Supporting interest in a study domain: A longitudinal test of the interplay between interest,utility-value,and competence beliefs

The current study used a longitudinal design to model initial interest and utility-value as antecedents of developing interest and course proficiency. Using measures from four time points across one academic year and competency assessed at the beginning of the previous year, we examined direct and mediated contributions of utility-value, self-efficacy, and self-concept for the development of domain interest. Japanese tertiary students (n = 614; Female = 129) undertaking a compulsory year-long study of English as a foreign language participated. Students reported motivation (interest, utility-value and competence beliefs of self-efficacy and self-concept) for studying English as a foreign language. In addition, the design allowed detection of reciprocal effects: the forward effect of interest on competence beliefs and in turn the forward effects of competence beliefs on interest. Initial domain interest indicated direct and/or mediated effects for all constructs, while self-efficacy indicated a reciprocal relationship with domain interest. Profile analyses (LPA) identified 3 motivation profiles that were stable across two semesters. Testing a mover-stayer model (LPTA) indicated some movement between the low and medium intensity profiles of motivation.     

The mediating role of workplace social support on the relationship between trait emotional intelligence and teacher burnout

This study investigated the mediating effect of workplace social support on the relationship between trait emotional intelligence and teacher burnout among 307 Chinese middle school teachers. Structural equation modelling revealed a satisfactory fit between the data and our theoretical model. Workplace social support partially mediated the relationship between trait emotional intelligence and teacher burnout. Neither gender nor age moderated the relationship between trait emotional intelligence and teacher burnout. Emotional intelligence and workplace social support can protect teachers from teacher burnout. Thus, providing effective emotional intelligence training and creating supportive workplace conditions requires increased attention from education administrators.     

砂土颗粒SEM图像分析方法的研究

提取砂土颗粒SEM图像的细观特性参数对砂土颗粒的细观研究具有极其重要的意义。在提取砂土颗粒的细观特性参数时遇到了图像质量不高,粘连颗粒比较严重等问题,影响了特征参数的提取。针对这个问题,对砂土颗粒SEM图像的特征进行了分析,借助开运算、中值滤波、直方图均衡化等方法,对图像进行处理,优化了图像质量。使用Otsu法二值化,对处理后的砂土颗粒图像应用形态学处理,改进的分水岭分割算法等,分割粘连的砂土颗粒。最后提取了砂土颗粒的数目、占空比、质心等参数,为岩土的组构张量描述提供了数据支撑。     

Drawing Conclusions from Cross-Lagged Relationships: Re-Considering the Role of the Time-Interval

The cross-lagged panel model (CLPM), a discrete-time (DT) SEM model, is frequently used to gather evidence for (reciprocal) Granger-causal relationships when lacking an experimental design. However, it is well known that CLPMs can lead to different parameter estimates depending on the time-interval of observation. Consequently, this can lead to researchers drawing conflicting conclusions regarding the sign and/or dominance of relationships. Multiple authors have suggested the use of continuous-time models to address this issue.

In this article, we demonstrate the exact circumstances under which such conflicting conclusions occur. Specifically, we show that such conflicts are only avoided in general in the case of bivariate, stable, nonoscillating, first-order systems, when comparing models with uniform time-intervals between observations. In addition, we provide a range of tools, proofs, and guidelines regarding the comparison of discrete- and continuous-time parameter estimates.     

基于农户满意度的农地转出绩效影响因素分析——以武汉、鄂州两地典型调查样本为例

本文基于农户满意度的视角,通过构建农户满意度指数模型探讨农地转出绩效的影响因素,并利用武汉、鄂州两市农地流转典型地区的调查数据,运用结构方程模型对两地农地转出绩效的影响因素进行了定量研究。研究发现：农户对农地转出活动的感知质量是影响武汉、鄂州两地农地转出绩效的决定性因素。两地政府相关部门对农地流转活动给予的政府支持行为对农地转出绩效的提高起到了极其重要的促进作用。农地转出活动中的可靠性因素对两地农地转出绩效产生了重要的影响。农地转出活动中的规范性措施与人员互动措施对两地农地转出绩效产生了一定的积极影响。两地农地转出后期的农户不满处理系统缺乏效率,负向影响了农地转出绩效。最后,根据研究结论,从改善农地转出绩效限制因素、提高农地转出绩效的角度提出了相关政策建议。     

钴离子在γ-Al2O3载体中自发扩散的研究

采用浸渍法将不同浓度Co(NO3)2溶液浸入多孔γ-Al2O3载体中,得到Co(NO3)2/γ-Al2O3样品,然后将这些样品在不同的温度下烘烤1小时.用X射线衍射(XRD)、X射线光电子能谱(XPS)、扫描电子显微镜(SEM)和正电子湮没寿命谱等方法研究了质量分数(以CoO质量分数计)分别为3.39%和12.63%的Co(Ⅱ)/γ-Al2O3样品中的Co(Ⅱ)随烘烤温度不同而在样品中的扩散情况.     

Using SEM to Analyze Complex Survey Data: A Comparison between Design-Based Single-Level and Model-Based Multilevel Approaches

Both ad-hoc robust sandwich standard error estimators (design-based approach) and multilevel analysis (model-based approach) are commonly used for analyzing complex survey data with nonindependent observations. Although these 2 approaches perform equally well on analyzing complex survey data with equal between- and within-level model structures (B. O. Muthén & Satorra, 1995), the performances of these 2 approaches for analyzing multilevel data with unequal between- and within-level structures have not yet been systematically examined. In this study, we extended B. O. Muthén and Satorra's (1995) Muthén, B. O. and Satorra, A. 1995. Complex sample data in structural equation modeling. Sociological Methodology, 25: 267–316. [Crossref], [Web of Science ®] , [Google Scholar] study by comparing these 2 approaches and an additional model-based maximum model for analyzing multilevel data considering number of clusters, cluster size, intraclass correlation, and the equality of different level structures. The simulation results showed the model-based maximum model generally performed well across conditions. This model is also recommended as an alternative for analyzing nonindependent survey data, especially when the information of the higher level model structure is not known.     

On the Performance of Likelihood-Based Difference Tests in Nonlinear Structural Equation Models

This article investigates likelihood-based difference statistics for testing nonlinear effects in structural equation modeling using the latent moderated structural equations (LMS) approach. In addition to the standard difference statistic T_D, 2 robust statistics have been developed in the literature to ensure valid results under the conditions of nonnormality or small sample sizes: the robust T_DR and the “strictly positive” T_DRP. These robust statistics have not been examined in combination with LMS yet. In 2 Monte Carlo studies we investigate the performance of these methods for testing quadratic or interaction effects subject to different sources of nonnormality, nonnormality due to the nonlinear terms, and nonnormality due to the distribution of the predictor variables. The results indicate that T_D is preferable to both T_DR and T_DRP. Under the condition of strong nonlinear effects and nonnormal predictors, T_DR often produced negative differences and T_DRP showed no desirable power.