A literature review of expert problem solving using analogy

We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of non-trivial problems. We identified twelve studies. These studies suggest that analogical reasoning plays an important role in problem solving, but that CBR tools do not model this in a biologically plausible way. For example, the ability to induce structure and therefore find deeper analogies is widely seen as the hallmark of an expert. However, CBR tools fail to provide support for this type of reasoning for prediction. We conclude this mismatch between experts’ cognitive processes and software tools contributes to the erratic performance of analogy-based prediction

Analogical Predictions

This paper deals with exchangeable analogical predictions,\ud and proposes a Bayesian model for such predictions.\ud The paper first discerns two kinds of analogical\ud predictions, based on similarity of individuals and of types\ud respectively. It then introduces a Bayesian framework that\ud employs hypotheses for making predictions. This framework\ud is used to describe predictions based on the similarity\ud of individuals, and further relates exchangeable predictions\ud with a specific partition of hypotheses on types. Exchangeable\ud predictions based on type similarity are determined by\ud prior probabilities over the partition, but the partition obstructs\ud the control over the similarity relations. Finally the\ud paper develops a model for exchangeable predictions\ud based on type similarity, which employs hypotheses on\ud similarity between individuals, thereby offering a better\ud control over the similarity relations

Motion as manipulation: Implementation of motion and force analogies by event-file binding and action planning\ud

Tool improvisation analogies are a special case of motion and force analogies that appear to be implemented pre-conceptually, in many species, by event-file binding and action planning. A detailed reconstruction of the analogical reasoning steps involved in Rutherford's and Bohr's development of the first quantized-orbit model of atomic structure is used to show that human motion and force analogies generally can be implemented by the event-file binding and action planning mechanism. Predictions that distinguish this model from competing concept-level models of analogy are discussed, available data pertaining to them are reviewed, and further experimental tests are proposed

Effect of Scaffolding on Helping Introductory Physics Students Solve Quantitative Problems Involving Strong Alternative Conceptions

It is well-known that introductory physics students often have alternative conceptions that are inconsistent with established physical principles and concepts. Invoking alternative conceptions in quantitative problem-solving process can derail the entire process. In order to help students solve quantitative problems involving strong alternative conceptions correctly, appropriate scaffolding support can be helpful. The goal of this study is to examine how different scaffolding supports involving analogical problem solving influence introductory physics students' performance on a target quantitative problem in a situation where many students' solution process is derailed due to alternative conceptions. Three different scaffolding supports were designed and implemented in calculus-based and algebra-based introductory physics courses to evaluate the level of scaffolding needed to help students learn from an analogical problem that is similar in the underlying principles but for which the problem solving process is not derailed by alternative conceptions. We found that for the quantitative problem involving strong alternative conceptions, simply guiding students to work through the solution of the analogical problem first was not enough to help most students discern the similarity between the two problems. However, if additional scaffolding supports that directly helped students examine and repair their knowledge elements involving alternative conceptions were provided, students were more likely to discern the underlying similarities between the problems and avoid getting derailed by alternative conceptions when solving the targeted problem. We also found that some scaffolding supports were more effective in the calculus-based course than in the algebra-based course. This finding emphasizes the fact that appropriate scaffolding support must be determined via research in order to be effective

Modeling human-like morphological prediction

We test a model of morphological prediction based on analogical deduction using phonemic similarity by applying it to German plural suffix prediction for a set of 24 nonce forms for which McCurdy et al. (2020) elicited human judgements, and which they found were poorly matched by productions of an encoder-decoder model of Kirov and Cotterell (2018). Their results raise the question of what kinds of models best mirror human judgements. We show that the predictions of the analogical models we tested mirror human judgements better than the encoder-decoder model

Discourse metaphors: the link between figurative language and habitual analogies

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Design thinking support: information systems versus reasoning

Numerous attempts have been made to conceive and implement appropriate information systems to support architectural designers in their creative design thinking processes. These information systems aim at providing support in very diverse ways: enabling designers to make diverse kinds of visual representations of a design, enabling them to make complex calculations and simulations which take into account numerous relevant parameters in the design context, providing them with loads of information and knowledge from all over the world, and so forth. Notwithstanding the continued efforts to develop these information systems, they still fail to provide essential support in the core creative activities of architectural designers. In order to understand why an appropriately effective support from information systems is so hard to realize, we started to look into the nature of design thinking and on how reasoning processes are at play in this design thinking. This investigation suggests that creative designing rests on a cyclic combination of abductive, deductive and inductive reasoning processes. Because traditional information systems typically target only one of these reasoning processes at a time, this could explain the limited applicability and usefulness of these systems. As research in information technology is increasingly targeting the combination of these reasoning modes, improvements may be within reach for design thinking support by information systems