18 resultados para Collaborative Process Modelling
Resumo:
The cataloging process, is responsible for building systems consisting of sets of interconnected elements and combined forms of representation, creating tools to facilitate the flow of information in various informational environments. It presents structures that offer favorable conditions for access to formal codes of symbolic representation and to the channels of information transfer, performing with competence the decoding and encoding of codes and rules used to represent knowledge and to describe information, documents and resources. The objective of this paper is to present the challenge of transforming operational data into consistent information, the role of the forms of representation and the mental constructions for defining the memory markers of users of catalogs. It shows as results the memory markers indicated by three categories of users for the description of a book like resource and points to the need of collaborative and cooperative work in cataloging and to the need of catalog modelling focused on the user.
Resumo:
This article presents some of the results of a qualitative research project about the influences of the pedagogic strategies used by a mediator (graduate student in applied linguistics) in the supervision process of a Teletandem partner (undergraduate student in languages) on her pedagogical practice. It was done within the project Teletandem Brazil: foreign language for all. Based on the reflective teaching paradigm and collaborative language learning, with special emphasis on tandem learning, we analyzed the contributions of the collaborative relationship established between the graduate student and the student-teacher in her first teaching experience. The results bring about implications for the field of language teacher education in a perspective of education within practice, evidencing the experience of collaborative learning in teletandem as an opportunity for reflective teacher education of pre-service teachers.
Resumo:
This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), times of infection, and harvest (24, 48, 72 hours) and the monitored output parameter was viral production. A multilevel factorial experimental design was performed for the study of this system. Fractions of this experimental approach (18, 24, 30, 36 and 42 runs), defined according uniform designs, were used as alternative for modelling through artificial neural network and thereafter an output variable optimization was carried out by means of genetic algorithm methodology. Model prediction capacities for all uniform design approaches under study were better than that found for classical factorial design approach. It was demonstrated that uniform design in combination with artificial neural network could be an efficient experimental approach for modelling complex bioprocess like viral production. For the present study case, 67% of experimental resources were saved when compared to a classical factorial design approach. In the near future, this strategy could replace the established factorial designs used in the bioprocess development activities performed within biopharmaceutical organizations because of the improvements gained in the economics of experimentation that do not sacrifice the quality of decisions.