rural areas).


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