The Effect of Teacher Education Level, Teaching Experience, And Teaching Behaviors On Student Science Achievement

Previous literature leaves us unanswered questions about whether teaching behaviors mediate the relationship between teacher education level and experience with student science achievement. This study examined this question with 655 students from sixth to eighth grade and their 12 science teachers. Student science achievements were measured at the beginning and end of 2006-2007 school year. Given the cluster sampling of students nested in classrooms, which are nested in teachers, a two-level multilevel model was employed to disentangle the effects from teacher-level and student-level factors. Several findings were discovered in this study. Science teachers possessing of advanced degrees in science or education significantly and positively influenced student science achievement. However, years of teaching experience in science did not directly influence student science achievement. A significant interaction was detected between teachers possessing an advanced degree in science or education and years of teaching science, which was inversely associated to student science achievement. Better teaching behaviors were also positively related to student achievement in science directly, as well as mediated the relationship between student science achievement and both teacher education and experience. Additionally, when examined separately, each teaching behavior variable (teacher engagement, classroom management, and teaching strategies) served as a significant intermediary between both teacher education and experience and student science achievement. The findings of this study are intended to provide insights into the importance of hiring and developing qualified teachers who are better able to help students achieve in science, as well as to direct the emphases of ongoing teacher inservice training

Direct Imaging of Kinetic Pathways of Atomic Diffusion in Monolayer Molybdenum Disulfide

Direct observation of atomic migration both on and below surfaces is a long-standing but important challenge in materials science as diffusion is one of the most elementary processes essential to many vital material behaviors. Probing the kinetic pathways, including metastable or even transition states involved down to atomic scale, holds the key to the underlying physical mechanisms. Here, we applied aberration-corrected transmission electron microscopy (TEM) to demonstrate direct atomic-scale imaging and quasi-real-time tracking of diffusion of Mo adatoms and vacancies in monolayer MoS 2, an important two-dimensional transition metal dichalcogenide (TMD) system. Preferred kinetic pathways and the migration potential-energy landscape are determined experimentally and confirmed theoretically. The resulting three-dimensional knowledge of the atomic configuration evolution reveals the different microscopic mechanisms responsible for the contrasting intrinsic diffusion rates for Mo adatoms and vacancies. The new insight will benefit our understanding of material processes such as phase transformation and heterogeneous catalysis

The Role of School Adaptation and Self-Concept in Influencing Chinese High School Students’ Growth in Math Achievement

A longitudinal designed research study was conducted to provide empirical evidence regarding the influences of three dimensions of students’ school adaptation on their math achievement growth over the first year of high school. These dimensions included learning adaptation, stress management, and personal communication. Student math achievement growth was measured using the student growth percentile (SGP) score. Structural equation modeling (SEM) was used to test for the possible mediating role of self-concept behind those three relationships. Based on the model comparison, it was discovered that school adaptation significantly and positively influences student math achievement growth via mediating effects of student academic self-concept, as opposed to showing a direct impact on students. The findings of this study have important implications for educators and parents to aid students in their pursuit of academic success

Incorporating gene co-expression network in identification of cancer prognosis markers

<p>Abstract</p> <p>Background</p> <p>Extensive biomedical studies have shown that clinical and environmental risk factors may not have sufficient predictive power for cancer prognosis. The development of high-throughput profiling technologies makes it possible to survey the whole genome and search for genomic markers with predictive power. Many existing studies assume the interchangeability of gene effects and ignore the coordination among them.</p> <p>Results</p> <p>We adopt the weighted co-expression network to describe the interplay among genes. Although there are several different ways of defining gene networks, the weighted co-expression network may be preferred because of its computational simplicity, satisfactory empirical performance, and because it does not demand additional biological experiments. For cancer prognosis studies with gene expression measurements, we propose a new marker selection method that can properly incorporate the network connectivity of genes. We analyze six prognosis studies on breast cancer and lymphoma. We find that the proposed approach can identify genes that are significantly different from those using alternatives. We search published literature and find that genes identified using the proposed approach are biologically meaningful. In addition, they have better prediction performance and reproducibility than genes identified using alternatives.</p> <p>Conclusions</p> <p>The network contains important information on the functionality of genes. Incorporating the network structure can improve cancer marker identification.</p

Atomistic dynamics of sulfur-deficient high-symmetry grain boundaries in molybdenum disulfide

As a common type of structural defect, grain boundaries (GBs) play an important role in tailoring the physical and chemical properties of bulk crystals and their two-dimensional (2D) counterparts such as graphene and molybdenum disulfide (MoS2). In this study, we explore the atomic structures and dynamics of three kinds of high-symmetry GBs (α, β and γ) in monolayer MoS2. Atomic-resolution transmission electron microscopy (TEM) is used to characterize their formation and evolutionary dynamics, and atomistic simulation based analysis explains the size distribution of α-type GBs observed under TEM and the inter-GB interaction, revealing the stabilization mechanism of GBs by pre-existing sulfur vacancies. The results elucidate the correlation between the observed GB dynamics and the migration of sulfur atoms across GBs via a vacancy-mediated mechanism, offering a new perspective for GB engineering in monolayer MoS2, which may be generalized to other transition metal dichalcogenides