Epistemological Attitudes Towards Sources of Knowledge Semantic Questionnaire

Given the everlasting significance of knowledge in society and academia,this article proposes a theoretical and methodological perspective on conceptualizing and investigating it.Specifically,it aims to explore the epistemological attitude(EA)theory and its semantic approach to assessing sources of knowledge.The article provides a concise overview of the EA theory,which advocates for a systemic perspective on cognition and knowledge.It introduces and elaborates on the core concept and model,which serve as the foundation for the proposed methodology.This methodology suggests examining knowledge objects through subjective,contextual,and epistemological realms as multi-level knowledge constructs.Emphasizing the importance of semantics in studying knowledge,categories,and meanings,the article proposes an epistemological attitude towards sources of knowledge semantic questionnaire.The article delves into the methodology,reflecting on its four consecutive stages.It begins with the formal and substantive stages,which involve selecting sources,choosing academic experts as target participants,and developing content.The procedural stage follows,in which an expert review approach is employed to assess the content validity of the method.Finally,the article discusses the semantic method,elucidating its structure,features,semantic categories,and assessment procedure.The proposed method provides a unique contribution by enabling the analysis of the epistemological and socio-psychological meanings of sources,representing them as semantic constructs.

Does a Country/Region's Economic Status Affect Its Universities' Presence in International Rankings?

Purpose: Study how economic parameters affect positions in the Academic Ranking of World Universities' top 500 published by the Shanghai Jiao Tong University Graduate School of Education in countries/regions with listed higher education institutions. Design/methodology/approach: The methodology used capitalises on the multi-variate characteristics of the data analysed. The multi-colinearity problem posed is solved by running principal components prior to regression analysis, using both classical(OLS) and robust(Huber and Tukey) methods. Findings: Our results revealed that countries/regions with long ranking traditions are highly competitive. Findings also showed that some countries/regions such as Germany, United Kingdom, Canada, and Italy, had a larger number of universities in the top positions than predicted by the regression model. In contrast, for Japan, a country where social and economic performance is high, the number of ARWU universities projected by the model was much larger than the actual figure. In much the same vein, countries/regions that invest heavily in education, such as Japan and Denmark, had lower than expected results.Research limitations: Using data from only one ranking is a limitation of this study, but the methodology used could be useful to other global rankings. Practical implications: The results provide good insights for policy makers. They indicate the existence of a relationship between research output and the number of universities per million inhabitants. Countries/regions, which have historically prioritised higher education, exhibited highest values for indicators that compose the rankings methodology; furthermore,minimum increase in welfare indicators could exhibited significant rises in the presence of their universities on the rankings.Originality/value: This study is well defined and the result answers important questions about characteristics of countries/regions and their higher education system.