In my opinion, starting from the objective law of the development of things, according to the principle of human selection and the needs of the measurement task, selecting the appropriate measurement accuracy, through simplification or assimilation, approximation or approximation, mapping or projection and other physical-mathematical means, and ultimately the statistical processing with linear algebra or addition and subtraction can be regarded as the correct computational thinking.
For example, measuring a coastline to the SI system of meters at the most, usually to the kilometer is sufficient. To be precise to the millimeter, micron, nanometer, picometer, or femtometer, i.e., the more precise, the more absurd.
For example, measuring economic dynamics, if based on a small number of samples, the more precise, the more absurd, because measurements are personality traits. Only with a sufficient sample, and with big data statistics, can a more credible estimate be produced.
Calculation = measurement + statistics, in addition to considering the random error, in particular, to consider a number of factors of systematic error, such as: the quality of personnel, the performance of equipment, the quality of materials, the rationality of the method, the influence of the environment.
Reasonable is the premise of calculation, concise is the core of calculation. Gravitational field equations that are inherently irrational and so cumbersome as to be impossible to calculate are clearly not proper computational thinking. The Newtonian dynamical system is concise and clear, and is proper computational thinking. Computer principles as simple as 0 and 1 are the greatest computational thinking.