ResumenEn los últimos años, el fomento de la empleabilidad y la adquisición de competencias se ha convertido en una de las prioridades de las universidades en el marco del Espacio Europeo de Educación Superior. Esto ha supuesto un nuevo impulso para afrontar las crecientes dificultades relacionadas con la inserción laboral de los titulados y los desajustes entre la formación recibida y los requisitos de los puestos de trabajo. En el nuevo paradigma educativo, las competencias se han convertido en la referencia a partir de la cual se organiza, planifica y evalúa el aprendizaje, y las agencias de calidad encargadas de evaluar los planes de estudio han introducido nuevos criterios ligados a la empleabilidad y la inserción laboral. Sin embargo, en España la información sobre muchos de estos temas es insuficiente, especialmente en cuanto a las competencias que se necesitan a lo largo de la vida laboral y la aportación de la universidad en su adquisición, los factores que determinan el acceso al empleo y la estabilidad laboral, la satisfacción con el trabajo y con la formación recibida, la idoneidad de las metodologías educativas utilizadas, o los desajustes entre la educación y el empleo. Con esta finalidad, en el año 2012 se creó el Observatorio de Empleabilidad y Empleo Universitarios. El objetivo de este artículo es la presentación de los resultados de esta iniciativa sistémica de política universitaria encaminada al seguimiento y a la medición de la empleabilidad y el empleo de los universitarios en España. AbstractIn the last years, the promotion of employability and the achievement of competences have become a priority for universities within the European Higher Education Area. For universities, this has entailed a renovated concern for their graduates' integration into the labour market and the mismatches between the competences achieved during academic education and the employers' requirements. In the new educational paradigm, competences have become the reference from which the education of university students is organized, planned and evaluated, so the Quality Agencies have introduced new criteria related to employability in academic programs assessment. However, in Spain there is not enough information on these issues, especially regarding the competences that students will need in their career path and the role of higher education in its acquisition, the factors that influence to obtain a job and job stability, job and education satisfaction, the suitability of the educational methodologies, or the mismatches between education and labour market. With this aim, in 2012, the Observatory for Employability and University Employment was created. The objective of this article is to present the results of this systemic university policy initiative focused on monitoring and measuring the employability and employment of university graduates in Spain.Empleabilidad de los titulados universitarios en España.Proyecto OEEU Employability of University Graduates in Spain. OEEU Project
This paper describes the technological approach for the development of the system that supports the Observatory for University Employability and Employment developed under the leadership of the UNESCO Chair in University Management and Policy. This observatory, nowadays, collects data from more than 50 Spanish universities and more than 134,000 graduate students in order to measure diverse factors linked to their professional career development and their employability. The paper explains many problems that this kind of project related to Academic Analytics and Institutional Intelligence needs to face and solve, as well as it explains some of the most important concerns and considerations that should be taken in the context of deploying a project like the described in a national scope. Also, the paper shows an introduction of how was planned the data strategy to gather the information, how was built the collector system, and how it will exploit the information from the perspective of Academic Analytics in order to provide great insights about the factors in graduate's employability in order to use it to make decisions and feedback the Institutional Intelligence processes.
This paper presents an original study with the aim of propose and test a machine learning approach to research about employability and employment. To understand how the graduates get employed, researchers propose to build predictive models using machine learning algorithms, extracting after that the most relevant factors that describe the model and employing further analysis techniques like clustering to get deeper insights. To test the proposal, is presented a case study that involves data from the Spanish Observatory for Employability and Employment (OEEU). Using data from this project (information about 3000 students), has been built predictive models that define how these students get a job after finalizing their degrees. The results obtained in this case study are very promising, and encourage authors to refine the process and validate it in further research.
This chapter outlines the technological evolution experimented by the Observatory for University Employability and Employment's information system to become a data-driven technological ecosystem. This observatory collects data from more than 50 Spanish universities and their graduate students (bachelor's degree, master's degree) with the goal of measuring the factors that lead to students' employability and employment. The goals pursued by the observatory need a strong technological support to gather, process, and disseminate the related data. The system that supports these tasks has evolved from a standard (traditional) information system to a data-driven ecosystem, which provides remarkable benefits covering the observatory's requirements. The benefits, the foundations, and the way the data-driven ecosystem is built will be described throughout the chapter, as well as how the information obtained is exploited in order to provide insights about the employment and employability variables.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.