Heuristic thinking makes a chemist smart

Abstract

We focus on the virtually neglected use of heuristic principles in understanding and teaching of organic chemistry. As human thinking is not comparable to computer systems employing factual knowledge and algorithms--people rarely make decisions through careful considerations of every possible event and its probability, risks or usefulness--research in science and teaching must include psychological aspects of the human decision making processes. Intuitive analogical and associative reasoning and the ability to categorize unexpected findings typically demonstrated by experienced chemists should be made accessible to young learners through heuristic concepts. The psychology of cognition defines heuristics as strategies that guide human problem-solving and deciding procedures, for example with patterns, analogies, or prototypes. Since research in the field of artificial intelligence and current studies in the psychology of cognition have provided evidence for the usefulness of heuristics in discovery, the status of heuristics has grown into something useful and teachable. In this tutorial review, we present a heuristic analysis of a familiar fundamental process in organic chemistry--the cyclic six-electron case, and we show that this approach leads to a more conceptual insight in understanding, as well as in teaching and learning.

Modelling Chemical Reasoning to Predict and Invent Reactions

“…It can produce highly plausible predictions; however, the predictions are not foolproof. This is analogous to human‐generated hypotheses, for which ideas that look good on paper might turn out not to be experimentally feasible …”

“…However, we emphasise that the found paths are not a transitive law. Our model has to been seen as heuristic or as a form of inductive inference . It can produce highly plausible predictions; however, the predictions are not foolproof.…”

“…Unlike many machine-learning approaches, this makeso ur approach white-box,w hich is ad esirablef eature of artificial intelligence systems. [12] However, we emphasise that the found paths are not at ransitive law.O ur model hast ob een seen as heuristic [48] or as af orm of inductive inference. [1][2][3][4] It can produce highly plausible predictions; however,t he predictions are not foolproof.…”

Heuristic Chemistry—Elimination Reactions

“…Elimination reactions are key steps in designing large unsaturated scaffolds, for example, annulenes, cyclophanes, phenylenes, and polymers. [1,4] The manifold varieties of elimination reactions can also be reduced to small groups of reaction types that follow the same reaction principle. Just as an addition reaction combines two fragments, the elimination reaction is the reverse process.…”

Anthropogenic reaction parameters – the missing link between chemical intuition and the available chemical space

“…This intuition driven process facilitates the problem solving and the solution is generally found with a minimum of effort. Like chess masters, who recognize a good move within a wink of an eye, experts in synthetic organic chemistry are able to heuristically 35 recognize the relevant components of a chemical problem, followed by a fast analysis of possible prospects and rapidly provide a solution including which synthetic strategy, reaction conditions, catalysts or reagents should be used. In both academic and industrial settings, high-level chemistry performance is directly related to the experts' deep knowledge acquired through prolonged studies and deliberate practice.…”