Search

We examined the performance of coefficient alpha and its potential competitors (ordinal alpha, omega total, Revelle's omega total [omega RT], omega hierarchical [omega h], greatest lower bound [GLB], and coefficient "H") with continuous and discrete data having different types of non-normality. Results showed the estimation bias was acceptable for continuous data with varying degrees of non-normality when the scales were strong (high loadings). This bias, however, became quite large with moderate strength scales and increased with increasing non-normality. For Likert-type scales, other than omega h, most indices were acceptable with non-normal data having at least four points, and more points were better. For different exponential distributed data, omega RT and GLB were robust, whereas the bias of other indices for binomial-beta distribution was generally large. An examination of an authentic large-scale international survey suggested that its items were at worst moderately non-normal; hence, non-normality was not a big concern. We recommend (a) the demand for continuous and normally distributed data for alpha may not be necessary for less severely non-normal data; (b) for severely non-normal data, we should have at least four scale points, and more points are better; and (c) there is no single golden standard for all data types, other issues such as scale loading, model structure, or scale length are also important.

We compared coefficient alpha with five alternatives (omega total, omega RT, omega h, GLB, and coefficient H) in two simulation studies. Results showed for unidimensional scales, (a) all indices except omega h performed similarly well for most conditions; (b) alpha is still good; (c) GLB and coefficient H overestimated reliability with small samples and short scales, and (d) sensitivity to scale quality reduced with longer scales. For contaminated scales, (a) all indices except omega h were reasonably unbiased with non-severe contamination; (b) alpha, omega total, and GLB were more sensitive in picking up contamination with shorter scales, whereas omega RT and omega h were not; and (c) coefficient H could not pick up contaminated items among high-quality items. For applied researchers, (a) supplementary information of scale characteristics helps choose the appropriate index; (b) comparing different scales with one golden standard is inappropriate; (c) omega h should not be used alone.

Background: Socioeconomic status (SES) is important in students' reading development. The mechanism of how they are linked, however, is underexplored. Aims: This research aimed to explore whether reading self-concept mediates the link between SES and reading achievement and whether teacher support moderates the direct and indirect link between SES and reading achievement. Samples: Using PISA 2018 database, we selected 17,346 15-year-olds from 537 schools in B-S-J-Z (China) and the United States (U.S.). Methods: Multilevel linear models were calculated to explore the potential mediation of self-concept and the potential moderation of teacher support between SES and reading achievement. Results: Results reveal that reading self-concept mediated the link between SES and reading achievement at student level both in China and the United States, and teacher support moderated the link between SES and reading self-concept both at student level and school level only in China, but not in the United States. Conclusion: Our research highlights the importance of self-concept and teacher support in improving students' reading achievement, especially for students of low SES, which has important theoretical significance and practical enlightenment for reading instruction.

The article introduces a mathematics education measure in response to the COVID-19 epidemic in China and explores students' degree of approval and perception of digital equity towards the response. After the outbreak of the COVID-19, "the Chinese New Century Primary School Mathematics Textbook" (NCPM) committee had developed a series of micro classes (abbreviated as NCPM micro classes), and more than 25 million teachers and students in China watched the NCPM micro classes during the 3 months social isolation. Then, students' degree of approval towards the NCPM micro classes and perception of digital equity were examined after social isolation. A total of 132,740 pieces of data were collected from Chinese primary school students. Quantitative analysis of student's degree of approval towards different parts of NCPM micro classes indicated that the introduction, interaction, summary and consolidation, curriculum characteristics, and goal achievement parts of the NCPM micro classes have received high approval from students, and students with higher former achievement perceived a higher degree of approval towards the NCPM micro classes. Furthermore, we found that gender, socioeconomic status, school location, and learning location had no significant impact on students' degree of approval, indicating a digital equity exists. This study helps researchers or educators understand the mathematics education response to the COVID-19 outbreak in China and extends our understanding of primary students' degree of approval and perception of digital equity with these online classes.

Fault diagnosis of wind turbines has always been a challenging problem due to their complexity and harsh working conditions. Although data-mining-based fault diagnosis methods can accurately and efficiently diagnose potential faults, the visibility is extremely poor. In this paper, digital twin technology is introduced into the fault diagnosis of wind turbine drive train systems, and a wind turbine drive train fault diagnosis method based on digital twin technology is proposed, which monitors and simulates the actual operating condition in real-time by establishing a digital twin model of the wind turbine drive train. In addition, an improved variational modal decomposition combined with particle swarm optimization least squares support vector machine (IVMD-PSO-LSSVM) fault diagnosis method is proposed, which not only improves the accuracy of fault diagnosis but also effectively shortens the diagnosis time and strengthens the response speed of the system. Finally, a digital twin system for condition monitoring and fault diagnosis of wind turbine drive trains is developed based on the Unity 3D platform. Experiments show that the proposed IVMD-PSO-LSSVM can accurately identify fault types with an accuracy rate of 99.1%, which is an improvement of 3.4% compared to before. The proposed digital twin model can be used for real-time monitoring of wind turbine vibration data and provide a more intuitive real-time simulation of the wind turbine's operating status. This facilitates quick fault location and enables more accurate and efficient maintenance. [ABSTRACT FROM AUTHOR]

