Teachers’ judgments of students’ academic achievement are not only affected by the achievement themselves but also by several other characteristics such as ethnicity, gender, and minority status. In real-life classrooms, achievement and further characteristics are often confounded. We disentangled achievement, ethnicity and minority status and examined whether the achievement of ethnic minority students is judged according to the predominant expectation (expectation hypothesis) and whether teachers’ judgment accuracy is influenced by students’ ethnicity or their minority status (ethnicity hypothesis or minority hypothesis). We conducted 4 experimental studies with a computer simulation (the Simulated Classroom). In Studies 1 and 2 with N = 34 and N = 30 participants, we implemented Turkish (Study 1) and Asian students (Study 2) as minorities. In contrast to the expectation hypothesis, the expectations attributed to the achievement of ethnic minority students did not bias teachers’ judgments. In both studies we found greater judgment accuracy for ethnic minority students, thereby probing the ethnicity hypothesis. In Study 3 with N = 48 participants, we further disentangled ethnicity and minority using German students as minority students, thus probing the minority hypothesis. Again, minority students were judged more accurately. Implementing gender (male vs. female) as the minority characteristic in Study 4, with N = 52 participants, yielded the same result: Minority students were judged more accurately, therefore supporting the minority hypothesis. Thus, classroom characteristics need to be considered in research on teachers’ judgment accuracy to clarify the influence of individual student characteristics and composition effects beyond individual effects. (PsycINFO Database Record (c) 2017 APA, all rights reserved)

The effects of student characteristics on teachers’ judgment accuracy: Disentangling ethnicity, minority status, and achievement.

The concept of self is central to personhood, but personality research has largely ignored the relevance of recent advances in self–concept theory: multidimensionality of self–concept (focusing ins...

Psychological Comparison Processes and Self‐Concept in Relation to Five Distinct Frame‐of‐Reference Effects: Pan‐Human Cross‐Cultural Generalizability over 68 Countries

The developmental interplay of academic self-concept and achievement within and across domains among primary school students

This paper studies how a student’s ordinal rank in a peer group affects performance and specialisation choices in university. By exploiting data with repeated random assignment of students to teaching sections, we find that a higher rank increases performance and the probability of choosing related follow-up courses and majors. We document two types of dynamic effects. First, earlier ranks are less important than later ranks. Second, responses to rank changes are asymmetric: improvements in rank raise performance, while decreases in rank have no effect. Rank effects partially operate through students’ expectations about future grades.

Achievement Rank Affects Performance and Major Choices in College

The question of how learners’ motivation influences their academic achievement and vice versa has been the subject of intensive research due to its theoretical relevance and important implications for the field of education. Here, we present our understanding of how influential theories of academic motivation have conceptualized reciprocal interactions between motivation and achievement and the kinds of evidence that support this reciprocity. While the reciprocal nature of the relationship between motivation and academic achievement has been established in the literature, further insights into several features of this relationship are still lacking. We therefore present a research agenda where we identify theoretical and methodological challenges that could inspire further understanding of the reciprocal relationship between motivation and achievement as well as inform future interventions. Specifically, the research agenda includes the recommendation that future research considers (1) multiple motivation constructs, (2) behavioral mediators, (3) a network approach, (4) alignment of intervals of measurement and the short vs. long time scales of motivation constructs, (5) designs that meet the criteria for making causal, reciprocal inferences, (6) appropriate statistical models, (7) alternatives to self-reports, (8) different ways of measuring achievement, and (9) generalizability of the reciprocal relations to various developmental, ethnic, and sociocultural groups.

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Motivation-Achievement Cycles in Learning: a Literature Review and Research Agenda

The Big-fish-little-Pond effect is well acknowledged as the negative effect of class/school average achievement on student academic self-concept, which profoundly impacts student academic performance and mental development. Although a few studies have been done with regard to this effect, inconsistence exists in the effect size with little success in finding moderators. Here, we present a meta-analysis to synthesize related literatures to reach a summary conclusion on the BFLPE. Furthermore, student age, comparison target, academic self-concept domain, student location, sample size, and publication year were examined as potential moderators. Thirty-three studies with fifty-six effect sizes (total N = 1,276,838) were finally included. The random effects model led to a mean of the BFLPE at β = -0.28 (p < 0.001). Moreover, moderator analyses revealed that the Big-Fish-Little-Pond effect is an age-based process and an intercultural phenomenon, which is stronger among high school students, in Asia and when verbal self-concept is considered. This meta-analysis is the first quantitative systematic overview of BFLPE, whose results are valuable to the understanding of BFLPE and reveal the necessity for educators from all countries to learn about operative means to help students avoid the potential negative effect. Future research expectations are offered subsequently.

The Big-Fish-Little-Pond Effect on Academic Self-Concept: A Meta-Analysis.

