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In this doctoral thesis, I aimed to investigate the interplay between achievement and achievement motivation. To address this topic, I have chosen two important strands of research that provide different angles on the interplay between achievement and achievement motivation within the framework of the SEVT. The presented research questions were examined by capitalizing on data from international large-scale assessments.

The first strand of research, which I covered in Study I, was the extent to which gender differences in top-performing math students’ achievement, achievement profiles, and achievement motivation exist. While prior studies have largely examined single, isolated domains and have had a strong focus on U.S. samples, a systematic, meta- analytical analysis of these gender differences in the group of top-performing math

students across countries is lacking. To this end, I aimed to tackle in Study I the following research question:

Research Question 1: What is the extent of gender differences in top-performing

math students’ achievement, achievement profiles, and achievement motivation in mathematics, reading, and science across countries?

By applying a two-stage multilevel random-effects IPD meta-analysis of

representative individual student data, the main goal was to provide reliable and widely generalizable empirical knowledge about the direction, size, and variability of these gender differences in top-performing math students’ achievement, achievement profiles, and achievement motivation in these three core academic domains for a large number of countries. To this end, these analyses were conducted in the group of top-performing math students (top 5%) by drawing on six cycles from PISA (2000–2015, N = 115,481, 15-year- olds, 82 countries).

Furthermore, it is unclear how gender differences in top-performing math students emerge. One potential reason for cross-national variability in gender differences in this group of students are varying sociocultural factors, such as the level of gender equality in a country. SEVT and SRT predict that gender differences should be smaller in more gender equal societies than in less gender equal societies. To this end, I tackled in Study I a second research question:

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Research Question 2: To what extent are cross-national gender differences in the

group of top-performing math students related to sociocultural factors, or more specifically, to the level of gender equality in a country?

Using the same data as for Research Question 1, the goal was to examine the moderating role of different gender equality indicators for gender differences in top- performing math students’ achievement, achievement profiles, and achievement

motivation. Gender differences were synthesized in a two-stage multilevel mixed-effects IDP meta-analyses that examined the moderating effects of nation-level gender equality indicators in multivariate meta-regressions. Domain-specific gender equality indicators (i.e., primary, secondary, tertiary enrollment ratios and women’s share of higher positions and research positions) were selected from the ILO, the OECD, the UN, and UNESCO.

The second research strand, which I tackled in Study II, refers to the question of how achievement and academic self-concept––a central motivational construct in

educational psychology––are functionally related. The relationship between achievement and corresponding self-concepts is a critical aspect of the SEVT, but also of other

prominent theories of self-concepts formation. Researchers implicitly assume the relation between achievement and corresponding self-concepts to be linear. Although assuming a nonlinear relation between achievement and corresponding self-concepts is highly plausible because of individuals’ use of self-protective strategies in self-evaluative

situations, the functional relation between these constructs has not yet been systematically examined. To this end, I aimed to tackle the following research question in Study II:

Research Question 3: Which functional relation exists between students’ academic

achievement and corresponding academic self-concepts?

The goal was to examine whether relations between achievement and corresponding self-concepts are nonlinear and to what extent the nonlinearity is

generalizable across different domains, age groups, countries, and analytical approaches in an integrative data analysis. An integrative data analysis investigates the robustness of results by applying the same analysis protocol to several data sets (here: eight cycles from PISA [2000 mathematics and verbal domain, 2003, 2012], TIMSS [2011, 2015], and PIRLS [2011, 2016]). The results were then synthesized in multilevel meta-analytic models. To further examine the generalizability of the results, the functional relation between achievement and corresponding self-concepts was analyzed across two domains (mathematics and the verbal domain), two age groups (elementary and secondary school students) across 13 countries using two analytical approaches (quadratic and interrupted regressions).

Together, by combining both research strands and answering the above-mentioned research questions, this doctoral thesis aims to foster the understanding of the interplay between achievement and achievement motivation in new ways and to inform the SEVT. To do so, I applied state-of-the-art research synthesis methods on representative high- quality student data, and adopted measures of intraindividual hierarchies in top-performing math students’ achievement. To provide an overview of the examined relationships

assumed by the SEVT, I illustrated and color-coded them for each study in Figure 4 (Study I) and Figure 5 (Study II). In the figures, only those components of the SEVT are depicted that were covered in the respective studies (for the full model, see Figure 1). As shown in Figures 4 and 5, Study I covered a broad range of gender differences in top-performing math students’ achievement, achievement profiles, and achievement motivation related to the SEVT, whereas Study II focused more specifically on two components of the SEVT–– achievement and academic self-concepts. Figure 6 provides a combined overview of the examined relationships assumed by the SEVT for the doctoral thesis as a whole.

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Figure 4. Overview of Components of the Situated Expectancy–Value Theory (SEVT) That Were Examined in Study I of the Present Doctoral

Thesis.

Note. Inner rectangle = Constructs assumed by the SEVT; Outer rectangle = Selected set of variables included in the analysis.

Adapted from “35 years of research on students’ subjective task values and motivation: A look back and a look forward” by A. Wigfield and J. S. Eccles, 2020, in A. J. Elliot, Advances in Motivation Science, Vol. 7, p. 165 (https://doi.org/10.1016/bs.adms.2019.05.002). Copyright 2020 by Elsevier. Reprinted with permission.

Figure 5. Overview of Components of the Situated Expectancy–Value Theory (SEVT) That Were Examined in Study II of the Present Doctoral

Thesis.

Note. Inner rectangle = Constructs assumed by the SEVT; Outer rectangle = Selected set of variables included in the analysis.

Adapted from “35 years of research on students’ subjective task values and motivation: A look back and a look forward” by A. Wigfield and J. S. Eccles, 2020, in A. J. Elliot, Advances in Motivation Science, Vol. 7, p. 165 (https://doi.org/10.1016/bs.adms.2019.05.002). Copyright 2020 by Elsevier. Reprinted with permission.

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Figure 6. Overview of Components of the Situated Expectancy–Value Theory (SEVT) of Achievement Performance and Choice That Were

Studied in the Present Doctoral Thesis. The Inner Rectangle Represents the Constructs Assumed by SEVT, While the Outer Rectangle Represents the Selected Set of Constructs Included in Study I (Blue) and in Study II (Green)

Note. Adapted from “35 years of research on students’ subjective task values and motivation: A look back and a look forward” by A. Wigfield and J. S. Eccles, 2020, in A. J. Elliot, Advances in Motivation Science, Vol. 7, p. 165 (https://doi.org/10.1016/bs.adms.2019.05.002). Copyright 2020 by Elsevier. Reprinted with permission.