Articles

We found that: (1) Attention to SET originated in the US in the 1970s, spreading to German-speaking countries in the mid-1990s and continuing in China and Latin America in the early 2000s. (2) SET is commonly viewed as a control tool deserving methodological improvement, while bias is debated in the US. We also found local trajectories: (3) Whereas in the US and Latin America SET is primarily seen as a management tool, German-speaking and Chinese authors reflect more on improving teaching. Chinese scholars consider SET a valid instrument for state control associated with artificial intelligence. Also, (4) SET is commonly used in medical education in the US and the German-speaking region and in physical education in China.

Repeated calls for responsible research metrics and professional codes of conduct in evaluative bibliometrics highlight the need to investigate which qualifications and competencies enable a proficient application of bibliometric methods and indicators. Taking competence research as a point of departure, this chapter delineates salient dimensions of professional competence in bibliometric research evaluation by reviewing a selected subset of the literature. The reviewed literature focuses on handbooks, monographs, and scholarly and practitioner articles that introduce theory and methodology of bibliometrics and showcase applications to scholars and practitioners mainly outside of the scientometric research community.

This Intelligence Brief takes a closer look at students’ health. Compared to the overall population of the same age, students less often perceive their health as good or very good. Logistic regression analyses with German student data show strong and negative relations between financial difficulties and students’ health perception. Additionally, a cross-country comparison with EUROSTUDENT data consistently shows comparatively large shares of impaired students among those with financial difficulties. The findings indicate that policy makers should pay special attention to both impaired and financially challenged students in order to ensure their successful higher education participation and prevent negative societal effects of poor health.

We conduct an independent cluster validation study on published clustering solutions of a research testbed corpus, the Astro dataset of publication records from astronomy and astrophysics. We extend the dataset by collecting external validation data serving as proxies for the latent structure of the corpus. Specifically, we collect (1) grant funding information related to the publications, (2) data on topical special issues, (3) on specific journals’ internal topic classifications and (4) usage data from the main online bibliographic database of the discipline. The latter three types of data are newly introduced for the purpose of clustering validation and the rationale for using them for this task is set out.