Difference between revisions of "Introduction"

*'''''<math>P-value</math>''''':   In medicine, for example, to confirm an experiment or validate a series of data collected through laboratory instruments or surveys, reliance is placed on "Statistical Inference," and in particular on a well-known value called "significance test" (P-value). However, even this concept, now rooted in the practice of researchers, is being questioned. A recent study has focused attention on a campaign conducted in the journal "Nature" against the use of the "significance test."<ref>{{cita libro  

  }} Mar;567(7748):305-307.</ref> With over 800 signatories, including eminent scientists, this campaign can be seen as an important turning point and a "Silent Revolution" in the field of statistics, touching logical and epistemological aspects.<ref>{{cita libro  

  }} Jan;65(1):1-12.</ref><ref>{{cita libro  

  }}</ref> The critique is aimed at overly simplified statistical analyses, still present in numerous publications. This has stimulated a debate, sponsored by the American Statistical Association, which led to the creation of a special issue of "The American Statistician Association" titled "Statistical Inference in the 21st Century: A World Beyond p < 0.05", containing 43 articles by statisticians looking towards the future[16]. This special issue proposes new ways to communicate the significance of research findings beyond the arbitrary threshold of a P-value and offers guidelines for research that accepts uncertainty, is reflective, open, and modest in claims.<ref name="wasser">{{cita libro  

  }} 73, 1–19. </ref> The future will reveal whether these attempts to provide more solid statistical support to science, beyond traditional significance tests, will find resonance in future publications.<ref>{{cita libro  

  }} Aug 13;10:1866.</ref> This evolution aligns with Kuhn's concept of scientific progress, reflecting a reworking of some descriptive statistical content within the discipline.

* '''Interdisciplinarity''': <br>In the field of science policy, it is universally recognized that solving science-based problems requires an interdisciplinary research approach (IDR), as highlighted by the European Union's Horizon 2020 project.<ref>European Union, ''[https://ec.europa.eu/programmes/horizon2020/en/h2020-section/societal-challenges Horizon 2020]''</ref> Recent studies have explored the reasons for the cognitive and epistemic difficulties that researchers encounter in conducting IDR. One identified cause is the decline of philosophical interest towards the epistemology of IDR, attributed to the dominant "Physical Paradigm of Science." This paradigm limits the recognition of significant developments in IDR, both in the context of the philosophy of science and in the practice of research itself. In response, an alternative philosophical paradigm has been proposed, called the "Engineering Paradigm of Science," which offers alternative philosophical perspectives on fundamental aspects such as the purpose of science, the nature of knowledge, the epistemic and pragmatic criteria for the acceptance of knowledge, and the role of technological tools. Consequently, it highlights the need for researchers to make use of metacognitive support structures, called metacognitive scaffolds, to facilitate the analysis and reconstruction of the processes by which knowledge is constructed across different disciplines. In the context of IDR, such metacognitive scaffolds are essential for promoting effective communication between disciplines, allowing scholars to analyze and articulate how each discipline contributes to the construction of knowledge.<ref name=":0">{{cita libro