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Robotics competitions for K-12 students are popular, but are students really learning and improving their STEM scores through robotics competitions? If not, why not? If they are, how much more effective is learning through competitions than traditional classes? Is there room for improvement? What is the best robotics competition model to maximize students STEM learning? One robotics competition designed to promote the use of math and science is Robofest. Robofest is an autonomous robotics competition with many unique features for STEM education. An example is that students need to solve unknown problems on the day of the competition. The Robofest competition requires use of mathematics and sensors which discourages dead reckoning. Results from 4th-12th graders who completed a STEM assessment before and after the 2010-2011 Robofest competition found students in the Robofest group showed significant improvement in math scores after the competition, compared to students in a control group. These results suggest robotics competitions modeled after Robofest have the potential to maximize STEM learning.

Since learning English is very popular in non-English speaking countries, developing modern assisted-learning tools that support effective English learning is a critical issue in the English-language education field. Learning English involves memorization and practice of a large number of vocabulary words and numerous grammatical structures. Vocabulary learning is a principal issue for English learning because vocabulary comprises the basic building blocks of English sentences. Therefore, many studies have attempted to improve the efficiency and performance when learning English vocabulary. With the accelerated growth in wireless and mobile technologies, mobile learning using mobile devices such as PDAs, tablet PCs, and cell phones has gradually become considered effective because it inherits all the advantages of e-learning and overcomes limitations of learning time and space that limit web-based learning systems. Therefore, this study presents a personalized mobile English vocabulary learning system based on Item Response Theory and learning memory cycle, which recommends appropriate English vocabulary for learning according to individual learner vocabulary ability and memory cycle. The proposed system has been successfully implemented on personal digital assistant (PDA) for personalized English vocabulary learning. The experimental results indicated that the proposed system could obviously promote the learning performances and interests of learners due to effective and flexible learning mode for English vocabulary learning.

The hydrogenation and dehydrogenation of a thin film of Mg with a Pd cap layer was measured using neutron reflectometry. Upon hydrogenation, (at 373 K and 0.2 MPa H2), the Mg film swelled in the surface normal direction by an amount roughly equal to the difference in volume between MgH2 and Mg. After dehydrogenation (at 343-423 K), the Mg film returned to a composition of Mg but retained the swelled thickness by incorporating voids. The presence of the voids is confirmed by SEM micrographs. The voids may explain some of the changes in absorption kinetics after full cycling of Mg films. [ABSTRACT FROM AUTHOR]

Discusses results of an investigation of magnetic flux-drag forces for high-critical temperature superconductors. Experimental setup; Measurement of the flux-drag torque acting on a yttrium-barium-copper-oxide superconducting sample due to the off-axis circular motion of a permanent magnet; Description of the hysteretic curves of the flux-drag torque.