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Home arrow Education arrow Evaluating Collaboration Networks in Higher Education Research: Drivers of Excellence
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Excellence Research Performance Framework

Performance is a dependent variable in most of the research systems management (Geisler, 2005). According to this assumption, we argue that it is necessary to take action in order to improve research performance. So, our question is this: how research monitoring and research evaluation can be improved to support excellence performance?

To provide a comprehensive and complete picture of our conceptual argumentation, we build a research performance framework (Fig. 1.2).

Research performance framework. (Source

Fig. 1.2 Research performance framework. (Source: The authors, 2016)

Radosevic and Yoruk (2014, p. 18) drew attention to “the capacity to absorb knowledge generated at dynamic areas of the S&T frontier matters more than the capacity to generate new knowledge in stagnant areas of scientific frontier.” They argue that the “remarkable rise of Asia Pacific and relatively Latin America in both papers and citations is not accompanied by improvements in the relative impact which has remained almost unchanged for the last 30 years” (Radosevic and Yoruk, 2014, p. 11). For emergent economies to reach leadership positions, they should be concerned not only by increasing production but also by relevant scientific knowledge of the social and economic growth.

We defend also that development of international connections and international collaboration is crucial to achieving excellence in science dynamics. Sharing knowledge and building new knowledge with international partnerships facilitate knowledge dissemination and knowledge production. We need elaborate markers, qualitative and quantitative indicators, for the evaluation of research networks (Leite et al., 2014a). By seeking consistent alignment with multidimensional factors, it is possible to develop excellence at all levels (micro, meso, and macro levels; individuals, teams, networks, institutions, and countries). Measuring research performance across all those levels is a key driver for improving knowledge production.

In the next chapter, we will reflect on the achievements and possibilities of science dissemination, which does not have the same understanding in the scientific academic communities around the world. In emerging countries, there is limited access to publications and there are difficulties in publishing in English. At the global level, non-English articles are subvalorized and this is a universal knowledge lost. As we all agree, knowledge is our greatest resource, our common good. By examining our own research practices, we will show how difficult it is to be included in the international scientific community.

Note

1. Social sciences (social-sciences-general and economics and business), fundamental sciences (chemistry, geosciences, mathematics, and physics), applied sciences (computer science, engineering, materials science, and space science), and life sciences (the remaining fields). About 21 categories of broad fields in science and social sciences are listed by Thomson Reuters.

 
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