With the widening urban-rural gap caused by urbanisation, the equity of urban-rural education has become a research hotspot. This study explored the differences in motivational beliefs about English learning among Chinese urban and rural students and the impact of motivational beliefs on their English performance. A total of 6326 urban and 2600 rural Chinese eighth graders participated in the survey. Data were collected using self-reported motivational belief scale and English performance test. The independent sample t-test showed that motivational beliefs and English performance of urban students were significantly higher than that of rural students in China. Multilevel analysis demonstrated that at the student level, intrinsic value has the highest predictive power for English performance of urban and rural students, while extrinsic value can only predict English performance of rural students and self-efficacy can only predict English performance of urban students. However, at the school level, motivational beliefs cannot significantly predict English performance of urban and rural students. These results are of great significance to improve English education in rural areas and further promote education equity in China and other East Asian countries. [ABSTRACT FROM AUTHOR]

Teacher feedback in reading class is closely associated with students' reading achievement. However, the underlying mechanisms of their relationship has been underexplored, especially in cross-cultural contexts. Using Control Value Theory of Achievement Emotions (CVTAE), this study tested the cross-cultural generalizability of reading enjoyment as a mediator between teacher feedback and reading achievement among 536,848 15-year-olds from 75 countries/economies in PISA 2018. Multilevel structural equation modeling (MSEM) results showed that students who perceived more teacher feedback gained more enjoyment in reading activities, and thus scored higher in reading. This relationship was confirmed in 73 out of 75 countries/economies. However, at the school level, this association existed in only 25 of 75 countries/economies. These findings indicate cross-cultural generalization of reading enjoyment as a mediator between teacher feedback and reading achievement only at the student level, which not only provides cross-cultural evidence for CVTAE, but also sheds light on reading instruction of adolescents. [ABSTRACT FROM AUTHOR]

Short scales are time‐efficient for participants and cost‐effective in research. However, researchers often mistakenly expect short scales to have the same reliability as long ones without considering the effect of scale length. We argue that applying a universal benchmark for alpha is problematic as the impact of low‐quality items is greater on shorter scales. In this study, we proposed simple guidelines for item reduction using the "alpha‐if‐item‐deleted" procedure in scale construction. An item can be removed if alpha increases or decreases by less than.02, especially for short scales. Conversely, an item should be retained if alpha decreases by more than.04 upon its removal. For reliability benchmarks,.80 is relatively safe in most conditions, but higher benchmarks are recommended for longer scales and smaller sample sizes. Supplementary analyses, including item content, face validity, and content coverage, are critical to ensure scale quality. [ABSTRACT FROM AUTHOR]

The correlation between motivational beliefs and foreign language learning has been widely explored. However, there has been little investigation of this link among learners with different foreign language levels. Based on expectancy-value theory (EVT), this research examined the association between motivational beliefs and English achievement of 11,854 Chinese secondary students. Data were collected using students' self-reported English self-efficacy, intrinsic value, utility value, and English achievement test. The results of ANOVA showed that self-efficacy, intrinsic value, and utility value of high-achieving English learners were significantly higher than that of medium-achieving ones, followed by low-achieving ones. Multiple regression analysis demonstrated that after controlling for socioeconomic status and gender, intrinsic value was most correlated with high- and medium-achieving learners' English achievement, followed by self-efficacy, while utility value was not significantly associated with English achievement of the two groups. In addition, utility value was most strongly related with low-achieving learners' English achievement, followed by intrinsic value, but self-efficacy was not positively linked with their English achievement. These findings not only extend EVT and validate the situative perspective of motivation research, but also have practical implications for foreign language education. [ABSTRACT FROM AUTHOR]

We examined the performance of coefficient alpha and its potential competitors (ordinal alpha, omega total, Revelle's omega total [omega RT], omega hierarchical [omega h], greatest lower bound [GLB], and coefficient H) with continuous and discrete data having different types of non-normality. Results showed the estimation bias was acceptable for continuous data with varying degrees of non-normality when the scales were strong (high loadings). This bias, however, became quite large with moderate strength scales and increased with increasing non-normality. For Likert-type scales, other than omega h, most indices were acceptable with non-normal data having at least four points, and more points were better. For different exponential distributed data, omega RT and GLB were robust, whereas the bias of other indices for binomial-beta distribution was generally large. An examination of an authentic large-scale international survey suggested that its items were at worst moderately non-normal; hence, non-normality was not a big concern. We recommend (a) the demand for continuous and normally distributed data for alpha may not be necessary for less severely non-normal data; (b) for severely non-normal data, we should have at least four scale points, and more points are better; and (c) there is no single golden standard for all data types, other issues such as scale loading, model structure, or scale length are also important. [ABSTRACT FROM AUTHOR]

Family context has been found to influence achievement emotions, but the factors that might moderate this association remain relatively unexplored. To address this gap, this research examined the moderation of teacher–student relationships (TSR) in the link between family socioeconomic status (SES) and emotions in foreign language (FL) learning drawing on control-value theory of achievement emotions and attachment theory. The research involved 4,155 eighth-grade students from China, who completed scales reporting their SES, FL enjoyment, FL anxiety, and FL burnout. The moderating effect model demonstrated that TSR played a moderating role in the relationship between SES and negative emotions in FL learning such as anxiety and burnout. However, no significant moderation was observed between SES and FL enjoyment. Specifically, a warm TSR was found to alleviate the negative impact of low SES on negative emotions in FL learning, such as anxiety and burnout. Conversely, TSR did not demonstrate the capacity to enhance the positive emotions associated with FL learning, such as enjoyment, among students from higher SES backgrounds. This research suggests the necessity to intervene with low SES students, with the aim of fostering supportive TSR and ultimately alleviating negative emotions in FL learning. [ABSTRACT FROM AUTHOR]