平面几何问题解决过程中的元认知实验研究

This study was based on the cognitive-metacognitive model of mathematical problem solving established by Lester & Garofalo(1985). The method of protocal analysis was used and 19 excellent students(9 male and 10 female) & 19 learning-disabled students(11 male and 8 female) in middle school(grade 3)were tested and interviewed during they solved plane geometry problems. The main results showed as follows: (1) There was a significant difference between excellent students and learning-disabled students on time-assignment when they solved plane geometry problems. Excellent students used more time on phase organization and less time on phase execution. There was no difference on phases orientation and verification. (2) Excellent students showed higher metacognitive level than learning-disabled students. The deference existed in phases orientation and organization. Excellent students reported more metacognitive sentences in phases orientation and organization than learning-disabled students. They had more self-awareness and goal-awareness. They had more "knowledge about what they know" and "knowledge about what they should use". They designed more globle goal and subgoals and made more self-evaluation. (3) Both the excellent students' and learning-disabled students' self-checking level should be improved.

Reversible Nanopatterning on Self-Assembled Monolayers on Gold

The reversible fabrication of positive and negative nanopatterns on 1-hexadecanethiol (HDT) self-assembled monolayers (SAMs) on Au(111) was realized by bias-assisted atomic force microscopy (AFM) nanolithography using an ethanol-ink tip. The formation of positive and negative nanopatterns via the bias-assisted nanolithography depends solely on the polarity of the applied bias, and their writing speeds can reach 800,um/s and go beyond 1000 mu m/s, respectively. The composition of the positive nanopatterns is gold oxide and the nanometer-scale gold oxide can be reduced by ethanol to gold, as proved by X-ray photoelectron spectroscopy (XPS) analysis, forming the negative nanopatterns which can be refilled with HDT to recover the SAMs.