People’s decisions may change when made in a foreign language (FL). Research testing this foreign language effect (FLE) has mostly used scenarios where uncertainty is expunged or reduced to a form of risk, whereas real-life decisions are usually characterized by uncertainty around outcome likelihood. In the current work, we aimed to investigate whether the FLE on decision-making extends to uncertain scenarios. Moreover, as it is still unclear what linguistic and psychological factors contribute to the FLE, we tested the effects of participants’ FL background, cognitive style and risk-taking attitude on decision processes under certain and uncertain conditions. Overall, we report null effects of language context (native versus foreign language) and problem condition (certain versus uncertain prospects) on participants’ choices. In addition, we found that both FL background and decision makers’ traits modulated participants’ choices in a FL, without emerging into the ‘classic’ FLE on decision-making. However, the direction of such effects was complex, and not always compatible with previous FLE theories. In light of these results, our study highlights the need to reconceptualize the FLE and its implications on decision-making.

Designers often rely on their self-evaluations – either independently or using design tools – to make concept selection decisions. When evaluating designs for sustainability, novice designers, given their lack of experience, could demonstrate psychological distance from sustainability-related issues, leading to faulty concept evaluations. We aim to investigate the accuracy of novice designers’ self-evaluations of the sustainability of their solutions and the moderating role of their (1) trait empathy and (2) their beliefs, attitudes and intentions toward sustainability on this accuracy. We conducted an experiment with first-year engineering students comprising a sustainable design activity. In the activity, participants evaluated the sustainability of their own designs, and these self-evaluations were compared against expert evaluations. We see that participants’ self-evaluations were consistent with the expert evaluations on the following sustainable design heuristics: (1) longevity and (2) finding wholesome alternatives. Second, trait empathy moderated the accuracy of self-evaluations, with lower levels of fantasy and perspective-taking relating to more accurate self-evaluations. Finally, beliefs, attitudes and intentions toward sustainability also moderated the accuracy of self-evaluations, and these effects vary based on the sustainable design heuristic. Taken together, these findings suggest that novice designers’ individual differences (e.g., trait empathy) could moderate the accuracy of the evaluation of their designs in the context of sustainability.

This study presents findings from a 4-year panel study examining three major questions regarding the measurement of social value orientation (SVO). First, we investigate the test–retest reliability of the Slider Measure (SLM, Murphy et al., 2014) over a period of up to 4 years in a large, demographically diverse sample. Second, we compare the stability of the SLM to related measurements of prosociality and distributional preferences along the behavior–behavioral tendency–trait continuum, including single behaviors (e.g., the Dictator Game and the Prisoner’s Dilemma), alternative behavioral tendencies (e.g., survey-based measures of altruism), and broader personality traits (e.g., Big-Five, HEXACO, Dark Factor D). Third, we explore differences in individual trajectories of SVO, focusing on how age and gender influence its stability and change over time. Our study thus complements earlier research on the stability of the SLM by extending the time period and depth of analysis, and putting the measure in the context of other related measures. The results show a considerable degree of stability, higher than all behavioral games, but often lower than fully fledged measures of personality traits. Furthermore, we find that age has a stabilizing effect on behavior in the SLM. With regard to gender, we find that women behave generally more prosocial than men but that they do not differ in their stability. We conclude that the SLM is a suitable method for assessing individual SVO over longer time periods and is best thought of as covering a sweet spot between stable personality traits and immediate behavioral expressions.

Some scholars have treated overconfidence as an individual difference—that is, assuming the tendency to be overconfident is stable within a person and differs meaningfully from person to person. We question this assumption. We investigate consistency within individuals between its three forms—overestimation, overplacement, and overprecision—in multiple domains (Study 1a and 1b), at multiple times (Study 1b and 2), and with multiple measures (Study 3a and 3b). We find mixed evidence of trait-like consistency. We do find some evidence of within-individual stability across domains and time points. However, we find little consistency across different measures of the same form of overconfidence—specifically overprecision. Instead, we find more consistent evidence that overconfidence varies situationally and contextually.

