New focus on basic research in China's advancement in science and technology

On 1 January 2022,a new version of the Law on China's Science and Technology(S&T)Advancement('科学技术进步法')went into effect.This is the second revision of the Law,w...     

Innovation and reform: China's 14th Five-Year Plan unfolds

The Chinese government has recently announced a compre-hensive proposal of the 14th Five-Year Plan for the next phase of development in all sectors of Chinese s...     

An analysis of mobility in global rankings: making institutional strategic plans and positioning for building world-class universities

Since the start of the twenty-first century, university rankings have become internationalized. Global rankings have a variety of uses, levels of popularity and rationales and they are here to stay. An examination of the results of the current global ranking reveals that well-reputed world-class universities are amongst the top ranked ones. A major concern for university administrators in many parts of the world is how to use the global rankings wisely in their mid-term and long-term strategic planning for building their institutions into world-class universities. Four major global rankings have been developed: the Academic Ranking of World Universities, the World University Rankings, the Webometrics Ranking of World Universities and the Performance Ranking of Scientific Papers for World Universities. The main purpose of this paper is to explore the most influential indicators in these global university rankings that will affect the rank mobility of an institution. Based on an analysis of correlation coefficients and K-means clustering, a model of strategic institutional planning for building a world-class university is proposed.     

Turning Crisis into Opportunity: Nature of Science and Scientific Inquiry as Illustrated in the Scientific Research on Severe Acute Respiratory Syndrome

Interviews with key scientists who had conducted research on Severe Acute Respiratory Syndrome (SARS), together with analysis of media reports, documentaries and other literature published during and after the SARS epidemic, revealed many interesting aspects of the nature of science (NOS) and scientific inquiry in contemporary scientific research in the rapidly growing field of molecular biology. The story of SARS illustrates vividly some NOS features advocated in the school science curriculum, including the tentative nature of scientific knowledge, theory-laden observation and interpretation, multiplicity of approaches adopted in scientific inquiry, the inter-relationship between science and technology, and the nexus of science, politics, social and cultural practices. The story also provided some insights into a number of NOS features less emphasised in the school curriculum—for example, the need to combine and coordinate expertise in a number of scientific fields, the intense competition between research groups (suspended during the SARS crisis), the significance of affective issues relating to intellectual honesty and the courage to challenge authority, the pressure of funding issues on the conduct of research and the ‘peace of mind’ of researchers, These less emphasised elements provided empirical evidence that NOS knowledge, like scientific knowledge itself, changes over time. They reflected the need for teachers and curriculum planners to revisit and reconsider whether the features of NOS currently included in the school science curriculum are fully reflective of the practice of science in the 21st century. In this paper, we also report on how we made use of extracts from the news reports and documentaries on SARS, together with episodes from the scientists’ interviews, to develop a multimedia instructional package for explicitly teaching the prominent features of NOS and scientific inquiry identified in the SARS research.

Evaluating the Selection of Normal-Theory Weight Matrices in the Satorra–Bentler Correction of Chi-Square and Standard Errors

In the application of the Satorra–Bentler scaling correction, the choices of normal-theory weight matrices (i.e., the model-predicted vs. the sample covariance matrix) in the calculation of the correction remains unclear. Different software programs use different matrices by default. This simulation study investigates the discrepancies due to the weight matrices in the robust chi-square statistics, standard errors, and chi-square-based model fit indexes. This study varies the sample sizes at 100, 200, 500, and 1,000; kurtoses at 0, 7, and 21; and degrees of model misspecification, measured by the population root mean square error of approximation (RMSEA), at 0, .03, .05, .08, .10, and .15. The results favor the use of the model-predicted covariance matrix because it results in less false rejection rates under the correctly specified model, as well as more accurate standard errors across all conditions. For the sample-corrected robust RMSEA, comparative fit index (CFI) and Tucker–Lewis index (TLI), 2 matrices result in negligible differences.