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With the COVID-19 outbreak, emergency remote teaching -- an unprepared distant mode of education became the only possible alternative for schools. The present large-scale survey with 3,672 Grade 3 and 9 students, their parents, and 863 teachers/principals was conducted in the metropolitan city of Hong Kong after half a year of school lockdown. Results showed teachers, principals, and parents were worried about students' inability to concentrate and learn without teachers' explanations. In contrast, students, particularly younger ones, were less affected. They perceived their academic achievement was not worsened and they were more lively. Generally, lack of computers and stable internet was not seen as problems. Notably, socially disadvantaged students were not different in their perceived challenges, affects, life satisfaction, or perceived academic achievement. For cities with adequate provision of computers and internet facilities, the pandemic probably forced a positive and giant leap in using advanced technologies and pedagogies.

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.

Critical thinking is one of the important higher-order skills very much treasured in education, but hard to be measured using paper-pencil tests. In line with recent recommendation to measure high-order thinking skills with interactive tasks (vs. static one set of questions), in this study we developed an interactive and automated game-based assessment of critical thinking, using the Toulmin Model. In two real-life simulation stories, through interactive tasks in progressing scenes in the stories, students chose and rated evidence and conflicting reasons as supportive or non-supportive arguments in making the eventual decision. Critical thinking scores were awarded on choosing the appropriate evidence and reasons. The psychometric quality of the game was evaluated with 185 Chinese senior secondary students. Results showed that (i) reliabilities as measured by Cronbach's a of the whole scale and subdomains were reasonable; (ii) parallel form reliability was high; (iii) its correlation and convergent validity with the popular Halpern Critical Thinking Assessment were comparable to those in other studies; (iv) it was generally not related to academic performance; and (v) the game was interesting and engaging. We also noted that students hesitated to query others and they were weak in applying critical thinking to problem-solving, which were in congruent with previous research showing students rarely used critical thinking to solve complex, real-world problems. In sum, we demonstrated successfully the use of interactive simulation tasks in measuring critical thinking. With the advancement of technology, our study suggested the possibility of assessing hard-to-measure important complex higher-order competence with dynamic games.

The big-fish-little-pond effect (BFLPE), the negative effect of school-/class-average achievement on academic self-concept, is one of educational psychology's most universal findings. However, critiques of this research have proposed moderators based on achievement motivation theories. Nevertheless, because these motivational theories are not sufficiently well-developed to provide unambiguous predictions concerning moderation of the BFLPE and underlying social comparison processes, we developed a Theory-Integrating Approach; bringing together a panel of experts, independently making theoretical predictions, revising the predictions over several rounds based on independent feedback from the other experts, and a summary of results. We pit a priori hypotheses derived from achievement motivation theories against the more parsimonious a priori prediction that there is no moderation based on previous BFLPE empirical research and Darwinian-economic theory (N = 1,925 Hong Kong students, 47 classes, M age = 12 years). Consistent with both BFLPE research and Darwinian perspectives, but in contrast to achievement motivation theory predictions, the highly significant BFLPE was not moderated by any of the following: prior achievement, expectancy-value theory variables, achievement goals, implicit theories of ability, self-regulated learning strategies, and social interdependence theory measures. Although we cannot "prove" that there are no student-level moderators of the BFLPE, our synthesis of social comparison posited in the BFLPE theory and an evolutionary perspective support BFLPE's generalizability. We propose further integration of our Theory-Integrating Approach with traditional Delphi methods, combining quantitative and qualitative approaches to develop a priori theoretical predictions and identify limitations in existing theory as an alternative form of systematic review.

In large-scale low-stake assessment such as the Programme for International Student Assessment (PISA), students may skip items (missingness) which are within their ability to complete. The detection and taking care of these noneffortful responses, as a measure of test-taking motivation, is an important issue in modern psychometric models. Traditional approaches based on questionnaires and item response theory may have different limitations. In the present research, we proposed a new way by directly using "participant-own-defined" missing item information (user missingness) in a zero-inflated Poisson model. An empirical study using the PISA 2015 data (eight representative economies in two cultures) and another simulation study were conducted to validate our new approach. Results indicated that our model could successfully capture test-taking motivation. We also found that the Confucian students had lower user missingness irrespective of item positions as compared with their Western counterparts.

