How concentrated are shining skills in particular disciplines or practices?

This set of column charts represents how each term is distributed across 34 research disciplines.

For each term, the disciplines are ordered from that referring to it most, to that referring to it least. Consequently, that ordering of disciplines is unique to each term (as illustrated in this additional data). For example, critical thinking falls away rapidly from its first discipline, compared to systems thinking.

The raw document count shows the number of documents using each term in each discipline (somewhere in their full text) over a recent five-year period (2020-2024). The proportions data shows the concentration of each term in each discipline (as a percentage of all publications in that discipline). The normalised data sets the concentration level to 1 for the first discipline, so the way that concentration falls away can be compared across terms. Critical thinking dominates these first two views, so selecting specific terms of interest permits better comparisons in those views.

The column charts illustrate the distribution of thinking skills across disciplines, but we can also examine the distribution across application areas, such as the UN's Sustainable Development Goals (SDGs):

This heatmap represents the relative prevalence of each term in documents associated with the 17 SDGs.

The raw document counts report how many of the documents associated with each SDG use each term in their full text over a recent five-year period (2020-2024). The intersection of critical thinking and SDG 4 ("Quality Education") dominates in this view. Normalising the data per SDG reveals which terms are most prevalent for each SDG (e.g. critical thinking and systems thinking). Normalising per skill reveals which SDGs are most prevalent for each term (e.g. SDG 4 and SDG 3: "Good Health and Well Being").

Having considered the distribution of terms over disciplines and SDGs separately, we might ask how those distributions are related:

This scatter plot (or bubble chart) represents the prevalence of each term and how concentrated or distributed those terms are.

For both the disciplines and the SDGs, the spread of each term across multiple categories was measured by determining a single value: 1 minus the Gini coefficient (of concentrations), labelled here as "1-Gini." Lower values indicate concentration in only a few categories; higher values indicate a more even distribution across multiple categories.

Note that systems thinking is quite evenly distributed across multiple disciplines and multiple SDGs (which can be confirmed by examining the first two plots on this page). In contrast, computational thinking is highly concentrated in a small number of disciplines and SDGs. To reduce clutter on the plot, it can be useful to filter out terms of less interest, such as only viewing those terms ranked in the top 10 (according to title-abstract prevalence between 2020-2024, which is the basis of the bubble scaling).

The data presented on this page are more fully reported in a bibliometric analysis, the details of which can be found on the About page.