Diálogos Adaptativos Para a Aprendizagem de Radiologia
Resumo
Este artigo descreve como princípios cognitivos e computacionais podem ser aplicados na criação de modelos de interface e de aprendizes para o treinamento de longo prazo em Radiologia médica. Um estudo empírico apresenta os conceitos chave que ocorrem em diálogos tutoriais apenas entre humanos nos diferentes estágios de aquisição da perícia. Os resultados desse estudo são detalhados e associados ao projeto do ambiente RUI-2, uma ferramenta de autoria e sua “shell” de Sistema Tutor Inteligente para múltiplos domínios de Radiologia médica. Uma breve discussão oferece uma visão crítica do método seguida de metas futuras de pesquisa.Referências
A. Collins, P. Neville, K. Bielaczyc (2000). The role of different media in designing learning environments. International Journal of Artificial Intelligence in Education, 11(1):144-162.
M. Sharples, N. Jeffery, B. du Boulay, B. Teather, D. Teather, and G. du Boulay. (2000). Structured computer-based training in the interpretation of neuroradiological images. International Journal of Medical Informatics, 60(3):263. 280.
S. Ainsworth, (2006) DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16 (3), 183-198.
R. Power, D. Scott (1998). Multilingual authoring using feedback texts. In Proceedings of the 17th International Conference on Computational Linguistics (COLING/ACL-98), pag. 1053-1059.
D. Cury, N. Omar, A. Direne (1998). Modelos baseados em estereótipos e oráculos para a aprendizagem de conceitos visuais. Revista Brasileira de Informática na Educação, v. 2, pp 43-53, 1998.
K. Luchini, C. Quintana, and E. Soloway (2004). Design guidelines for learner-centered handheld tools. In Proc. of the ACM Conference on Human Factors in Computing Systems (CHI2004), pp. 24.29.
S. Bull and J. Kay (2007). Student models that invite the learner in: The SMILI open learner modelling framework. International. Journal of Artificial Intelligence in Education, 17(2):89-120.
S. Lam, J. Pan, D. Sleeman, and W. Vasconcelos (2006). A finegrained approach to resolving unsatisfiable ontologies. In Proc. of the IEEE/WIC/ACM International Conference on Web Intelligence (WI-2006).
I. Arroyo, T. Murray, B. Woolf, and C. Beal (2004). Inferring hidden learning variables from student help seeking behavior. In Proc. of the 7th International Conference on Intelligent Tutoring Systems (ITS2004), pages 782.784. Springer.
P. Gott and A. Lesgold (2000). Competence in the workplace: How cognitive performance models and situated instruction can accelerate skill acquisition. In R. Glaser, editor, Advances ininstructional Psychology. Lawrence Erlbaum.
A. Direne, D. Scott (2001). Identifying the component features of expertise in domains of complex visual recognition. Relatório Técnico ITRI-01-23, Information Technology Research Institute, University of Brighton - Inglaterra.
M. Estep, editor (2006). Self-Organizing Natural Intelligence: Issues of Knowing, Meaning, and Complexity. Springer, New York.
M. Sharples, N. Jeffery, B. du Boulay, B. Teather, D. Teather, and G. du Boulay. (2000). Structured computer-based training in the interpretation of neuroradiological images. International Journal of Medical Informatics, 60(3):263. 280.
S. Ainsworth, (2006) DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16 (3), 183-198.
R. Power, D. Scott (1998). Multilingual authoring using feedback texts. In Proceedings of the 17th International Conference on Computational Linguistics (COLING/ACL-98), pag. 1053-1059.
D. Cury, N. Omar, A. Direne (1998). Modelos baseados em estereótipos e oráculos para a aprendizagem de conceitos visuais. Revista Brasileira de Informática na Educação, v. 2, pp 43-53, 1998.
K. Luchini, C. Quintana, and E. Soloway (2004). Design guidelines for learner-centered handheld tools. In Proc. of the ACM Conference on Human Factors in Computing Systems (CHI2004), pp. 24.29.
S. Bull and J. Kay (2007). Student models that invite the learner in: The SMILI open learner modelling framework. International. Journal of Artificial Intelligence in Education, 17(2):89-120.
S. Lam, J. Pan, D. Sleeman, and W. Vasconcelos (2006). A finegrained approach to resolving unsatisfiable ontologies. In Proc. of the IEEE/WIC/ACM International Conference on Web Intelligence (WI-2006).
I. Arroyo, T. Murray, B. Woolf, and C. Beal (2004). Inferring hidden learning variables from student help seeking behavior. In Proc. of the 7th International Conference on Intelligent Tutoring Systems (ITS2004), pages 782.784. Springer.
P. Gott and A. Lesgold (2000). Competence in the workplace: How cognitive performance models and situated instruction can accelerate skill acquisition. In R. Glaser, editor, Advances ininstructional Psychology. Lawrence Erlbaum.
A. Direne, D. Scott (2001). Identifying the component features of expertise in domains of complex visual recognition. Relatório Técnico ITRI-01-23, Information Technology Research Institute, University of Brighton - Inglaterra.
M. Estep, editor (2006). Self-Organizing Natural Intelligence: Issues of Knowing, Meaning, and Complexity. Springer, New York.
Publicado
12/07/2008
Como Citar
DIRENE, Alexandre; SUNYE, Marcos; CASTILHO, Marcos; SILVA, Fabiano; BONA, Luis; GARCÍA, Laura; SCOTT, Donia.
Diálogos Adaptativos Para a Aprendizagem de Radiologia. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 8. , 2008, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2008
.
p. 81-90.
ISSN 2763-8952.
