3,358 research outputs found

    Identification of Key Performance Indicators in Project-Based Organisations through the Lean Approach

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    For the time being, companies and organisations are being forced to compete in utterly complex and globalised environments, facing massive natural, economic, and technological challenges on a daily basis. Addressing these challenges would be impossible without a proper approach that helps them identify, measure, understand, and control the performance of their organisations. Lean principles and techniques rise as a solution. This paper justifies and proposes the use of lean principles and techniques to identify key performance indicators (KPIs) in project-based organisations based on their organisational and operational needs. The research focuses mainly on the identification and categorisation of KPIs through a qualitative approach, based on systematic literature review (SLR) of performance indicators, project management, and project success. As a case study, an analysis of relevant information of an R&D and innovation project-based organisation, such as quality manuals, a benchmarking process, internal studies, and surveys regarding what success means for different kinds of stakeholders and for the organisation itself was conducted. As a result, this research is of a high value for project-based organisations, especially those that are not apprised of how to correctly formulate a series of KPIs, or whose path to it is still not clear.Authors are grateful to Basque government group IT IT1337-19 and the Spanish Ministry of Science Mineco REF DPI2016-74845-R and project PID2019-109340RB-I00

    Creating a performance-oriented e-learning environment: A design science approach

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    E-learning is now being used by many organizations as an approach for enhancing the skills of knowledge workers. However, most applications have performed poorly in motivating employee learning, being perceived as less effective due to a lack of alignment of learning with work performance. To help solve this problem, we developed a performance-oriented approach using design science research methods. It uses performance measurement to clarify organizational goals and individual learning needs and links them to e-learning applications. The key concept lies in a Key Performance Indicator model, where organizational mission and vision are translated into a set of targets that drive learning towards a goal of improving work performance. We explored the mechanisms needed to utilize our approach and examined the necessary conceptual framework and implementation details. To demonstrate the effectiveness of the approach, a prototype workplace e-learning system was developed and used to evaluate the effectiveness of our approach. © 2011 Elsevier B.V. All rights reserved.postprin

    Results readiness in social protection and labor operations : technical guidance notes for labor markets task teams

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    Labor allocation to its most efficient use, promoting employment and human capital investment as well as functioning labor markets can contribute to long?term economic growth, poverty reduction and to help workers manage their risks. A labor market policy framework includes both regulations and programs. However, the optimal framework is not standard and universal but varies country by country depending on the level of economic and financial development, culture and other structural characteristics. Labor market projects are equally concentrated in Latin America and the Caribbean and Eastern Europe and Central Asia regions and one is China. Interestingly, the number of projects having'improving labor market'as the primary component has increased over time. All project development objectives in the cohort of projects reviewed focus on promoting higher employment and increasing economic opportunities as the main objective especially via training programs. About half of the projects also seek to reach specific vulnerable groups by improving targeting mechanisms and to improve the quality of social assistance services by reducing the cost of job search through access to enhanced employment services and by improving employability.Safety Nets and Transfers,Labor Markets,Labor Policies,Housing&Human Habitats,Poverty Monitoring&Analysis

    Innovation and social learning in higher education institutions

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    Considering the existing experiences and the concrete needs of the hearing - impaired and visually - impaired groups for accessing HEI programmes, this handboook brings some important innovations: 1. A functional approach, proposing the methods and procedures to be used for developing and delivering ICT based learning offer valid also for these target group (not specially done for them, but designed in such a way that correspond also to their specific needs). This is that will support the target groups in their education and also social inclusion. 2. A subsequent proposal of a kind of “Quality Label”, to establish quality standards and assessment procedures and instruments to be used for evaluating whether Higher Educational Institutions’ offers and training programmes correspond to the ISOLearn standards regarding the accessibility of these groups to their learning offer. 3. Both the Handbook and the “Quality Label” should be tested on a specific qualification which should become a benchmark for the HEI ICT based learning programmes. The concrete experience will demonstrate the benefits for all the stakeholders (e.g. HEI and disadvantaged groups) of promoting social learning approach in HEI.info:eu-repo/semantics/publishedVersio

    Adding value to school leadership and management

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    Lean project management an application in reserch and technological development (RTD) projects

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    219 p.Las herramientas y los principios del Lean Thinking se han propuesto como un posible enfoque paracomplementar la gestión de proyectos al centrarse en la creación de valor, la mejora continua y lareducción de actividades que no añaden valor. La aplicación combinada de estos dos conceptos se conocecomo Lean Project Management. El enfoque de Lean Project Management se aplica para la mejora delrendimiento de los proyectos en una amplia gama de sectores, como la construcción, el desarrollo desoftware e incluso recientemente a proyectos de investigación y desarrollo, aunque se ha encontrado pocaevidencia de su aplicación conjunta. Para la mejora continua y la mejora de la gestión, es crucial definirlos Indicadores Clave de Rendimiento (KPI) de la organización. La gestión de proyectos Lean es un granapoyo para este propósito. El objetivo de esta tesis es investigar la integración del Lean con la gestión deproyectos y su aplicación en organizaciones basadas en proyectos. Esta tesis proporciona una exhaustivarevisión sistemática de la literatura publicada y la correlación con los indicadores clave de rendimiento delos proyectos. Se presenta un modelo de Lean Project Management que enmarca las herramientas deLean combinados con conceptos y prácticas de gestión de proyectos. Se realiza un estudio de caso en unaempresa basada en proyectos de Investigación y DesarrolloTecnológico (IDT) aplicando el modelo degestión de proyectos Lean propuesto para la identificación de los K

