Using Project Management Techniques to Design a PMP Mathematics Study App for the Windows Universal Platform

Background As a late comer to the smartphone market, Microsoft has fallen behind the Apple and Google app ecosystems in the quantity and quality of apps offered. To attract developer talent, Microsoft released the Universal Windows Platform which enables apps to run across Windows devices with few additional modifications. Although the Windows app ecosystem has realized an increased number of available apps, few apps related to project management are currently available. About the project This project will design a PMP Certification Mathematics Study App for the Universal Windows Platform which will serve as a reference and study aid for the PMP certification exam. The app will be available to mobile and PC users who are utilizing the Microsoft Windows 10 and Windows 8 operating systems. Features of the app will include project management formula lookup, formula flashcards, and practice problems. At the completion of the project, the app will be submitted to the Windows Store for review and publishing to the Windows 10 application ecosystem. Approach The project scope will include the design of the app from requirements gathering to completion. Project deliverables will be aligned with Windows store applications evaluation criteria for responsiveness, reliability, and style. This project will conclude with submission of a completed application design to the project sponsor.Title Page / Table of Contents / List of Exhibits / Abstract / Background / About the project / Approach / Keywords / Introduction / Project Purpose / Project Approach / Research and Analysis / Research Approach / Research Analysis / Application Design Rating Verification / Research Objective 1: Investigate the preferred learning style of potential users / Research Objective 1: Design Conclusions and Implications / Flashcards Module / Formula Builder Module / Formula Reference Module / Research Objective 2: Investigate the most important aspect of user satisfaction / Research Objective 2: Design Conclusions and Implications / Research Conclusions / Requirements Gathering / User Interface Design / Project Deliverable Design / ViTech CORE / Input Application Requirements / Identify Application Components / Identify Component Functions / Identify Use Cases and Test Activities / Project Deliverables / Application Design Documents / Application Hierarchy / Conclusions and Recommendations / ViTech CORE Software Con/ lusions / Graphing Capabilities / Diagnostics Capabilities / Requirements Mapping and Verification / Final Project Deliverables / Recommendations for Further Research and Development / Application Publishing / Further Development and Product Updates / User Feedback Collection / Application Update Opportunities / Application Expansion Opportunitie

Acceptance model of electronic medical record

This paper discusses acceptance issues of Electronic Medical Record System (EMR), particularly in Malaysia. A detailed overview of EMR and its benefits are firstly discussed. A number of acceptance models are scrutinized. Then factors affecting EMR acceptance are put forward. Finally, before proposing an EMR acceptance model, an instrument formed by adapting and then finding its factors loading is presented

Teaching periodontal pocket charting to dental students: a comparison of computer assisted learning and traditional tutorials

AIM: The aim of this study was to compare the effectiveness of a computer assisted learning (CAL) programme with that of traditional small group tutorials in teaching theoretical and practical aspects of periodontal pocket charting. METHOD: Sixty-one third year undergraduate dental students were randomized to either receive a tutorial or to work through the CAL programme. Students using the CAL programme completed questionnaires relating to previous computer experience and the ease of use of the programme. All students were assessed immediately after the intervention by means of a confidence log, a practical exercise and a further confidence log. They were assessed again three weeks later by means of a confidence log and a multiple-choice written test. RESULTS: There were very few significant differences between groups for any of the assessments used. However, subjective comments indicated that students occasionally felt disadvantaged if they had not received a tutorial. CONCLUSION: CAL and traditional teaching methods are equally effective in teaching periodontal pocket charting to undergraduate dental students

An e-learning platform for delivering educational contents in a school environment

Learning is a continuous process, without end, which takes place throughout life, and is the result of the interaction of an individual with a physical external environment, a social context or with herself. In what new technologies may help improving and making more effective the interaction of an individual during his learning process? This paper describes the use of a platform for delivering educational contents to students, to put theories into practice through the use of an LMS and highlight the strengths and weaknesses that have these learning tools in a school environment, in which - besides its formative aspect - upbringing is important.learning management system, digital contents.

The works metallurgist: An evaluation of a CAL package on phase diagrams

The Works Metallurgist is used in the Open University course: Materials — Engineering and Science. It is being evaluated as part of a larger study of CAL teaching in Science and Technology at the Open University. With 540 students, the course provides a sufficiently large sample for a range of evaluation methods to be employed in a variety of settings (e.g. home, residential school). The methods used include questionnaires, attitude scales and pre/post achievement tests, observations and interviews. The focus of the evaluation exercise is on the effectiveness of CAL in contributing to student learning. The issue of the educational quality of the program and its instructional features are considered in this paper, in association with the goals of the program

Learning to Address Health Inequality in the United States with a Bayesian Decision Network

Life-expectancy is a complex outcome driven by genetic, socio-demographic, environmental and geographic factors. Increasing socio-economic and health disparities in the United States are propagating the longevity-gap, making it a cause for concern. Earlier studies have probed individual factors but an integrated picture to reveal quantifiable actions has been missing. There is a growing concern about a further widening of healthcare inequality caused by Artificial Intelligence (AI) due to differential access to AI-driven services. Hence, it is imperative to explore and exploit the potential of AI for illuminating biases and enabling transparent policy decisions for positive social and health impact. In this work, we reveal actionable interventions for decreasing the longevity-gap in the United States by analyzing a County-level data resource containing healthcare, socio-economic, behavioral, education and demographic features. We learn an ensemble-averaged structure, draw inferences using the joint probability distribution and extend it to a Bayesian Decision Network for identifying policy actions. We draw quantitative estimates for the impact of diversity, preventive-care quality and stable-families within the unified framework of our decision network. Finally, we make this analysis and dashboard available as an interactive web-application for enabling users and policy-makers to validate our reported findings and to explore the impact of ones beyond reported in this work.Comment: 8 pages, 4 figures, 1 table (excluding the supplementary material), accepted for publication in AAAI 201

OpenML Benchmarking Suites

Machine learning research depends on objectively interpretable, comparable, and reproducible algorithm benchmarks. Therefore, we advocate the use of curated, comprehensive suites of machine learning tasks to standardize the setup, execution, and reporting of benchmarks. We enable this through software tools that help to create and leverage these benchmarking suites. These are seamlessly integrated into the OpenML platform, and accessible through interfaces in Python, Java, and R. OpenML benchmarking suites are (a) easy to use through standardized data formats, APIs, and client libraries; (b) machine-readable, with extensive meta-information on the included datasets; and (c) allow benchmarks to be shared and reused in future studies. We also present a first, carefully curated and practical benchmarking suite for classification: the OpenML Curated Classification benchmarking suite 2018 (OpenML-CC18)

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Selection of Statistical Software for Solving Big Data Problems: A Guide for Businesses, Students, and Universities

The need for analysts with expertise in big data software is becoming more apparent in today’s society. Unfortunately, the demand for these analysts far exceeds the number available. A potential way to combat this shortage is to identify the software taught in colleges or universities. This article will examine four data analysis software—Excel add-ins, SPSS, SAS, and R—and we will outline the cost, training, and statistical methods/tests/uses for each of these software. It will further explain implications for universities and future students