33,742 research outputs found

    Cracking the Code on Stem: A People Strategy for Nevada\u27s Economy

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    Nevada has in place a plausible economic diversification strategy—and it’s beginning to work. Now, the state and its regions need to craft a people strategy. Specifically, the state needs to boost the number of Nevadans who possess at least some postsecondary training in the fields of science, technology, engineering, or math—the so-called “STEM” disciplines (to which some leaders add arts and design to make it “STEAM”). The moment is urgent—and only heightened by the projected worker needs of Tesla Motors’ planned “gigafactory” for lithium-ion batteries in Storey County. Even before the recent Tesla commitment, a number of the more high-tech industry sectors targeted by the state’s new economic diversification strategy had begun to deliver significant growth. Most notable in fast-growing sectors like Business IT Ecosystems (as defined by the Governor’s Office for Economic Development) and large sectors like Health and Medical Services, this growth has begun to increase the demand in Nevada for workers with at least a modicum of postsecondary training in one or more STE M discipline. However, there is a problem. Even though many available opportunities require no more than the right community college certificate, insufficient numbers of Nevadans have pursued even a little STEM training. As a result, too few Nevadans are ready to participate in the state’s emerging STEM economy. The upshot: Without concerted action to prepare more Nevadans for jobs in STEM-intensive fields, skills shortages could limit growth in the state’s most promising target industries and Nevadans could miss out on employment that offers superior paths to opportunity and advancement. Which is the challenge this report addresses: Aimed at focusing the state at a critical moment, this analysis speaks to Nevada’s STEM challenge by providing a new assessment of Nevada’s STEM economy and labor market as well as a review of actions that leaders throughout the state—whether in the public, private, civic, or philanthropic sectors—can take to develop a workforce capable of supporting continued growth through economic diversification

    Data Analytics in Higher Education: Key Concerns and Open Questions

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    “Big Data” and data analytics affect all of us. Data collection, analysis, and use on a large scale is an important and growing part of commerce, governance, communication, law enforcement, security, finance, medicine, and research. And the theme of this symposium, “Individual and Informational Privacy in the Age of Big Data,” is expansive; we could have long and fruitful discussions about practices, laws, and concerns in any of these domains. But a big part of the audience for this symposium is students and faculty in higher education institutions (HEIs), and the subject of this paper is data analytics in our own backyards. Higher education learning analytics (LA) is something that most of us involved in this symposium are familiar with. Students have encountered LA in their courses, in their interactions with their law school or with their undergraduate institutions, instructors use systems that collect information about their students, and administrators use information to help understand and steer their institutions. More importantly, though, data analytics in higher education is something that those of us participating in the symposium can actually control. Students can put pressure on administrators, and faculty often participate in university governance. Moreover, the systems in place in HEIs are more easily comprehensible to many of us because we work with them on a day-to-day basis. Students use systems as part of their course work, in their residences, in their libraries, and elsewhere. Faculty deploy course management systems (CMS) such as Desire2Learn, Moodle, Blackboard, and Canvas to structure their courses, and administrators use information gleaned from analytics systems to make operational decisions. If we (the participants in the symposium) indeed care about Individual and Informational Privacy in the Age of Big Data, the topic of this paper is a pretty good place to hone our thinking and put into practice our ideas

    A Novel Self-Organizing Map (SOM) With Data Mining Model for Formulation of Vocational Education Policies

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    Data mining is a process of extracting valuable and previously unknown patterns, insights, and knowledge from large datasets. data mining techniques enable the analysis of educational data to inform multi-level vocational education policies that contribute to regional sustainable development. By leveraging the power of data, policymakers can make evidence-based decisions, align vocational education with regional needs, and enhance the effectiveness and relevance of vocational education programs in promoting sustainable development. In this paper proposed an Associative Rule Kohonen SOM (AR-KS) for multi-level vocational educational policies assessment for sustainable development. Initially, the proposed AR-KS model collects relevant data, including information on vocational education programs, student performance records, regional development indicators, and policy documents. This data is then preprocessed to ensure consistency and quality. The next step involves training a Kohonen SOM using the preprocessed data. The SOM forms a topological map where each neuron represents a unique combination of policy variables and regional development factors. This map captures the multidimensional relationships among the variables and provides a visual representation of the policy space. The relationship between the patterns is computed with the associative rule-based training of SOM between variables. The analysis of the AR-KS framework allows policymakers to assess the impact of different vocational education policies on sustainable development goals. Overall, the proposed AR-KS framework offers a novel approach for assessing multi-level vocational educational policies in the context of sustainable development

    Learning analytics for the global south

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    Learning Analytics for the Global South is a compilation of papers commissioned for the Digital Learning for Development (DL4D) project. DL4D is part of the Information Networks in Asia and Sub-Saharan Africa (INASSA) program funded jointly by the International Development Research Centre (IDRC) of Canada and the Department for International Development (DFID) of the United Kingdom, and administered by the Foundation for Information Technology Education and Development (FIT-ED) of the Philippines. DL4D aims to examine how digital learning could be used to address issues of equity, quality, and efficiency at all educational levels in developing countries. Over the past two years, DL4D has brought together leading international and regional scholars and practitioners to critically assess the potentials, prospects, challenges, and future directions for the Global South in key areas of interest around digital learning. It commissioned discussion papers for each of these areas from leading experts in the field: Diana Laurillard of the University College London Knowledge Lab, for learning at scale; Chris Dede of Harvard University, for digital game-based learning; Charalambos Vrasidas of the Centre for the Advancement of Research and Development in Educational Technology, for cost-effective digital learning innovations; and for learning analytics, the subject of this compilation, Dragan Gašević of the University of Edinburgh Moray House School of Education and School of Informatics. Each discussion paper is complemented by responses from a developing country-perspective by regional experts in Asia, Latin America, Africa, and the Middle East. Learning Analytics for the Global South considers how the collection, analysis, and use of data about learners and their contexts have the potential to broaden access to quality education and improve the efficiency of educational processes and systems in developing countries around the world. In his discussion paper, Prof. Gašević articulates these potentials and suggests how learning analytics could support critical digital learning and education imperatives such as quality learning at scale and the acquisition of 21st century skills. Experts from Africa (Paul Prinsloo of the University of South Africa), Mainland China (Bodong Chen of the University of Minnesota, USA and Yizhou Fan of Peking University, People’s Republic of China), Southeast Asia (Ma. Mercedes T. Rodrigo of the Ateneo de Manila University, Philippines), and Latin America (Cristóbal Cobo and Cecilia Aguerrebere, both of the Ceibal Foundation, Uruguay) situate Prof. Gašević’s proposals in their respective regional contexts, framing their responses around six key questions: 1. What are the main trends and challenges in education in your region? 2. How can learning analytics address these challenges? 3. What models of learning analytics adoption would be most effective in your region? 4. What are the barriers in adoption of learning analytics in your region and how could these be mitigated? 5. How do you envision ethical use and privacy protection in connection with learning analytics being addressed in your region? 6. How can the operationalization of learning analytics be futureproofed in your region? We hope that this compilation will serve as a springboard for deeper conversations about the adoption and sustained use of learning analytics in developing countries – its potential benefits and risks for learners, educators, and educations systems, as well as the ways to move forward that are rigorous, context-appropriate, ethical, and accountable.This work was created with financial support from the UK Government’s Department for International Development and the International Development Research Centre, Canada. The views expressed in this work are those of the authors and do not necessarily represent those of the UK Government’s Department for International Development; the International Development Research Centre, Canada or its Board of Governors; the Foundation for Information Technology Education and Development; or the editors
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