2 resultados para external knowledge
em Universidad de Alicante
Resumo:
The continuous improvement of management and assessment processes for curricular external internships has led a group of university teachers specialised in this area to develop a mixed model of measurement that combines the verification of skill acquisition by those students choosing external internships with the satisfaction of the parties involved in that process. They included academics, educational tutors of companies and organisations and administration and services personnel in the latter category. The experience, developed within University of Alicante, has been carried out in the degrees of Business Administration and Management, Business Studies, Economics, Advertising and Public Relations, Sociology and Social Work, all part of the Faculty of Economics and Business. By designing and managing closed standardised interviews and other research tools, validated outside the centre, a system of continuous improvement and quality assurance has been created, clearly contributing to the gradual increase in the number of students with internships in this Faculty, as well as to the improvement in satisfaction, efficiency and efficacy indicators at a global level. As this experience of educational innovation has shown, the acquisition of curricular knowledge, skills, abilities and competences by the students is directly correlated with the satisfaction of those parties involved in a process that takes the student beyond the physical borders of a university campus. Ensuring the latter is a task made easier by the implementation of a mixed assessment method, combining continuous and final assessment, and characterised by its rigorousness and simple management. This report presents that model, subject in turn to a persistent and continuous control, a model all parties involved in the external internships are taking part of. Its short-term results imply an increase, estimated at 15% for the last course, in the number of students choosing curricular internships and, for the medium and long-term, a major interweaving between the academic world and its social and productive environment, both in the business and institutional areas. The potentiality of this assessment model does not lie only in the quality of its measurement tools, but also in the effects from its use in the various groups and in the actions that are carried out as a result of its implementation and which, without any doubt and as it is shown below, are the real guarantee of a continuous improvement.
Resumo:
Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.