学习不良儿童的元认知偏差及矫正

Metacognitive illusions or metacognitive bias is a concept that is a homologous with metacognitve monitor accuracy. In the dissertation, metacognitive illusions mainly refers to the absolute differences between judgment of learning (JOL) and recall because individuals are misguided by some invalid cues or information. JOL is one kind of metacognitive judgments, which is the prediction about the future performance of learned materials. Its mechanism and accuracy are the key issues in the study of JOL. Cue-utilization framework proposed by Koriat (1997) summarized the previous findings and provided a significant advance in understanding how people make JOL. However, the model is not able to explain individual differences in the accuracy of JOL. From the perspective of people’s cognitive bound, our study use posterior associative word pairs easy to produce metacognitive bias to explore the deeper psychological mechanism of metacontive bias. Moreover, we plan to investigate the cause to result in higher metacognitive illusions of children with LD. Based on these, the study tries to look for the method of mending metacognitive illusions. At the same time, we will summarize the findings of this study and previous literatures, and propose a revesied theory for explaining children’s with LD cue selection and utilization according to Koriat’s cue-utilization model. The results of the present study indicated that: (1) Children showed stable metacognitive illusions for the weak associative and posterior associative word pairs, it was not true for strong associative word pairs. It was higher metacognitive illusions for children with LD than normal children. And it was significant grade differences for metacognitive illusions. A priori associative strength exerted a weaker effect on JOL than it did on recall. (2) Children with LD mainly utilized retrieval fluency to make JOL across immediate and delay conditions. However, for normal children, it showed some distinction between encoding fluency and retrieval fluency as potential cues for JOL across immediate and delay conditions. Obviously, children with LD lacked certain flexibility for cue selection and utilization. (3)When word pairs were new list, it showed higher metacognitve transfer effects for analytic inferential group than heuristic inferential group for normal children in the second block. And metacognitive relative accuracy got increased for both children with and without LD across the experimental conditions. However, it was significantly improved only for normal children in analytic inferential group.

Prediction of GC retention values under various column temperature conditions from temperature programmed data

A numerical approach has been developed for the correlation of retention limes (total retention lime) with temperature in gas chromatography, which allows the calculation of retention parameters including retention index from data acquired under two or more different temperature program conditions. By using this procedure the optimization of temperature condition can be further achieved, especially when a temperature-programmed run is the most suitable mode in the preliminary development of an analytical method for the analysis of an unknown sample.

Prediction of soil organic partition coefficients by a soil leaching column chromatographic method

The soil organic partition coefficient (K-oc) is one of the most important parameters to depict the transfer and fate of a chemical in the soil-water system. Predicting K-oc by using a chromatographic technique has been developing into a convenient and low-cost method. In this paper, a soil leaching column chromatograpy (SLCC) method employing the soil column packed with reference soil GSE 17201 (obtained from Bayer Landwirtschaftszentrum, Monheim, Germany) and methanol-water eluents was developed to predict the K-oc of hydrophobic organic chemicals (HOCs), over a log K-oc range of 4.8 orders of magnitude, from their capacity factors. The capacity factor with water as an eluent (k(w)') could be obtained by linearly extrapolating capacity factors in methanol-water eluents (k') with various volume fractions of methanol (phi). The important effects of solute activity coefficients in water on k(w)' and K-oc were illustrated. Hence, the correlation between log K-oc and log k(w)' (and log k') exists in the soil. The correlation coefficient (r) of the log K-oc vs. log k(w)' correlation for 58 apolar and polar compounds could reach 0.987, while the correlation coefficients of the log K-oc-log k' correlations were no less than 0.968, with phi ranging from 0 to 0.50. The smaller the phi, the higher the r. Therefore, it is recommended that the eluent of smaller phi, such as water, be used for accurately estimating K-oc. Correspondingly, the r value of the log K-oc-log k(w)' correlation on a reversed-phase Hypersil ODS (Thermo Hypersil, Kleinostheim, Germany) column was less than 0.940 for the same solutes. The SLCC method could provide a more reliable route to predict K-oc indirectly from a correlation with k(w)' than the reversed-phase liquid chromatographic (RPLC) one.

Resolution prediction and optimization of temperature programme in comprehensive two-dimensional gas chromatography

A model is developed for predicting the resolution of interested component pair and calculating the optimum temperature programming condition in the comprehensive two-dimensional gas chromatography (GC x GC). Based on at least three isothermal runs, retention times and the peak widths at half-height on both dimensions are predicted for any kind of linear temperature-programmed run on the first dimension and isothermal runs on the second dimension. The calculation of the optimum temperature programming condition is based on the prediction of the resolution of "difficult-to-separate components" in a given mixture. The resolution of all the neighboring peaks on the first dimension is obtained by the predicted retention time and peak width on the first dimension, the resolution on the second dimension is calculated only for the adjacent components with un-enough resolution on the first dimension and eluted within a same modulation period on the second dimension. The optimum temperature programming condition is acquired when the resolutions of all components of interest by GC x GC separation meet the analytical requirement and the analysis time is the shortest. The validity of the model has been proven by using it to predict and optimize GC x GC temperature programming condition of an alkylpyridine mixture. (c) 2005 Elsevier B.V. All rights reserved.