The Global Burden of Animal Diseases (GBADs) programme will provide data-driven evidence that policy-makers can use to evaluate options, inform decisions, and measure the success of animal health and ...welfare interventions. The GBADs' Informatics team is developing a transparent process for identifying, analysing, visualising and sharing data to calculate livestock disease burdens and drive models and dashboards. These data can be combined with data on other global burdens (human health, crop loss, foodborne diseases) to provide a comprehensive range of information on One Health, required to address such issues as antimicrobial resistance and climate change. The programme began by gathering open data from international organisations (which are undergoing their own digital transformations). Efforts to achieve an accurate estimate of livestock numbers revealed problems in finding, accessing and reconciling data from different sources over time. Ontologies and graph databases are being developed to bridge data silos and improve the findability and interoperability of data. Dashboards, data stories, a documentation website and a Data Governance Handbook explain GBADs data, now available through an application programming interface. Sharing data quality assessments builds trust in such data, encouraging their application to livestock and One Health issues. Animal welfare data present a particular challenge, as much of this information is held privately and discussions continue regarding which data are the most relevant. Accurate livestock numbers are an essential input for calculating biomass, which subsequently feeds into calculations of antimicrobial use and climate change. The GBADs data are also essential to at least eight of the United Nations Sustainable Development Goals.
This methodological-theoretical synergy provides an integrative framework of learning analytics through the development of the human-and-machine symbiotic reinforcement learning. The framework ...intends to address the challenges of the current learning analytics model, including a lack of internal validity, generalizability, immediacy, transferability, and interpretability for precision education. The proposed framework consists of a master component (the brain) and its four subsuming components: social networking, the smart classroom, the intelligent agent, and the dashboard. The brain component takes in and analyzes multimodal streams of student data from the other components with the model-based reinforcement learning, which forms policies of adequate actions that maximize the long-term rewards for both the human and machine in the seamless learning environment. An example case plan in advanced statistics was demonstrated to illustrate the course description, data collected in each component, and how the components meet different features of the smart learning environment to deliver precision education. An empirical demonstration was provided using some selected mulitmodal data to inform the effectiveness of the proposed framework. The human-and-machine symbiotic reinforcement learning has theoretical and practical implications for the next-generation learning analytics models and research.
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This study introduced BookRoll, a digital teaching material delivery and e-book reading system, to record and trace students' preview status through the BookRoll dashboard in a university course and ...further support their self-regulated learning. One hundred nine freshmen from two separate classes at a university located in central Taiwan participated in this study, and their self-regulated learning and self-efficacy as well as academic achievement were evaluated. One class of 53 students was assigned to an experimental group using the BookRoll system embedded in Moodle, and the other class of 56 students was assigned a control group using Moodle without embedded BookRoll. This study indicated that the group of students using BookRoll exhibited significant improvements in self-regulated learning and self-efficacy; furthermore, the gain scores of the experiment group in self-regulated learning and self-efficacy were both significantly higher than those of the control group. In addition, a significant difference in academic achievement was also found between the two groups. Moreover, students' online e-book reading behaviors including attaching bookmarks, adding/deleting markers, attaching/removing/editing memos, and slide switching (next/previous/jumping page) were positively significantly correlated to their academic achievement.
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CMK company is a retail company that sell and distributes miniature vehicle items to small stores. CMK has several branches in various countries that use for operational and storage warehouse. This ...company faces the problem for analysing sales to decide the useful strategy since this company only uses Online Transaction Processing (OLTP) database. This study implements Online Analysis Processing (OLAP) database and data warehouse to provide useful information for this company by using the nine-step method designed by Kimball & Ross. The data will be performed into dashboard to make easier for CMK Company to analyze data. Furthermore, many useful information can be provided in short and efficient time.
