Experiencing more mathematics anxiety than expected? Contrasting trait and state anxiety in high achieving students

This study examined mathematics anxiety among high and low achieving students (N = 237, grades 9 and 10) by contrasting trait (habitual) and state (momentary) assessments of anxiety. Previous studies have found that trait anxiety measures are typically rated higher than state measures. Furthermore, the academic self-concept has been identified to play a moderating role in the trait-state discrepancy, with higher academic self-concept leading to a lower discrepancy (i.e. less overestimation of trait anxiety if state assessments reflect actual experience). Therefore, we assumed that high achievers who were expected to have high academic self-concepts would exhibit a smaller trait-state discrepancy than low achievers. Results confirmed these assumptions and revealed that high achievers even underestimated their trait anxiety. Implications are discussed.     

All Men Are Created Equal by the Media On Anti-Female Bias in the News Language

The mass media, namely, radio and television programs, newspaper and websites, plays an important role of broadcasting news, entertaining and educating people. And intentionally, or unintentionally carrying bias. In this male-dominated world,the female are always more often biased. This thesis mainly focuses on the anti-female bias in the news language by giving and discussing the examples selected from different news reports.     

OFDM数字调幅广播时频同步问题的研究

从OFDM系统模型入手,介绍OFDM系统信号波形特点,分析同步错误对OFDM信号的影响,简要介绍时频同步算法的优缺点,重点介绍联合估计定时和频偏的时频定时同步算法,它可以完成对采样定时和符号的同步,实现简单,准确度高,在信噪比低的情况下也能正常工作,也适用于无线多径瑞利衰落环境下的OFDM符号同步方法。     

Opportunities and limitations of using the linguistic category model as a measure of teachers’ implicit stereotypes in Germany

The current work focused on how ethnic stereotypes manifest themselves in language. The aim of our research was to investigate whether the Linguistic Category Model (LCM) is applicable to German teachers' language. More precisely, we investigated whether the categories proposed by Semin and Fiedler (1988) and mostly tested in the English-speaking world are applicable to German teachers' language and whether the pattern of Linguistic Intergroup Bias is evident in teachers' language. The analyses of two samples including in- and pre-service teachers (Study 1: N = 124, 76.6% female; Study 2: N = 104, 67.6% female) revealed difficulties in applying the LCM to German teachers' language. Further, neither of the two conducted studies found patterns of Linguistic Intergroup Bias in teachers’ language. We attribute this to a mismatch between the LCM and the German language and discuss the difficulties and limitations of applying the category system to other languages.