New Graduate RN Transition Program Evaluation and Replication

Evaluates the impact of pilot programs to improve new nurses' self-confidence, competencies in acute and non-acute specialties and advanced generalist skills, and employment outcomes. Includes best practices and recommendations for future programs

Incorporating Analytics into a Business Process Modelling Course

Embedding analytics is about integrating data analytics into operational systems that are part of an organization’s business processes. Currently, most organizations focus on automation business processes and enhancing productivity. However, going forward, in order to stay competitive, organizations have to go beyond automating their processes, by making them more intelligent, by embedding analytics into their processes and business applications. Therefore, there is need for enhancing the knowledge and skills of BPM professionals with know-how on improving a business process by embedding analytics into the workflow. In this paper contribution, the authors share their experience on how an existing process modelling, analysis and solution designing course was modified in order to incorporate the analytics component. The paper describes in detail the content, pedagogy, and lessons learned when introducing analytics into an existing business process modelling course. Thus providing one pathway for IS professors to adapt their current process modelling, enterprise systems and BPM courses to include analytics

Implementation of Business Intelligence on Banking, Retail, and Educational Industry

Information technology is useful to automate business process involving considerable data transaction in the daily basis. Currently, companies have to tackle large data transaction which is difficult to be handled manually. It is very difficult for a person to manually extract useful information from a large data set despite of the fact that the information may be useful in decision-making process. This article studied and explored the implementation of business intelligence in banking, retail, and educational industries. The article begins with the exposition of business intelligence role in the industries; is followed by an illustration of business intelligence in the industries and finalized with the implication of business intelligence implementation

A web-based course assessment tool with direct mapping to student outcomes

The assessment of curriculum outcomes is an essential element for continuous academic improvement. However, the collection, aggregation and analysis of assessment data are notoriously complex and time-consuming processes. At the same time, only few developments of supporting electronic processes and tools for continuous academic program assessment and curriculum performance feedback have emerged. In this paper, we introduce a novel course assessment process supported by a Web based interface that articulates and streamlines the assessment data collection, performance evaluation and tracking of remedial recommendations. To close the assessment loop, the Web interface provides also a mechanism to follow up on the implementation of remedial recommendations and analyzes their associated reflective actions during the subsequent course assessment cycle. A guide to map assessment instruments to the course and overall program outcomes is advocated by the proposed tool to propagate the course assessment results towards higher educational objectives (e.g., student outcomes) in a dashboard-like assessment interface. This approach streamlines improvements in education through reflecting the achievement of course outcomes on the achievement of higher educational objectives.In addition, the tool maps the course outcomes to the corresponding course outlines to facilitate the detection of areas where revisions in the instruction and content is needed, and to best respond to recommendations and remedial actions. We provide a methodical approach as well as a Web-based automation of the assessment process, which we evaluate in the context of our regular academic assessment cycles that have eventually led to a successful international accreditation experience. The collected assessment data shows a significant improvement in the achievement rate of the student outcomes after deploying the tool

Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning

The realities of the 21st-century learner require that schools and educators fundamentally change their practice. "Educators must produce college- and career-ready graduates that reflect the future these students will face. And, they must facilitate learning through means that align with the defining attributes of this generation of learners."Today, we know more than ever about how students learn, acknowledging that the process isn't the same for every student and doesn't remain the same for each individual, depending upon maturation and the content being learned. We know that students want to progress at a pace that allows them to master new concepts and skills, to access a variety of resources, to receive timely feedback on their progress, to demonstrate their knowledge in multiple ways and to get direction, support and feedback from—as well as collaborate with—experts, teachers, tutors and other students.The result is a growing demand for student-centered, transformative digital learning using competency education as an underpinning.iNACOL released this paper to illustrate the technical requirements and functionalities that learning management systems need to shift toward student-centered instructional models. This comprehensive framework will help districts and schools determine what systems to use and integrate as they being their journey toward student-centered learning, as well as how systems integration aligns with their organizational vision, educational goals and strategic plans.Educators can use this report to optimize student learning and promote innovation in their own student-centered learning environments. The report will help school leaders understand the complex technologies needed to optimize personalized learning and how to use data and analytics to improve practices, and can assist technology leaders in re-engineering systems to support the key nuances of student-centered learning

Automated impact assessment - How digitizing government enables rapid and tailor-made policy responses

As interest in the digital transformation of public administration grows, the main challenge remains to improve government governance systems and integrate a wider range of evidence into decisionmaking processes. The successful digitalization and application of such approaches improves the quality, responsiveness and flexibility of public administrations. The digialtization of processes has made it possible to use micro-level data to assess the impact of a policy or program and apply the feedback to improve the design and delivery of public services. Evidence-based policy-making evaluates programs based on their visible impacts. Large-scale data collected through digitized governance, coupled with econometric impact assessment, provides an ideal working toolkit for this. However, the current situation of European governments is one of slow adoption, as they are often slow to respond to new challenges. This is due to the static one-off impact assessment approaches used, the results of which quickly become outdated. With further digitalization, improvement of systems, and a rapidly changing situation, there is a need to speed up institutions’ ability to quickly draw working solutions to offset the effects of unexpected events in society and economy and react without delays if policy effects dissipate. This paper demonstrates how a high level of digitalization in government allows addressing such issues by automating causal impact assessment and making it a continuous part of the service delivery. The use case is an automated system for assessing active labour market policies in Estonia using individual-level data from government digital registers. Building on this, it shows how impact assessment automation depends on automatically generated data, only available due to the digitalization of other public services, and how versatile it is when it comes to proving casual evidence in a suddenly changing environment

Automating Society : Taking Stock of Automated Decision-Making in the EU

This is the first comprehensive study regarding the state of automated decision-making in Europe. Experts have looked at the situation at the EU level but also in 12 Member States: Belgium, Denmark, Finland, France, Germany, Italy, Netherlands Poland, Slovenia, Spain, Sweden and the UK. They assessed not only the political discussions and initiatives in these countries but also present a section "ADM in Action" for all states, listing examples of automated decision-making already in use

Automating Society: Taking Stock of Automated Decision-Making in the EU. BertelsmannStiftung Studies 2019

Imagine you’re looking for a job. The company you are applying to says you can have a much easier application process if you provide them with your username and password for your personal email account. They can then just scan all your emails and develop a personality profile based on the result. No need to waste time filling out a boring questionnaire and, because it’s much harder to manipulate all your past emails than to try to give the ‘correct’ answers to a questionnaire, the results of the email scan will be much more accurate and truthful than any conventional personality profiling. Wouldn’t that be great? Everyone wins—the company looking for new personnel, because they can recruit people on the basis of more accurate profiles, you, because you save time and effort and don’t end up in a job you don’t like, and the company offering the profiling service because they have a cool new business model