This paper presents the Space+ Data Dashboard (SDD), a robust platform developed by the Philippine Space Agency (PhilSA), designed to revolutionize space data access for institutions and citizens. ...Built using open-source technologies, the SDD seamlessly manages spatial and non-spatial datasets. The SDD is composed of three core components: backend, frontend, and database. The backend uses PostgreSQL with PostGIS for data storage and indexing, Geoserver for vector files, and the Open Data Cube for raster files. Django handles other data types and serves API requests. The front-end uses TerriaMap, a customizable web front-end built on TerriaJS to provide public access and geo-visualization, and ReactJS for user interface and interaction. The SDD is envisioned to fulfill PhilSA’s mandate to empower government institutions and the Filipino people using space technologies. It democratizes data access to facilitate the use of space + geospatial data in disaster management, urban planning, environmental monitoring, and informed decision-making. The dashboard also offers direct downloads of various space-derived datasets. In championing data accessibility, PhilSA ensures data-driven decision-making, advancing both national space initiatives and the United Nations' Sustainable Development Goals.
Teacher dashboards are a specific form of analytics in which visual displays provide teachers with information about their students; for example, concerning student progress and performance on tasks ...during lessons or lectures. In the present paper, we focus on the role of teacher dashboards in the context of teacher decision-making in K–12 education. There is large variation in teacher dashboard use in the classroom, which could be explained by teacher characteristics. Therefore, we investigate the role of teacher characteristics — such as experience, age, gender, and self-efficacy — in how teachers use dashboards. More specifically, we present two case studies to understand how diversity in teacher dashboard use is related to teacher characteristics. Surprisingly, in both case studies, teacher characteristics were not associated with dashboard use. Based on our findings, we propose an initial framework to understand what contributes to diversity of dashboard use. This framework might support future research to attribute diversity in dashboard use. This paper should be seen as a first step in examining the role of teacher characteristics in dashboard use in K–12 education.
Abstract
Due to the increase in withdrawals and temporary absences of students from changes in the external environment, distance learning universities are trying to establish various policies and ...increase the number of enrolled students, and at the same time, are trying to establish various policies and efforts to increase the enrollment. However, it is difficult to systematically diagnose the main cause of the interruption of students, and prior research efforts related to the problem of student suspension in distance learning universities have accumulated, since there are various reasons for the student suspensions. In the proposed distance university Studies Suspension Prevention System (SSPS), distance university students can use two types of learning analytics services. In order to analyze learning activities, we propose the asynchronous learning activity analysis module, and the synchronous learning activity analysis module. In the asynchronous analysis module and symchronous analysis module, quiz, LINE group chatting & discussion forum communication, and online lecture has a learning state score according to the lecturer’s directions. Learning activities in the learning management system have three kinds of learning states, passive activity state, negative activity state, and medium activity state. Learning activity states are used to predict the student learning state. In the proposed Student Support System, there are two types of learning support services connected to the smart learning portal server. One is the intelligent distance university chatbot service for personalized chatting and caring services. The other is push message services for alarm, warning, notices, and alerts, such as dashboard service.
Small-scale fisheries are responsible for landing half of the world's fish catch, yet there are very sparse data on these fishing activities and associated fisheries production in time and space. ...Fisheries-dependent data underpin scientific guidance of management and conservation of fisheries systems, but it is inherently difficult to generate robust and comprehensive data for small-scale fisheries, particularly given their dispersed and diverse nature. In tackling this challenge, we use open source software components including the Shiny R package to build PeskAAS; an adaptable and scalable digital application that enables the collation, classification, analysis and visualisation of small-scale fisheries catch and effort data. We piloted and refined this system in Timor-Leste; a small island developing nation. The features that make PeskAAS fit for purpose are that it is: (i) fully open-source and free to use (ii) component-based, flexible and able to integrate vessel tracking data with catch records; (iii) able to perform spatial and temporal filtering of fishing productivity by fishing method and habitat; (iv) integrated with species-specific length-weight parameters from FishBase; (v) controlled through a click-button dashboard, that was co-designed with fisheries scientists and government managers, that enables easy to read data summaries and interpretation of context-specific fisheries data. With limited training and code adaptation, the PeskAAS workflow has been used as a framework on which to build and adapt systematic, standardised data collection for small-scale fisheries in other contexts. Automated analytics of these data can provide fishers, managers and researchers with insights into a fisher's experience of fishing efforts, fisheries status, catch rates, economic efficiency and geographic preferences and limits that can potentially guide management and livelihood investments.
