Madeleine Bieg

Do Girls Really Experience More Anxiety in Mathematics

Two studies were conducted to examine gender differences in trait (habitual) versus state (momentary) mathematics anxiety in a sample of students (Study 1: N = 584; Study 2: N = 111). For trait math anxiety, the findings of both studies replicated previous research showing that female students report higher levels of anxiety than do male students. However, no gender differences were observed for state anxiety, as assessed using experience-sampling methods while students took a math test (Study 1) and attended math classes (Study 2). The discrepant findings for trait versus state math anxiety were partly accounted for by students’ beliefs about their competence in mathematics, with female students reporting lower perceived competence than male students despite having the same average grades in math. Implications for educational practices and the assessment of anxiety are discussed.

What Students Think They Feel Differs from What They Really Feel - Academic Self-Concept Moderates the Discrepancy between Students' Trait and State Emotional Self-Reports

This study investigated whether there is a discrepancy pertaining to trait and state academic emotions and whether self-concept of ability moderates this discrepancy. A total of 225 secondary school students from two different countries enrolled in grades 8 and 11 (German sample; n = 94) and grade 9 (Swiss sample; n = 131) participated. Students’ trait academic emotions of enjoyment, pride, anger, and anxiety in mathematics were assessed with a self-report questionnaire, whereas to assess their state academic emotions experience-sampling method was employed. The results revealed that students’ scores on the trait assessment of emotions were generally higher than their scores on the state assessment. Further, as expected, students’ academic self-concept in the domain of mathematics was shown to partly explain the discrepancy between scores on trait and state emotions. Our results indicate that there is a belief-driven discrepancy between what students think they feel (trait assessment) and what they really feel (state assessment). Implications with regard to the assessment of self-reported emotions in future studies and practical implications for the school context are discussed.

The Glass Half Empty: How Emotional Exhaustion Affects the State-Trait Discrepancy in Self-Reports of Teaching Emotions

Following from previous research on intensity bias and the accessibility model of emotional self-report, the present study examined the role of emotional exhaustion in explaining the discrepancy in teachers’ reports of their trait (habitual) versus state (momentary, “real”) emotions. Trait reports (habitual emotions, exhaustion) were assessed via trait questionnaires, and state reports (momentary emotions) were assessed in real time via the experience sampling method by using personal digital assistants (N = 69 high school teachers; 1,089 measures within teachers). In line with our assumptions, multi-level analyses showed that, as compared to the state assessment, teachers reported higher levels of habitual teaching-related emotions of anger, anxiety, shame, boredom, enjoyment, and pride. Additionally, the state-trait discrepancy in self-reports of negative emotions was accounted for by teachers’ emotional exhaustion, with high exhaustion levels corresponding with a greater state-trait discrepancy. Exhaustion levels did not moderate the state-trait discrepancy in positive emotions indicating that perceived emotional exhaustion may reflect identity-related cognitions specific to the negative belief system. Implications for research and educational practice are discussed.

Assessing Academic Emotions via the Experience Sampling Method

This chapter outlines the experience sampling method (ESM) and addresses practical issues when conducting ESM research on academic emotions (sample size, number of assessments, missing data, hardware and software, measures, analysis). Examples of ESM studies in the field of academic emotions are highlighted, and the strengths (e.g., high ecological validity) as well as pitfalls (e.g., intensive data collection) of ESM for the assessment of emotions in educational settings are discussed. Finally, the chapter highlights opportunities for growth in this research area, including the development of state academic emotions scales and combining real-time self-reports with objective measures (e.g., biological data).

Academic Emotions and Their Regulation via Emotional Intelligence

The focus of this chapter is academic emotions, defined as emotions related to learning and achievement. In the first part, we define academic emotions and outline methods for assessing them. We then describe the relationship between academic emotions and other constructs, focusing on Pekrun’s (Educational Psychology Review, 18, 315–341, 2006) control-value theory to explain the effects and antecedents of academic emotions. In the second part of the chapter, we describe how students can regulate their academic emotions in a goal-directed way. We focus on emotional intelligence (EI) as a central competency for regulating academic emotions. Lastly, we present a model for the development of emotional intelligence in learning and achievement situations.

How Much Trait Variance Is Captured by Measures of Academic State Emotions

Although the popularity of research on academic emotions is on the rise, little is known about the extent to which these emotional experiences are due to stable (trait) versus situational (state) influences. In the present paper, we applied the latent state-trait approach (LST) to multiple state assessments of five frequently experienced discrete academic emotions (enjoyment, pride, anger, anxiety, boredom) to disentangle their trait versus state variance components. We had two main aims: (1) to identify the differential contributions of the person-specific (trait) and situation-specific (state) variance components of discrete academic emotions, and (2) to examine the relations between different discrete academic emotions with regard to their latent trait and latent state residual components. Eight hundred thirty-seven German students participated in this diary study that lasted 2–3 weeks. During this time, students responded to short (two items per emotion) questionnaires asking about their lesson-specific state emotions in mathematics. The results revealed that for each academic emotion the trait variance and state residual components were of about equal size. Further, while differently valenced (positive vs. negative) latent trait components of students’ emotions were mostly uncorrelated (with the exception of boredom), differently valenced latent state residual components of students’ emotions were negatively correlated. We discuss our findings in relation to the structure of current affect and highlight their implications for classroom practices.

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.

Examining the accuracy of students' self-reported academic grades from a correlational and a discrepancy perspective : Evidence from a longitudinal study

The present longitudinal study examined the reliability of self-reported academic grades across three phases in four subject domains for a sample of 916 high-school students. Self-reported grades were found to be highly positively correlated with actual grades in all academic subjects and across grades 9 to 11 underscoring the reliability of self-reported grades as an achievement indicator. Reliability of self-reported grades was found to differ across subject areas (e.g., mathematics self-reports more reliable than language studies), with a slight yet consistent tendency to over-report achievement levels also observed across grade levels and academic subjects. Overall, the absolute value of over- and underreporting was low and these patterns were not found to differ between mathematics and verbal subjects. In sum, study findings demonstrate the consistent predictive utility of students’ self-reported achievement across grade levels and subject areas with the observed tendency to over-report academic grades and slight differences between domains nonetheless warranting consideration in future education research.