Linear mixed-effects models have been increasingly used to analyze dependent data in psychological research. Despite their many advantages over ANOVA, critical issues in their analyses remain. Due to increasing random effects and model complexity, estimation computation is demanding, and convergence becomes challenging. Applied users need help choosing appropriate methods to estimate random effects. The present Monte Carlo simulation study investigated the impacts when the restricted maximum likelihood (REML) and Bayesian estimation models were misspecified in the estimation. We also compared the performance of Akaike information criterion (AIC) and deviance information criterion (DIC) in model selection. Results showed that models neglecting the existing random effects had inflated Type I errors, unacceptable coverage, and inaccurate R-squared measures of fixed and random effects variation. Furthermore, models with redundant random effects had convergence problems, lower statistical power, and inaccurate R-squared measures for Bayesian estimation. The convergence problem is more severe for REML, while reduced power and inaccurate R-squared measures were more severe for Bayesian estimation. Notably, DIC was better than AIC in identifying the true models (especially for models including person random intercept only), improving convergence rates, and providing more accurate effect size estimates, despite AIC having higher power than DIC with 10 items and the most complicated true model. [ABSTRACT FROM AUTHOR]

This study investigated the mediating roles of self-efficacy and anxiety on the effects of teacher-student relationship on mathematical problem-solving ability. A total of 1667 fifth graders from central China participated in the large-scale survey. The findings indicated that (1) teacher-student relationship had a direct and positive effect on students' mathematical problem-solving ability; (2) the positive link between teacher-student relationship and mathematical problem-solving ability was partially mediated through self-efficacy; (3) the teacher-student relationship affected students' mathematical problem-solving ability through self-efficacy and maths anxiety, but the effect of self-efficacy on mathematical anxiety was smaller. Implications for the importance of teacher-student relationships in education as well as suggestions for future research are discussed.

Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e., 1-1-1, 2-1-1, and 2-2-1) of intensive longitudinal mediation (ILM) analyses based on DSEM and RDSEM models. Specifically, each ILM model was demonstrated with a simulated example and illustrated with the corresponding annotated Mplus codes. We compared two types of detrending methods in mediation analyses and showed that RDSEM was superior to DSEM because the latter included the timetj variable as a Level 1 predictor. Lastly, we extended ILM analyses based on DSEM and RDSEM to multilevel autoregressive mediation models, cross-classified DSEM, and intensive longitudinal moderated mediation models. [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 present study examined the link between teacher-student relationship at the class level and academic achievement via the serial multiple mediation effect of self-efficacy and learning strategy in Chinese EFL context with 11,036 eighth graders. Student-reported measures of teacher-student relationship, English self-efficacy, learning strategy and curriculum-based measures of English achievement were collected in fall 2015. Multilevel mediation model revealed that the positive relationship between teacher-student relationship at the class level and English achievement was partially mediated by self-efficacy, cognitive and metacognitive strategy, and serially mediated by self-efficacy and then learning strategy in Chinese EFL context, controlling for SES and gender. The findings suggest that positive teacher-student relationship can help students to develop English proficiency by fostering their English self-efficacy and use of learning strategy. The results of the present study extend our understanding of influential factors in foreign language learning processes and hold substantive theoretical and practical implications for educational researchers as well as teachers.

