Design rationale is the justification behind a product component, often captured via written reports and oral presentations. Research shows that the structure and information used to communicate and document rationale significantly influence human behavior. To better understand the influence of design rationale on engineering design, we investigate the information engineers and designers include in design rationales in written reports. Eight hundred and forty-six pages of student engineering design reports from 28 teams representing 116 individuals were analyzed using a mixed-methods approach and compared across project types. The rationales from the reports were coded inductively into concepts and later applied to five industry reports consisting of 218 pages. The findings reveal a spectrum of rationales underpinning design decisions. Grounded in the data, the feature, specification and evidence (FSE) framework emerged as a feature-based and low-effort capture approach. We discuss the need to improve design communication in engineering design, through structuring rationales (i.e., using the proposed FSE framework or other representations) and improving technical writing skills. Lastly, by enhancing design rationale communication and documentation practices, significant benefits can be realized for computational support tools such as automatic rationale extraction or generative approaches.

When we're inquiring to find out whether p is true, knowing that we'll get better evidence in the future seems like a good reason to suspend judgment about p now. But, as Matt McGrath has recently argued, this natural thought is in deep tension with traditional accounts of justification. On traditional views of justification, which doxastic attitude you are justified in having now depends on your current evidence, not on what you might learn later. McGrath proposes to resolve this tension by distinguishing between different ways of having a neutral attitude. I argue that McGrath's account is unable to account for the full range of cases in which an agnostic attitude is warranted. We can remedy this by pairing his account with my theory of transitional and terminal attitudes, which claims that attitudes are justified in different ways depending on whether they are formed in intermediate stages of deliberation or as conclusions of deliberation. I compare my view with an alternative, more parsimonious one, according to which deliberation itself is a source of new evidence. I argue that this alternative proposal is faced with a dilemma: it either generates a vicious regress, or it fails to capture the relevant cases.

Our experience of reasoning is replete with conflict. People phenomenologically vacillate between options when confronted with challenging decisions. Existing experimental designs typically measure a summary of the experience of the conflict experienced throughout the choice process for any individual choice or even between multiple observers for a choice. We propose a new method for measuring vacillations in reasoning during the time-course of individual choices, utilizing them as a fine-grained indicator of cognitive conflict. Our experimental paradigm allows participants to report the alternative they were considering while deliberating. Through 3 experiments, we demonstrate that our measure correlates with existing summary judgments of conflict and confidence in moral and logical reasoning problems. The pattern of deliberation revealed by these vacillations produces new constraints for theoretical models of moral and syllogistic reasoning.

According to Action-First theorists, like Jonathan Dancy, reasons for action explain reasons for intentions. According to Intention-First theorists, like Conor McHugh and Jonathan Way, reasons for intentions explain reasons for action. In this paper, I introduce and defend a version of the Action-First theory called “Instrumentalism.” According to Instrumentalism, just as we can derive, using principles of instrumental transmission, reasons to ψ from reasons to ϕ (provided there’s some relevant instrumental relation between ψ-ing and ϕ-ing), we can derive reasons to intend to ϕ from reasons to ϕ (provided there’s some relevant instrumental relation between intending to ϕ and ϕ-ing). After providing some defense of Instrumentalism, I turn to two recent, important arguments for the Intention-First theory advanced by McHugh and Way, and I argue that neither of them succeed. I conclude that we should reject the Intention-First theory and that we have grounds for optimism about the Action-First theory.

A peculiar feature of our species is that we settle what to believe, value, and do by reasoning through narratives. A narrative is adiachronic, information-rich story that contains persons, objects, and at least one event. When we reason through narrative, we usenarrative to settle what to do, to make predictions, to guide normative expectations, and to ground which reactive attitudes we think areappropriate in a situation. Narratives explain, justify, and provide understanding. Narratives play a ubiquitous role in human reasoning. Andyet, narratives do not seem up to the task. Narratives are often unmoored representations (either because they are do not purport to referto the actual world, or because they are grossly oversimplified, or because are known to be literally false). Against this, I argue thatnarratives guide our reasoning by shaping our grasp of modal structure: what is possible, probable, plausible, permissible, required,relevant, desirable and good. Narratives are good guides to reasoning when they guide us to accurate judgments about modal space. Icall this the modal model of narrative. In this paper, I develop an account of how narratives function in reasoning, as well as an account ofwhen reasoning through narrative counts as good reasoning.

Influential ‘fast-and-slow’ dual process models suggest that sound reasoning requires the correction of fast, intuitive thought processes by slower, controlled deliberation. Recent findings with high-level reasoning tasks started to question this characterization. Here we tested the generalizability of these findings to low-level cognitive control tasks. More specifically, we examined whether people who responded accurately to the classic Stroop and Flanker tasks could also do so when their deliberate control was minimized. A two-response paradigm, in which people were required to give an initial ‘fast’ response under time–pressure and cognitive load, allowed us to identify the presumed intuitive answer that preceded the final ‘slow’ response given after deliberation. Across our studies, we consistently find that correct final Stroop and Flanker responses are often non-corrective in nature. Good performance in cognitive control tasks seems to be driven by accurate ‘fast’ intuitive processing, rather than by ‘slow’ controlled correction of these intuitions. We also explore the association between Stroop and reasoning performance and discuss implications for the dual process view of human cognition.

We present an abstract model of rationality that focuses on structural properties of attitudes. Rationality requires coherence between your attitudes, such as your beliefs, values and intentions. We define three ‘logical’ conditions on attitudes: consistency, completeness and closedness. They parallel the familiar logical conditions on beliefs, but contrast with standard rationality conditions such as preference transitivity. We establish a formal correspondence between our logical conditions and standard rationality conditions. Addressing John Broome’s programme ‘rationality through reasoning’, we formally characterize how you can (not) become more logical by reasoning. Our analysis connects rationality with logic, and enables logical talk about multi-attitude psychology.

We claim that understanding human decisions requires that both automatic and deliberate processes be considered. First, we sketch the qualitative differences between two hypothetical processing systems, an automatic and a deliberate system. Second, we show the potential that connectionism offers for modeling processes of decision making and discuss some empirical evidence. Specifically, we posit that the integration of information and the application of a selection rule are governed by the automatic system. The deliberate system is assumed to be responsible for information search, inferences and the modification of the network that the automatic processes act on. Third, we critically evaluate the multiple-strategy approach to decision making. We introduce the basic assumption of an integrative approach stating that individuals apply an all-purpose rule for decisions but use different strategies for information search. Fourth, we develop a connectionist framework that explains the interaction between automatic and deliberate processes and is able to account for choices both at the option and at the strategy level.