Table 1 Scientific knowledge dimensions

Content knowledge

Physics:

Motion and forces (e.g. velocity, friction) and action at a distance (e.g. magnetic, gravitational and electrostatic forces)

Energy and its transformation (e.g. conservation, dissipation)

Interactions between energy and matter (e.g. light and radio waves, sound and seismic waves)

Chemistry:

Structure and properties of matter (e.g. particle model, bonds,,changes of state, thermal and electrical conductivity)

Chemical changes (e.g. chemical reactions, energy transfer in chemical reaction)

Energy and its transformation (e.g. chemical reactions)

Biology:

Cells (e.g. structures and function, DNA, plant and animal)

The concept of an organism (e.g. unicellular and multicellular)

Humans (e.g. health, nutrition, subsystems such as digestion, respiration, circulation, excretion,reproduction and their relationship)

Populations (e.g. species, evolution, biodiversity, genetic variation)

Ecosystems (e.g. food chains, matter and energy flow)

Biosphere (e.g. ecosystem services, sustainability)

Geography:

Structures of the Earth systems (e.g. lithosphere, atmosphere, hydrosphere)

Energy in the Earth systems (e.g. sources, global climate)

Change in Earth systems (e.g. plate tectonics, geochemical cycles, constructive and destructive forces)

Earth’s history (e.g. fossils, origin and evolution)

Earth in space (e.g. gravity, solar systems, galaxies)

The history and scale of the universe and its history (e.g. light year, Big Bang theory)

Procedure knowledge

The concept of variables, including dependent, independent and control variables

Concepts of measurement, e.g. quantitative (measurements), qualitative (observations), the use of a scale, categorical and continuous variables

Ways of assessing and eneraliza uncertainty, such as repeating and averaging measurements

Mechanisms to ensure the replicability (closeness of agreement between repeated measures of the same quantity) and accuracy of data (the closeness of agreement between a measured quantity and a true value of the measure)

Common ways of abstracting and representing data using tables, graphs and charts, and using them appropriately

The control-of-variables strategy and its role in experimental design or the use of eneraliza controlled trials to avoid confounded findings and identify possible causal mechanisms

The nature of an appropriate design for a given scientific question, e.g. experimental, field-based or pattern-seeking

Epistemic knowledge

The constructs and defining features of science. That is:

The nature of scientific observations, facts, hypotheses, models and theories

The purpose and goals of science (to produce explanations of the natural world) as distinguished from technology (to produce an optimal solution to human need), and what constitutes a scientific or technological question and appropriate data

The values of science, e.g. a commitment to publication, objectivity and the elimination of bias

The nature of reasoning used in science, e.g. deductive, inductive, inference to the best explanation (abductive), analogical, and model-based

The role of these constructs and features in justifying the knowledge produced by science. That is:

How scientific claims are supported by data and reasoning in science

The function of different forms of empirical enquiry in establishing knowledge, their goal (to test explanatory hypotheses or identify patterns) and their design (observation, controlled experiments, correlational studies)

How measurement error affects the degree of confidence in scientific knowledge

The use and role of physical, system and abstract models and their limits

The role of collaboration and critique, and how peer review helps to establish confidence in scientific claims

The role of scientific knowledge, along with other forms of knowledge, in identifying and addressing societal and technological issues