In the Interactive Alignment Theory, alignment is promoted by dialogic features on a dialogue-monologue continuum. More alignment in prototypical dialogue (a chat among friends) than in prototypical monologue (a lecture) seems plausible, but the role of other dialogic features for alignment is less clear. The current study tests the joint influence of two such features: communicative intent and a live interlocutor. Four structural priming experiments contrasted the magnitude of structural alignment between a dialogue situation that involved a joint task and an otherwise identical monologue situation that lacked a communicative component. None of the four experiments showed any statistical differences in alignment between dialogue and monologue. Post-hoc analyses on the pooled data of Experiments 2–4 further suggested that individual differences in attention (operationalized through reaction time variability in the picture verification component of the task we used to elicit alignment) might modulate overall structural alignment, and that dialogue (presumably through sustaining attention) might be able to sustain alignment over time to a greater extent than monologue. These results suggest a role for attention in supporting structural alignment, but the lack of clear differences between alignment magnitudes in monologue and dialogue (absent in individual experiments and weak even in the pooled analyses) suggests that communicative intent and a physically-present interlocutor have at best a minor role in promoting alignment.

A basic question for the study of the mental lexicon is whether there are morphological representations and processes that are independent of phonology and semantics. According to a prominent tradition, morphological relatedness requires semantic transparency: semantically transparent words are related in meaning to their stems, while semantically opaque words are not. This study examines the question of morphological relatedness using intra-modal auditory priming by Dutch prefixed verbs. The key conditions involve semantically transparent prefixed primes (e.g., aanbieden ‘offer’, with the stem bieden, also ‘offer’) and opaque primes (e.g., verbieden ‘forbid’). Results show robust facilitation for both transparent and opaque pairs; phonological (Experiment 1) and semantic (Experiment 2) controls rule out the possibility that these other types of relatedness are responsible for the observed priming effects. The finding of facilitation with opaque primes suggests that morphological processing is independent of semantic and phonological representations. Accordingly, the results are incompatible with theories that make semantic overlap a necessary condition for relatedness, and favor theories in which words may be related in ways that do not require shared meaning. The general discussion considers several specific proposals along these lines, and compares and contrasts questions about morphological relatedness of the type found here with the different but related question of whether there is morphological decomposition of complex forms or not.

Factorial experiments in research on memory, language, and in other areas are often analyzed using analysis of variance (ANOVA). However, for effects with more than one numerator degrees of freedom, e.g., for experimental factors with more than two levels, the ANOVA omnibus F-test is not informative about the source of a main effect or interaction. Because researchers typically have specific hypotheses about which condition means differ from each other, a priori contrasts (i.e., comparisons planned before the sample means are known) between specific conditions or combinations of conditions are the appropriate way to represent such hypotheses in the statistical model. Many researchers have pointed out that contrasts should be “tested instead of, rather than as a supplement to, the ordinary ‘omnibus’ F test” (Hays, 1973, p. 601). In this tutorial, we explain the mathematics underlying different kinds of contrasts (i.e., treatment, sum, repeated, polynomial, custom, nested, interaction contrasts), discuss their properties, and demonstrate how they are applied in the R System for Statistical Computing (R Core Team, 2018). In this context, we explain the generalized inverse which is needed to compute the coefficients for contrasts that test hypotheses that are not covered by the default set of contrasts. A detailed understanding of contrast coding is crucial for successful and correct specification in linear models (including linear mixed models). Contrasts defined a priori yield far more useful confirmatory tests of experimental hypotheses than standard omnibus F-tests. Reproducible code is available from https://osf.io/7ukf6/.

Speakers tend to lengthen the durations of words when a phonologically overlapping word has recently been produced. Although there are multiple accounts of why lengthening occurs, all of these accounts generally assume that competition at some point in the production-comprehension process leads to lengthening. We investigated the contexts that lead to competition and consequent lengthening of target word duration. In three experiments, we manipulated the contexts in which a target word was produced. Speakers produced simple descriptions of animations involving referents that shared initial phonology with another potential referent (e.g., hat and hand). In Experiments 1 and 2, we manipulated whether the related referent (i.e. hat) was named by the speaker themselves, by another person, or was unmentioned. Experiment 2 additionally made speakers aware of competitors in the environment. In both experiments, we found that lengthening does not occur whenever there are two referents in the display that could be confused, even when it is clear that they are confusable. Instead, speakers only lengthened target words when the speaker or another person had named the phonologically related word out loud. Experiment 3 tested whether the task relevance of a phonological competitor influenced naming and found that speakers lengthen words that overlap with previously produced words, even when they were no longer competitors in the display. We propose that an auditory memory account best explains these results and discuss the implications of these findings for other accounts of lengthening.

Cognitive mechanisms underlying the limited transfer effects of working memory (WM) training remain poorly understood. We tested in detail the Strategy Mediation hypothesis, according to which WM training generates task-specific strategies that facilitate performance on the trained task and its untrained variants. This large-scale pre-registered randomized controlled trial (n = 258) used a 4-week adaptive WM training with a single digit n-back task. Strategy use was probed with open-ended strategy reports. We employed a Strategy training group (n = 73) receiving external strategy instruction, a Traditional training group (n = 118) practicing without strategy instruction, and Passive controls (n = 67). Both training groups showed emerging transfer to untrained n-back task variants already at intermediate test after 3 training sessions, extending to all untrained n-back task variants at posttest after 12 training sessions. The Strategy training group outperformed the Traditional training group only at the beginning of training, indicating short-lived strategy manipulation effects. Importantly, in the Traditional training group, strategy evolvement modulated the gains in the trained and untrained n-back tasks, supporting the Strategy Mediation hypothesis. Our results concur with the view of WM training as cognitive skill learning.

Communication in face-to-face human interaction entails complying with social and moral norms about knowledge possession and transfer, and violations of these norms are sanctionable offenses. Underestimating an addressee’s knowledge can be tantamount to an insult, especially in domains over which they have superior epistemic authority. This paper examines cases where parties are in explicit disagreement about both the content of an utterance and relative authority over the knowledge in that domain. In three studies, participants judged the relative acceptability of disagreement across different knowledge domains and across conditions in which the disagreeing parties had various social relationships and/or differing levels of expertise. The acceptability of disagreement systematically differed across knowledge domains, suggesting there is gradient texture to ‘epistemic territory’. The results also suggest that social distance and relative epistemic authority independently modulate the perceived acceptability of disagreement, as do the relative time and effort spent on knowledge acquisition.

There has been a longstanding debate concerning whether interference in recognition memory is attributable to other items on the study list (i.e., item-noise) or to prior memories (i.e., context-noise and background-noise). Recently, Osth and Dennis (2015) devised a global matching model that could estimate the magnitude of each interference contribution and they found that context-noise and background-noise were dominant in recognition. In the present investigation, data from a list length experiment were analysed using variants of the Osth, Jansson, Dennis, and Heathcote (2018) model, that integrates the memory retrieval components of the Osth and Dennis (2015) model with the diffusion decision model (Ratcliff, 1978) to jointly account for choice probabilities and RT distributions. The standard version of the model, like existing recognition models, treated each condition as if no proactive interference had accumulated over the session. A more comprehensive version of the model allowed both study and test items from prior conditions to contribute proactive interference (PI) to future conditions. While the standard model estimated a dominance of background-noise, the PI model estimated a dominance of item-noise, reversing the conclusions made by Osth and Dennis (2015). Along with list length, the experimental design provided a measure of the test position effect (TPE). While the standard model attributed the TPE to context drift, the PI model attributed the TPE to both context drift and increases in item-noise.