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This postscript describes two specific problem-solving issues. The first highlights the need, in practice, for both higher- and lower-order thinking skills (HOTS and LOTS). Algorithms, dealing with LOTS-type problems, can often be demanding and are likely to have initially employed both HOTS and extensive practice to achieve the level of expertise required. The synergy between HOTS and LOTS is demonstrated by looking at the contribution of chemistry and biochemistry to overcoming the current coronavirus (COVID-19) pandemic, firstly by determining (in just 12 days) the structure of the SARS-CoV-2 virus, and then by the subsequent development of appropriate tests, drugs and vaccines. The second issue considers the analogy between chaos theory and problem-solving research. Chaos theory refers to states of dynamical systems where random states of disorder and irregularities are often governed by deterministic laws that are highly sensitive to the initial conditions. The Lyapunov time provides an analogy with the duration of the predictive power of problem-solving models, such as the working memory overload hypothesis. The timespan for which predictions of such models are valid is currently unknown. Future research will hopefully be able to provide the answers.

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