Two groups of 12-year-old ethnic minority (EM) users of alphasyllabary (66 Tibetan and 45 Yi) were compared with 42 Han Chinese students in comprehending Chinese narrative and expository texts, each with inferential questions requiring short open-ended written answers. Three constructs (verbal working memory, orthographic and sentential processing), each with two indicators, were hypothesized to predict text comprehension differentially in the three groups. A 43-item Students' Approaches to Learning (SAL) scale showed the EM students might not have developed effective strategies in learning Chinese. A task x group MANCOVA with SAL as covariate showed substantial differences in the students' performance. Multiple comparisons found group differences changed across tasks. Structural equation modeling, multiple regression analyses point to the significant and differential contribution of the constructs and the tasks to the two genres of Chinese text comprehension in the different groups. Educational implications include strengthening teaching the structure and function of Chinese characters, words, syntax and the need for adaptive curriculum materials.

To examine relationships between the global construct of multidimensional data and external criteria, bifactor exploratory structural equation modeling (B-ESEM) and traditional methods (e.g., unidimensional confirmatory factor analyses, CFA; parceled CFA; and bifactor models) can be used. We compared their performance in a Monte Carlo simulation study. (a) B-ESEM performed the best, followed by parceled CFA and bifactor models, and the unidimensional CFA was the worst. The relative biases of predicting the external criteria with the global construct increased with larger cross-loadings and greater model complexity and decreased with an increasing percentage of uncontaminated correlations (PUC). (b) With few large cross-loadings, relative biases of B-ESEM structural coefficients were negligible. In contrast, PUC determined our choice of unidimensional CFA, parceled CFA, or bifactor models. (c) With many large cross-loadings and high general factor loadings, B-ESEM was preferred. (d) No model was acceptable with many large cross-loadings and low general factor loadings. [ABSTRACT FROM AUTHOR]

Critical thinking is a unifying goal of modern education. While past research has mostly examined the efficacy of a single instructional approach to teaching critical thinking, recent literature has begun discussing mixed teaching approaches. The present study examines three modes of instruction, featuring the direct instruction approach and the inquiry-based approach in different sequences and proportions, in enhancing Chinese secondary student's critical thinking performance. A total of 651 Grade 12 students participated in an 18-hour intervention with pre- and post-intervention measures on critical thinking performance and critical thinking dispositions. Specifically, critical thinking assessments utilizing different response format were used. Those who received training showed greater improvement on at least one of the critical thinking assessments compared to those who received no training. Participants' performances with regards to different critical thinking assessments are discussed. Benefits of adopting more than one instructional approach to teaching critical thinking are highlighted.

The present study investigated multidimensional motivation and engagement among Chinese middle school students in Australia (N?=?273), Hong Kong (N?=?528), and Mainland China (N?=?2106; randomly selected N?=?528). Findings showed that a multidimensional model of motivation and engagement fit very well for all three groups. Multi-group invariance tests showed that the number of factors, factor loadings, factor correlations and item uniquenesses were invariant across the three groups -- as were inter-correlations with a set of cognate correlates (class participation, school enjoyment, positive intentions, academic buoyancy) -- hence no differences of "kind". However, differences of "degree" were indicated through significant mean-level effects between groups, with self-reports favouring Australian Chinese students over Hong Kong and (to a lesser extent) Mainland Chinese students. We propose these findings shed important light on Chinese students' academic motivation and engagement and also on socio-cultural perspectives on motivation and engagement because they assist understanding about effects attributable to context and effects attributable to ethnicity. Given this, the study is a timely contribution to current understanding of the Chinese learner in this, the "Asian Century".

The present study examined pedagogic components of Chinese reading literacy in a representative sample of 1164 Grades 7, 9 and 11 Chinese students (mean age of 15 years) from 11 secondary schools in Hong Kong with each student tested for about 2.5 hours. Multiple group confirmatory factor analyses showed that across the three grade levels, the eight reading literacy constructs (Essay Writing, Morphological Compounding, Correction of Characters and Words, Segmentation of Text, Text Comprehension, Copying of Characters and Words, Writing to Dictation and Reading Aloud), each subserved by multiple indicators, had differential concurrent prediction of scaled internal school performance in reading and composing. Writing-reading and their interactive effects were foremost in their predictive power, followed by performance in error correction and writing to dictation, morphological compounding, segmenting text and copying with reading aloud playing a negligible role. Our battery of tasks with some refinement could serve as a screening instrument for secondary Chinese students struggling with Chinese reading literacy.