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Abstract
Background
All sustainable developmental goals (SDGs) require implementing sustainable strategies and monitoring to track progress. But what is known of sub-Sahara Africa (SSA)'s efforts in ...following this stride to reduce by 30% mortality from non-communicable diseases (NCDs) through prevention (SDG 3.4), by considering the effect of social determinants of health (SODHs) on type 2 diabetes increasing prevalence?
Methods
Our search produced 2005 unique articles. Only 10 studies were used in the analysis of this study. These studies include 1 from Botswana, 2 from Ghana, 2 from Kenya, 3 from Nigeria and 2 from South Africa. The findings were evaluated in a greater extent.
Results
All studies (100%) showed non-adherence to exercise and poor glycemic control. 7 studies (70%) on education revealed lack of knowledge or misconceptions, 5 studies (50%) with obesity showed a strong linkage between obesity and type 2 diabetes, and 4 studies (40%) on diet, showed diets high in carbohydrates, saturated fats, and sodium predisposition to type 2 diabetes. All studies (100%) linked urbanization with an increased prevalence of type 2 diabetes.
Conclusions
Changes in SODHs seem to be contributing to the growing prevalence of diabetes in SSA. These changes with other key data should be considered and tailored to policy processes, environment, infrastructures, and norms for prevention strategies and informing dashboard development for SDG 3.4.
Key messages
Social determinants of health must reflect in relevant causal pathways, settings, and sectors for preventive intervention such as in taxation; regulation of food advertising, school, and healthcare. Analysis of the effect of the changing social determinants of health on type 2 diabetes, will assist in establishing indicators for the dashboard development for SDG 3.4 for sub-Sahara Africa.
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Abstract
Background
In Pakistan, only 66% of children receive their basic vaccinations. However, the figure masks significant inequalities in vaccine coverage between urban and rural residences, ...slums and areas distantly located from EPI centers. Frequent outbreaks of vaccine-preventable diseases such as polio and measles, in urban cities like Karachi, signal the need for expanding vaccine services to underserved areas. In Apr'19, we introduced the Mobile Immunization Van initiative in Karachi in collaboration with EPI Sindh. Currently, two vans are deployed in hard-to-reach areas and slums to immunize under-2 children for routine vaccines.
Methods
Before the van visit, mobilization efforts are conducted in targeted areas to encourage caretakers to bring their child for vaccination. On the day of visit, the van is parked at a central location, and announcements are played on a loudspeaker to attract caregivers. All vaccinations are administered in the van, and entries are recorded in Government's Digital Immunization Registry along with GIS coordinates of immunized children. The data is then automatically transferred on to a web-dashboard for analysis and tracking.
Results
From Apr'19 to Jan'20, the vans have vaccinated 2,867 children, out of which 50% had never been immunized prior to the van visit. Of those who received their follow-up vaccines from the van, 80% were at least 4 weeks beyond from their vaccine due date. GIS analysis of van data confirmed that immunizations were conducted in slums, and areas distantly located from EPI centers. Moreover, compared to government outreach activity, proportion of BCG, Penta3 and Measles1 administrations in slums was higher through the vans by 5%, 6%, and 4% respectively.
Conclusions
The vans provide an opportunity for immunizing never-vaccinated children and children defaulting on their vaccine schedule, from the most vulnerable geographies, while simultaneously enrolling them in the Government's EPI Program for effective tracking.
Key messages
The mobile vans help achieve universal immunization coverage through provision of vaccine services in slum and rural hard-to-reach areas with limited access to government-provided services. The mobile vans help vaccinate and capture never-immunized children into the Government’s EPI records, reducing the number of children missed through routine services.
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