Using PISA 2012 data, the present study explored profiles of mathematics anxiety (MA) among 15-year old students from Finland, Korea, and the United States to determine the similarities and differences of MA across the three national samples by applying a multi-group latent profile analysis (LPA). The major findings were that (a) three MA profiles were found in all three national samples, i.e., Low MA, Mid MA, and High MA profile, and (b) the percentages of students classified into each of the three MA profiles differed across the Finnish, Korean, and American samples, with US having the highest prevalence of High MA, and Finland the lowest. Multi-group LPA also provided clear and useful latent profile separation. The High MA profile demonstrated significant poorer mathematics performance and lower mathematics interest, self-efficacy, and self-concept than the Mid and Low MA profiles. Same differences appeared between the Mid and Low MA profiles. The implications of the findings seem clear: (1) it is possible that there is some relative level of universality in MA among 15-year old students which is independent of cultural context; and (2) multi-group latent profile analysis could be a useful analytic tool for research on the study of classification and cultural differences of MA.

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Profiles of Mathematics Anxiety Among 15-Year-Old Students: A Cross-Cultural Study Using Multi-Group Latent Profile Analysis.

Item response theory (IRT) observed score kernel equating was evaluated and compared with equipercentile equating, IRT observed score equating, and kernel equating methods by varying the sample size and test length. Considering that IRT data simulation might unequally favor IRT equating methods, pseudo tests and pseudo groups were also constructed to make equating results comparable with those from the IRT data simulation. Identity equating and the large sample single group rule were both set as criterion equating (or true equating) on which local and global indices were based. Results show that in random equivalent groups design, IRT observed score kernel equating is more accurate and stable than others. In non-equivalent groups with anchor test design, IRT observed score equating shows lowest systematic and random errors among equating methods. Those errors decrease as a shorter test and a larger sample are used in equating; nevertheless, effect of the latter one is ignorable. No clear preference for data simulation method is found, though still affecting equating results. Preferences for true equating are spotted in random Equivalent Groups design. Finally, recommendations and further improvements are discussed.

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A Comparison of IRT Observed Score Kernel Equating and Several Equating Methods.

Aims The objective of this study was to investigate the longitudinal trajectory of BMI in the Chinese population, and to assess whether the gender or other personal characteristics were related to BMI, and whether there was a change in trajectory over time. Methods Data were obtained from 3,574 Chinese (5 to 89 years of age) who participated in the 2000–2011 of the China Health and Nutrition Survey. Latent growth curve models were used to investigate the longitudinal trajectory of BMI, and to examine the effect of some personal characteristics on BMI trajectory. Results The linear model resulted in a mean initial BMI value of 22.90 and a significant mean slope (Ms = 0.19, t = 10.73, p<0.001), suggesting a steady increase in BMI over time for the whole sample. For covariates, the educational level, alcohol and physical activity had differences on initial scores for BMI (β = 0.05, p<0.001; β = -0.12, p<0.05; β = -0.08, p<0.05; respectively.), and the age had differences on both the initial scores and slope for BMI (β = 0.01, p = <0.05; β = -0.03, p<0.01; respectively.). Baseline measures revealed gender-associated differences on initial scores for BMI, and the slope for male was significantly steeper than that for female (β = -0.11, p<0.05). The initial BMI status of Chinese living in the rural areas was significantly higher than that of Chinese living in the urban areas, and the slope for rural status was significantly steeper than that for urban status (β = 0.21, p<0.001). Conclusions Results indicated a linear trajectory of BMI in the Chinese population over a 12-year period. The longitudinal trajectories differed by age, gender and urban-rural status, suggesting different interventions should be adopted for different groups.

https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0207845&type=printable

The longitudinal trajectory of body mass index in the Chinese population: A latent growth curve analysis

Analysis of social network data often faces the problem of tie non-response. Recent studies show that the results of social network analyses can be severely biased if tie non-response was ignored. To overcome the problems created by tie non-response, several treatments were proposed in the literature: complete-case approach, unconditional mean imputation, reconstruction, and multiple imputation. In this paper we assessed the impact of tie non-response on social network analysis and investigated the performance of four treatments to handle tie non-response. The simulation results showed that ignoring tie non-response data in network analysis could underestimate the degree and centralization of social networks depending on the types of network and the proportion of missing ties. We also found that unconditional mean imputation was the best tie non-response treatment. Multiple imputation could successfully correct for tie non-response in a few specific situations. Complete case approach and reconstruction, however, were not recommended. We advocate the importance of further research to better understand consequences of tie non-response in social networks analysis and to provide statistical guidance to researchers to tackle this problem in the field.

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Minqiang Zhang

Papers

The Big-Fish-Little-Pond Effect on Academic Self-Concept: A Meta-Analysis.

Profiles of Mathematics Anxiety Among 15-Year-Old Students: A Cross-Cultural Study Using Multi-Group Latent Profile Analysis.

A Comparison of IRT Observed Score Kernel Equating and Several Equating Methods.

The longitudinal trajectory of body mass index in the Chinese population: A latent growth curve analysis

A Comparison Study of Tie Non-response Treatments in Social Networks Analysis