In recent years, with the development of electronic media, e-learning has begun to replace traditional teaching and learning with Internet service. With the availability of newly developed technology, opportunities have risen for the teacher of e-learning to using students¡¦ learning logs that recorded via Web site to understanding the learning state of students. This research will address an analytical mechanism that integrated multidimensional logs to let teachers observe students all learning behaviors and learning status immediately, and used decision tree analysis to detect when and what students may have a learning bottleneck. Finally, teachers can use those results to give the right student with the right remedial instruction at the right time. Summary, we have four conclusions: (1) the decision rules are different from course to course, for example instruction method and assessment method, assignment is a basis to assess student¡¦s learning effectiveness, as well those attributes cooperate with learning effectiveness are related to student¡¦s learning behaviors. (2) To accumulate those learning behavior attributes with the time point actually detect learners probably learning effectiveness early. The variation of effectiveness with different time interval is not clearly, but all time intervals can detect learning effectiveness early. (3) To detect students¡¦ learning effectiveness with different grade level classifications, every grade level classifications can describe decision rules very well, but not to detect all students¡¦ learning effectiveness. (4) Although to detect high-grade students¡¦ learning effectiveness are very difficult, but we can detect lower-grade students¡¦ learning effectiveness. Finally, this research can really observe student¡¦s leaning states immediately, and early detect students¡¦ learning effectiveness. Therefore, teachers can make decisions to manage learning activities to promote learning effect.

Submitted by Claudinei Pracidelli (cpracide@ipen.br) on 2016-02-03T11:55:07Z No. of bitstreams: 0 / Made available in DSpace on 2016-02-03T11:55:07Z (GMT). No. of bitstreams: 0 / Dissertação (Mestrado em Tecnologia Nuclear) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

Submitted by Claudinei Pracidelli (cpracide@ipen.br) on 2016-02-03T11:55:07Z No. of bitstreams: 0 / Made available in DSpace on 2016-02-03T11:55:07Z (GMT). No. of bitstreams: 0 / O trabalho busca o desenvolvimento de um método experimental implementado em um software Web voltado à tomada de decisão, abordando mais especificadamente os processos de levantamento de ideias e geração de alternativas. Referências teóricas foram utilizadas para subsidiar os elementos, processos e tecnologias do software frente à áreas de tomada de decisão e sistemas colaborativos. As principais ferramentas disponíveis foram analisadas sob o contexto de tecnologias abertas, tendo algumas características de resolução de problemas observadas. A proposta combina elementos do brainstorming em seu formato eletrônico e do método de apresentação de dados da tabela de estratégias, com referência nas funcionalidades de sistemas amplamente utilizados e que operam sobre a priorização das informações por pequenos grupos de usuários. Fundamentações teóricas foram desenvolvidas e funcionalidades chave destes sistemas voltados à resolução de problemas foram analisadas. Para fins de demonstração, um caso prático foi realizado no Instituto de Pesquisas Energéticas e Nucleares, com ganhos e limitações encontradas no processo do software e da prática empregada. com a finalidade de apresentar os ganhos e limitações encontradas com o uso da ferramenta. / Dissertação (Mestrado em Tecnologia Nuclear) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

The objective of the thesis is the model-based analysis of spatial patterns of decomposition properties on the forested slopes of the montane level (ca. 1200-2200 m a.s.l.) in a study area in the Italian Alps (Val di Sole / Val di Rabbi, Autonomous Province of Trento). The analysis includes humus forms and enchytraeid assemblages as well as pH values, activities of extracellular enzymes and C/N ratios of the topsoil. The first aim is to develop, test and apply data-based techniques for spatial modelling of soil ecological parameters. This methodological approach is based on the concept of digital soil mapping. The second aim is to reveal the relationships between humus forms, soil organisms and soil microbiological parameters in the study area. The third aim is to analyze if the spatial patterns of indicators of decomposition differ between the landscape scale and the slope scale. At the landscape scale, sample data from six sites are used, covering three elevation levels at both north- and south-facing slopes. A knowledge-based approach that combines a decision tree analysis with the construction of fuzzy membership functions is introduced for spatial modelling. According to the sampling design, elevation and slope exposure are the explanatory variables. The investigations at the slope scale refer to one north-facing and one south-facing slope, with 30 sites occurring on each slope. These sites have been derived using conditioned Latin Hypercube Sampling, and thus reasonably represent the environmental conditions within the study area. Predictive maps have been produced in a purely data-based approach with random forests. At both scales, the models indicate a high variability of spatial decomposition patterns depending on the elevation and the slope exposure. In general, sites at high elevation on north-facing slopes almost exclusively exhibit the humus forms Moder and Mor. Sites on south-facing slopes and at low elevation exhibit also Mull and Amphimull. The predictions of those enchytraeid species characterized as Mull and Moder indicators match the occurrence of the corresponding humus forms well. Furthermore, referencing the mineral topsoil, the predictive models show increasing pH values, an increasing leucine-aminopeptidase activity, an increasing ratio alkaline/acid phosphomonoesterase activity and a decreasing C/N ratio from north-facing to south-facing slopes and from high to low elevation. The predicted spatial patterns of indicators of decomposition are basically similar at both scales. However, the patterns are predicted in more detail at the slope scale because of a larger data basis and a higher spatial precision of the environmental covariates. These factors enable the observation of additional correlations between the spatial patterns of indicators of decomposition and environmental influences, for example slope angle and curvature. Both the corresponding results and broad model evaluations have shown that the applied methods are generally suitable for modelling spatial patterns of indicators of decomposition in a heterogeneous high mountain environment. The overall results suggest that the humus form can be used as indicator of organic matter decomposition processes in the investigated high mountain area.