Success for Every Child: Milwaukee Succeeds Milestone Report 2013

Milwaukee Succeeds is a unique effort is bringing together all the key stakeholders to support a common set of goals to improve educational outcomes for all children in the city of Milwaukee. Milwaukee and its children often end up on the wrong end of the list when it comes to education, poverty and the myriad of social and emotional issues surrounding them. To overcome these challenges, it will take a vision that all in our community embrace. After all, "success for every child, in every school" is a pretty large undertaking; one that will require a big commitment to fulfill. Milwaukee Succeeds believes our community is up for the challenge because we believe in the promise of our city. We know how hard individuals and groups are already working to improve the educational environment in Milwaukee. We have seen some dedicated efforts getting remarkable results with the children in our schools. But we also know it will take more than hard work. The work is too big for any one organization to tackle and the issues are too complex for any single group to overcome. It will take all of us -- parents, educators, community leaders, faith-based leaders, business leaders and more -- working toward our common goals. This Milestone Report lays out the challenges we face and the goals that have been set to tackle them. In the data section, the issues are outlined as they exist today - some of which may seem daunting. With each challenge, there are clear outcomes we have set to achieve by 2020. But this report also makes a promise: We pledge to work together to achieve the goals we have laid out and to fulfill our commitment to the kids. That is the spirit of Milwaukee Succeeds and all who will join forces with us to take on this important work. We are a diverse group who pledges to collaborate and to focus on issues where our collective effort can make an impact. One issue at a time, one problem at a time working across the spectrum of cradle to career is how we will see success unfold. We share the communitywide sense of urgency on improving the educational outcomes for children in our city, but we know that to create lasting change, we have to be in this for the long haul. This Milestone Report is just a starting point. It lays out the journey we have in front of us and the goals we expect to achieve along the way. We believe that by working together we all will get there. We know that by working together, we all will help Milwaukee succeed

Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

Cultural diversity and information and communication technology impacts on global virtual teams: An exploratory study.

Modern organizations face many significant challenges because of turbulent environments and a competitive global economy. Among these challenges are the use of information and communication technology (ICT), a multicultural workforce, and organizational designs that involve global virtual teams. Ad hoc teams create both opportunities and challenges for organizations and many organizations are trying to understand how the virtual environment affects team effectiveness. Our exploratory study focused on the effects of cultural diversity and ICT on team effectiveness. Interviews with 41 team members from nine countries employed by a Fortune 500 corporation were analyzed. Results suggested that cultural diversity had a positive influence on decision‐making and a negative influence on communication. ICT mitigated the negative impact on intercultural communication and supported the positive impact on decision making. Effective technologies for intercultural communication included e‐mail, teleconferencing combined with e‐Meetings, and team rooms. Cultural diversity influenced selection of the communication media

Silver Dreams Fund Learning and Evaluation Contract: Final report June 2014

This is a summary of the Final Report which presents the findings of the evaluation of the Big Lottery Fund's Silver Dreams Fund conducted by Ecorys.The Silver Dreams Fund was a £10 million programme which sought to address the gaps in provision by challenging organisations to come up with an innovative idea for a project that would "pioneer ways to help vulnerable older people deal more effectively with life-changing events".Our approach involved both formative and summative elements and was based upon a robust and evidence-based outcome evaluation framework. In addition, we have also undertaken an evaluation of the new programme management processes employed by the Big Lottery Fund which has been reported separately.In summary, the evaluation involved:- development of an evaluation framework and common indicators to measure outcomes;- provision of a package of self-evaluation support to projects;- programme level work to provide independent primary qualitative research and to validate findings from self-evaluations;- a range of learning activities; and- analysis and reporting

AI for the Common Good?! Pitfalls, challenges, and Ethics Pen-Testing

Recently, many AI researchers and practitioners have embarked on research visions that involve doing AI for "Good". This is part of a general drive towards infusing AI research and practice with ethical thinking. One frequent theme in current ethical guidelines is the requirement that AI be good for all, or: contribute to the Common Good. But what is the Common Good, and is it enough to want to be good? Via four lead questions, I will illustrate challenges and pitfalls when determining, from an AI point of view, what the Common Good is and how it can be enhanced by AI. The questions are: What is the problem / What is a problem?, Who defines the problem?, What is the role of knowledge?, and What are important side effects and dynamics? The illustration will use an example from the domain of "AI for Social Good", more specifically "Data Science for Social Good". Even if the importance of these questions may be known at an abstract level, they do not get asked sufficiently in practice, as shown by an exploratory study of 99 contributions to recent conferences in the field. Turning these challenges and pitfalls into a positive recommendation, as a conclusion I will draw on another characteristic of computer-science thinking and practice to make these impediments visible and attenuate them: "attacks" as a method for improving design. This results in the proposal of ethics pen-testing as a method for helping AI designs to better contribute to the Common Good.Comment: to appear in Paladyn. Journal of Behavioral Robotics; accepted on 27-10-201

Big Data for Traffic Monitoring and Management

The last two decades witnessed tremendous advances in the Information and Com- munications Technologies. Beside improvements in computational power and storage capacity, communication networks carry nowadays an amount of data which was not envisaged only few years ago. Together with their pervasiveness, network complexity increased at the same pace, leaving operators and researchers with few instruments to understand what happens in the networks, and, on the global scale, on the Internet. Fortunately, recent advances in data science and machine learning come to the res- cue of network analysts, and allow analyses with a level of complexity and spatial/tem- poral scope not possible only 10 years ago. In my thesis, I take the perspective of an In- ternet Service Provider (ISP), and illustrate challenges and possibilities of analyzing the traffic coming from modern operational networks. I make use of big data and machine learning algorithms, and apply them to datasets coming from passive measurements of ISP and University Campus networks. The marriage between data science and network measurements is complicated by the complexity of machine learning algorithms, and by the intrinsic multi-dimensionality and variability of this kind of data. As such, my work proposes and evaluates novel techniques, inspired from popular machine learning approaches, but carefully tailored to operate with network traffic. In this thesis, I first provide a thorough characterization of the Internet traffic from 2013 to 2018. I show the most important trends in the composition of traffic and users’ habits across the last 5 years, and describe how the network infrastructure of Internet big players changed in order to support faster and larger traffic. Then, I show the chal- lenges in classifying network traffic, with particular attention to encryption and to the convergence of Internet around few big players. To overcome the limitations of classical approaches, I propose novel algorithms for traffic classification and management lever- aging machine learning techniques, and, in particular, big data approaches. Exploiting temporal correlation among network events, and benefiting from large datasets of op- erational traffic, my algorithms learn common traffic patterns of web services, and use them for (i) traffic classification and (ii) fine-grained traffic management. My proposals are always validated in experimental environments, and, then, deployed in real opera- tional networks, from which I report the most interesting findings I obtain. I also focus on the Quality of Experience (QoE) of web users, as their satisfaction represents the final objective of computer networks. Again, I show that using big data approaches, the network can achieve visibility on the quality of web browsing of users. In general, the algorithms I propose help ISPs have a detailed view of traffic that flows in their network, allowing fine-grained traffic classification and management, and real-time monitoring of users QoE

Functional Skills Support Programme: Developing functional skills in physical education

This booklet is part of "... a series of 11 booklets which helps schools to implement functional skills across the curriculum. The booklets illustrate how functional skills can be applied and developed in different subjects and contexts, supporting achievement at Key Stage 3 and Key Stage 4. Each booklet contains an introduction to functional skills for subject teachers, three practical planning examples with links to related websites and resources, a process for planning and a list of additional resources to support the teaching and learning of functional skills." - The National Strategies website