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This chapter outlines the challenges that research and practice in higher education have faced in measuring students' competences and learning outcomes. Particular attention is given to the systematic and institutional contexts in Germany. Based on the outlined national and international contextual framework, the Germany-wide program “Modeling and Measuring Competences in Higher Education (KoKoHs)” is discussed in terms of its two central working stages, key outcomes and lessons learned. In particular, the central results of the second phase are presented for the first time and integrated into the current state of international research. Based on this analysis, perspectives for further research on student learning in higher education and implications for practice and policy are derived.

This chapter highlights the growing body of international research into the benefits of residence abroad for foreign language students, surveying studies from the past 35 years originating in both the U.S.A. and the U.K. It examines some of the problematic issues confronting researchers in this area and shows how these issues have contributed to a paucity of studies in the area and led to a diversity in research design. It reports on longitudinal study, the first of its kind in the U.K., which examined the linguistic benefits of residence abroad for a cohort of modern language students from a leading university. This 4-year study used repeated measures proficiency testing, involving a C-test, a grammar test and a range of qualitative measures, to chart the progress made by students on 6- and 12-month study placements in Germany. Findings confirm substantial proficiency gains on both of the main measures but fail to confirm gender and length of residence abroad as predictors of progress. Results also reveal strong differential individual performance during residence abroad. The chapter concludes with recommendations for future research aimed at exploring this key finding further.

The authors propose inference methods for endogeneity parameters in linear simultaneous equation models allowing for weak identification and missing instruments. Endogeneity parameters measure the impact of unobserved variables which may be correlated with observed explanatory variables, and play a central role in determining the “bias” associated with endogeneity and measurement errors in structural equations. These results expand, in several ways, the finite-sample theory in Doko Tchatoka and Dufour (2014) for this problem. The latter theory relies on relatively restrictive assumptions, in particular the hypothesis that the reduced form is complete (e.g., contains all the relevant instruments), which is questionable in many practical situations. While the new proposed inference methods retain identification robustness, they also allow the reduced form to be incomplete, for example, due to missing instruments. The authors propose easily applicable inference methods for endogeneity parameters – in particular, two-stage procedures (similar to those in Dufour, 1990). An application to a model of returns to schooling is presented.

The Hausman test is used in applied economic work as a test of misspecification. It is most commonly thought of as a test of whether one or more explanatory variables in a regression model are endogenous. The usual Hausman contrast test requires one estimator to be efficient under the null hypothesis. If data are heteroskedastic, the least squares estimator is no longer efficient. The first option is to estimate the covariance matrix of the difference of the contrasted estimators, as suggested by Hahn, Ham, and Moon (2011). Other options for carrying out a Hausman-like test in this case include estimating an artificial regression and using robust standard errors. Alternatively, we might seek additional power by estimating the artificial regression using feasible generalized least squares. Finally, we might stack moment conditions leading to the two estimators and estimate the resulting system by GMM. We examine these options in a Monte Carlo experiment. We conclude that the test based on the procedure by Hahn, Ham, and Moon has good properties. The generalized least squares-based tests have higher size-corrected power when heteroskedasticity is detected in the DWH regression, and the heteroskedasticity is associated with a strong external IV. We do not consider the properties of the implied pretest estimator.

Luxury branding, in the context of tangible luxury consumables, has received academic attention. But the notion remained inconclusive in the context of consumption of luxury intangibles. The travel setting provides an excellent backdrop to explore the complex cognitive process of assigning meaning to the relationship between travellers and luxury travel brands. The shifting image of luxury consumption from elitism to mass aspirational, too, needs to be studied for its transformative implications. The chapter focused on developing a brand relationship scale, namely, TraveLux, in the context of luxury travel consumption and tested its robustness to explain the shared sentiments and emotions of travellers, engaged in luxury travel, across social media. The chapter identifies a four construct instruments capturing the essence of immersive experience, ethnocultural acculturation, passion and excitement and self-congruence as a seedbed of luxury brand affinity for travellers. TraveLux was also found to capture the shared experience of travellers consuming luxury travel brands, thereby establishing a synch between the instrument constructs and manifested human cognition in real-life situations. The study expanded on the volume of literature pertaining to luxury branding in the context of product-oriented industry and addresses the existing void in understanding traveller–brand relationships in luxury travel contexts. The study implicates a theoretical change in branding concept in perceiving luxury brands as price-based exclusivity to a transformative cultural experience. Further extrapolations of the study could be made by incorporating subtle behavioural patterns of travellers in perceiving luxury and subsequent evocation and predisposition towards decision-making.

This chapter examines underrepresentation among African American and Hispanic students in gifted education using the perfect storm analogy, arguing that social inequality, elitism, and colorblindness are three forces that contribute to the poor presence of these groups in gifted education. Underrepresentation trends are presented, along with methods for calculating underrepresentation and inequity. Underrepresentation is placed under the larger issues of achievement gaps, and inequitable school practices, specifically de jure segregation. Models and discussions of social inequality, elitism, and colorblindness are presented to explain that the magnitude of underrepresentation is beyond statistical chance and a function of decision makers’ attitudes and beliefs grounded in deficit paradigms. The primary theses and admonitions are that gifted education underrepresentation is counterproductive in such a culturally different nation, and that desegregating gifted education is nonnegotiable. Suggestions for desegregating gifted education and eliminating inequities are provided.

The construct of cultural intelligence has recently been introduced to the management literature as an individual difference that may predict effectiveness and a variety of interpersonal behavior in the global business environment. This construct has enormous potential in helping to explain effectiveness in cross-cultural interactions. However, progress has been limited by the adequacy of existing measures. In this chapter, we describe the development and preliminary validation of a web-based assessment of cultural intelligence based on our conceptualization of cultural intelligence.