    Design of a performance-oriented workplace e-learning system using ontology

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    E-learning is emerging as a popular learning approach utilized by many organizations. Despite the ever increasing practices of e-learning in the workplace, most e-learning applications fail to meet learners' needs or serve organization's quests for success. Significant gaps exist between organizational interests and individual needs when they come to e-learning, which make e-learning applications less goal-effective. To solve this problem, a performance-oriented approach is presented in this study. Key performance indicators (KPIs) are set up to clarify organizational training needs, and help learners establish rational learning objectives. In addition, ontology is used for constructing formal and machine-understandable conceptualization of the performance-oriented learning environment. Using this approach, a KPI-oriented learning ontology and prototype system have been developed and evaluated to demonstrate the effectiveness of the approach. © 2010 Elsevier Ltd. All rights reserved.postprin

    A framework for strategic planning of data analytics in the educational sector

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    The field of big data and data analysis is not a new one. Big data systems have been investigated with respect to the volume of the data and how it is stored, the data velocity and how it is subject to change, variety of data to be analysed and data veracity referring to integrity and quality. Higher Education Institutions (HEIs) have a significant range of data sources across their operations and increasingly invest in collecting, analysing and reporting on their data in order to improve their efficiency. Data analytics and Business Intelligence (BI) are two terms that are increasingly popular over the past few years in the relevant literature with emphasis on their impact in the education sector. There is a significant volume of literature discussing the benefits of data analytics in higher education and even more papers discussing specific case studies of institutions resorting on BI by deploying various data analytics practices. Nevertheless, there is a lack of an integrated framework that supports HEIs in using learning analytics both at strategic and operational level. This research study was driven by the need to offer a point of reference for universities wishing to make good use of the plethora of data they can access. Increasingly institutions need to become ‘smart universities’ by supporting their decisions with findings from the analysis of their operations. The Business Intelligence strategies of many universities seems to focus mostly on identifying how to collect data but fail to address the most important issue that is how to analyse the data, what to do with the findings and how to create the means for a scalable use of learning analytics at institutional level. The scope of this research is to investigate the different factors that affect the successful deployment of data analytics in educational contexts focusing both on strategic and operational aspects of academia. The research study attempts to identify those elements necessary for introducing data analytics practices across an institution. The main contribution of the research is a framework that models the data collection, analysis and visualisation in higher education. The specific contribution to the field comes in the form of generic guidelines for strategic planning of HEI data analytics projects, combined with specific guidelines for staff involved in the deployment of data analytics to support certain institutional operations. The research is based on a mixed method approach that combines grounded theory in the form of extensive literature review, state-of-the-art investigation and case study analysis, as well as a combination of qualitative and quantitative data collection. The study commences with an extensive literature review that identifies the key factors affecting the use of learning analytics. Then the research collected more information from an analysis of a wide range of case studies showing how learning analytics are used across HEIs. The primary data collection concluded with a series of focus groups and interviews assessing the role of learning analytics in universities. Next, the research focused on a synthesis of guidelines for using learning analytics both at strategic and operational levels, leading to the production of generic and specific guidelines intended for different university stakeholders. The proposed framework was revised twice to create an integrated point of reference for HEIs that offers support across institutions in scalable and applicable way that can accommodate the varying needs met at different HEIs. The proposed framework was evaluated by the same participants in the earlier focus groups and interviews, providing a qualitative approach in evaluating the contributions made during this research study. The research resulted in the creation of an integrated framework that offers HEIs a reference for setting up a learning analytics strategy, adapting institutional policies and revising operations across faculties and departments. The proposed C.A.V. framework consists of three phases including Collect, Analysis and Visualisation. The framework determines the key features of data sources and resulting dashboards but also a list of functions for the data collection, analysis and visualisation stages. At strategic level, the C.A.V. framework enables institutions to assess their learning analytics maturity, determine the learning analytics stages that they are involved in, identify the different learning analytics themes and use a checklist as a reference point for their learning analytics deployment. Finally, the framework ensures that institutional operations can become more effective by determining how learning analytics provide added value across different operations, while assessing the impact of learning analytics on stakeholders. The framework also supports the adoption of learning analytics processes, the planning of dashboard contents and identifying factors affecting the implementation of learning analytics

    Systems Appraisal Feedback Report (2013)

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    This document includes the feedback report from the Higher Learning Commission on the Systems Portfolio submitted in 11/2002
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