The internal/external frame of reference (I/E) model (Marsh, 1986) posits that the effects of contrasting math and verbal domains of achievement are positive for matching academic self-concepts (ASCs) but negative for nonmatching ASCs (i.e., math achievement on verbal ASC; verbal achievement on math ASC). We extend the classic I/E model by contrasting the math domain with 2 verbal domains (Chinese, native language; English, foreign language) in combination with language of instruction (English or Chinese) for a sample of 1,950 Hong Kong Year 7 students. Consistent with predictions based on the Marsh and Shavelson (1985) ASC model and our extension of the I/E model, we found that native and foreign languages were not contrasted with each other in the formation of ASCs. However, achievement in both verbal domains negatively predicted math ASC, while math achievement was also negatively predicted by ASCs in both verbal domains. Support for the predictions was similar for students taught in English and Chinese languages of instruction. (Contains 4 figures and 1 table.)

Standardized parameter estimates are routinely used to summarize the results of multiple regression models of manifest variables and structural equation models of latent variables, because they facilitate interpretation. Although the typical standardization of interaction terms is not appropriate for multiple regression models, straightforward alternatives are well known (Aiken & West, 1991; Friedrich, 1982). Whereas the analogous problem exists for the estimation of latent interactions in structural equation modeling (SEM), the problem is more complex and apparently has not been resolved. Here we demonstrate that the appropriate "standardized" parameter estimates are easily formulated from parameter estimates routinely available from existing SEM software packages. Some properties of the appropriate "standardized" solution are mathematically derived, including the demonstration that the main and interaction effects are scale-free, as are the factor loadings. These desirable properties of the standardized solution are illustrated with a simulation data set using the unconstrained approach (Marsh, Wen, & Hau, 2004) to estimating latent interactions. These results support the use of the appropriate "standardized" solutions in interpreting and comparing SEM estimates of latent interactions. (Contains 2 tables, 2 figures, and 3 footnotes.)

The present study explored motivation and engagement among Chinese and Australian school students. Based on a sample of 528 Hong Kong Chinese 12-13 year olds and an archive sample of 6,366 Australian 12-13 year olds, achievement motivation was assessed using the Motivation and Engagement Scale-High School (MES-HS). Confirmatory factor analysis and structural equation modeling using LISREL found that, across Chinese and Australian students, there was similar factor structure, reliability, correlations with educational outcomes, and gender and age effects--suggesting there are no fundamental differences of "kind" between the two cultures. There were, however, differences of "degree" in that Australian students reported significantly higher levels of adaptive achievement motivation and significantly lower levels of maladaptive achievement motivation. It is concluded that although Australian students have higher levels of reported achievement motivation than Chinese students on a number of dimensions, the two groups' fundamental orientation does not appear to be markedly different in terms of motivation structure, profile, and relationships. This holds implications for cross-cultural motivation assessment, data analysis, and programmatic intervention aimed at enhancing (and sustaining) students' achievement motivation in different cultural and national contexts. (Contains 4 tables.)

The present study examined the role of verbal working memory (memory span, tongue twister), 2-character Chinese pseudoword reading, rapid automatized naming (letters, numbers), and phonological segmentation (deletion of rimes and onsets) in inferential text comprehension in Chinese in 518 Chinese children in Hong Kong in Grades 3 to 5. It was hypothesized that verbal working memory, together with a small contribution from the other constructs, would explain individual variation in the children's text comprehension. Structural equation modeling and hierarchical multiple regression analyses generally upheld the hypotheses. Though Chinese pseudoword reading did not play an important mediating role in the effect of verbal working memory on text comprehension, verbal working memory had strong effects on pseudoword reading and text comprehension. The findings on the Chinese language support current Western literature as well as display the differential role of the constructs in Chinese reading comprehension.