2 resultados para Learning strategies

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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In the field of misconceptions research, previous research was focused mainly on the effect of naive concepts on the learning of scientific concept. In this study, from the viewpoint of declarative and procedural knowledge, conceptual errors on Newtonian mechanics were studied comparatively between high-performance and low-performance students. Furthermore, the effects of self-explain learning strategies and reflective learning on the change of subjects' conceptual errors were explored. The result of experiments indicated: 1. There was significant difference in the number of conceptual errors of declarative and procedural knowledge between high-performance students and low-performance students. And Low-performance students made more conceptual errors of procedural knowledge than that of declarative knowledge. For high-performance students, there was no distinct difference between these two kinds of errors. 2. In the distribution of conceptual errors, most errors of declarative knowledge were mainly focused on the understanding of concepts of friction and acceleration. The errors of procedure knowledge most errors concentrated on the judgment of vector direction and the conceptual understanding. 3. Compared with high-performance students, the representation of conceptual declarative knowledge of low-performance students is less complex, more concrete and context bound. 4. The comparative analysis of problem-solving strategies showed: high-performance students preferred to apply analytic strategy, solving problems based on physical concepts and principles; low-performance students preferred to use context strategy, solving problem according to the literal meaning of problems, subjective and groundless presumption and wrong concepts and principles. 5. Self-explain strategies can help students correct their conceptual errors effectively. Reflective learning could help students to correct the concept errors in some degree, but the distinct effect was not observed.

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The largest damming project to date, the Three Gorges Dam has been built along the Yangtze River (China), the most species-rich river in the Palearctic region. Among 162 species of fish inhabiting the main channel of the upper Yangtze, 44 are endemic and are therefore under serious threat of global extinction from the dam. Accordingly, it is urgently necessary to develop strategies to minimize the impacts of the drastic environmental changes associated with the dam. We sought to identify potential reserves for the endemic species among the 17 tributaries in the upper Yangtze, based on presence/absence data for the 44 endemic species. Potential reserves for the endemic species were identified by characterizing the distribution patterns of endemic species with an adaptive learning algorithm called a "self-organizing map" (SOM). Using this method, we also predicted occurrence probabilities of species in potential reserves based on the distribution patterns of communities. Considering both SOM model results and actual knowledge of the biology of the considered species, our results suggested that 24 species may survive in the tributaries, 14 have an uncertain future, and 6 have a high probability of becoming extinct after dam filling.