This paper responds to Al-Hoorie, Hiver, and In’nami’s (2024) critique of the second language (L2) Motivational Self System (L2MSS) by advocating for an immediate cessation of its use in the absence of substantial revision and validation. We revisit foundational studies in the tradition, exposing critical methodological flaws that we feel undermine empirical support for the model. Further, we examine systemic factors that contributed to the largely uncritical acceptance of the model. Drawing on our own experiences, we reflect on how these dynamics have obstructed the adoption of more robust motivational theories available in psychology and education. We further caution that without a stronger emphasis on validating measurement instruments, similar distractions may continue to hinder progress in the field.

While our earlier report focused on the initial four months of the dataset (Saito et al., 2018, Language Learning), this study investigates the relationship between individual differences in motivation (Ideal Self and Ought–to Self), emotions (Enjoyment and Anxiety), and L2 speech learning among 121 Japanese English–as–a–Foreign–Language high school students over 1.5–years. Participants’ L2 speech proficiency consistently improved at each testing point (6 months, 10 months, and 1.5 years), while their motivation and emotions, measured through questionnaires, remained relatively stable. The results of structural equation modeling suggest that the relationship between motivation, emotions, and acquisition may evolve. Within the first 6-10 months, data indicated a correlational relationship, highlighting a mutual influence among motivation, emotions, and acquisition. However, as the study progressed beyond one year, after students had fully adapted to their educational settings, a clearer causal relationship emerged: Enhanced motivation and more positive emotions were linked to increased classroom practice, leading to significant gains in L2 speech proficiency. The predictive roles of Anxiety remained unclear in this longitudinal dataset.

An intriguing study concluded that political conservatives exhibited enhanced self-control using the Stroop task [Clarkson et al.: The self-control consequences of political ideology. Proc. Natl. Acad. Sci. U.S.A, 112(27): 8250–8253 (2015)]. We preregistered our plans to re-examine this finding using a larger, representative, incentivized, and ideologically balanced sample (n = 476). Across a variety of specifications, we report a consistent null effect of ideology on Stroop response latencies and the Stroop interference effect. These findings suggest that the previously reported result may not generalize. We conclude that there is no causal relationship between political ideology and self-control, as measured by the Stroop task.

This study examined the influence of letter transpositions on morphological facilitation in L1 English and L1 Chinese-L2 English speakers. Morphological priming effects were investigated by comparing morphologically complex primes that either contained transposed-letters (TL) within the stem or across the morpheme boundary, relative to a substituted-letter (SL) control. Within two masked primed lexical decision experiments, the same stem targets were preceded by morphologically related, TL-within, SL-within, TL-across, SL-across, or unrelated primes. Reaction time analyses with morphologically intact primes revealed facilitation in both L1 and L2 English. In L1, TL-within priming was significant, while the magnitude of TL-across priming varied as a function of positional specific bigram frequency and spelling proficiency. In L2, TL-priming was entirely absent. These findings support models of complex word recognition that accommodate relative flexibility in letter position encoding.

Individuals differ greatly in their ability to learn the sounds of second languages, even when learning starts early in life. Recent research has suggested that the ability to identify the idiosyncratic acoustic variations introduced into the speech stream by the speaker might be relevant for second-language (L2) phoneme learning. However, only a positive correlation between voice recognition and phoneme learning has been shown. In the present study, we investigated whether voice processing ability predicts L2 phoneme learning. We employed a battery of behavioral cognitive ability measures to assess voice processing ability and L2 phoneme learning in 57 early bilingual adults. Confirmatory factor analyses (CFAs) and structural equation modeling (SEM) revealed that voice processing ability predicts L2 phoneme learning. Our findings align with theories of speech perception that attribute a fundamental role to the analysis of voice cues and suggest that the accurate identification of speaker-specific variation is also relevant for phoneme learning.

The Arabic development of Syrian refugee children (N = 133; mean age = 9;4 at Time 1) was examined over 3 time periods during their first five years in Canada. Children were administered sentence repetition and receptive vocabulary tasks in English and Arabic, and information about age-of-arrival (AOA), schooling in Arabic and language environment factors was obtained via parent report. Older AOA was associated with superior Arabic abilities across time, but regardless of AOA, children showed plateau/attrition patterns in Arabic and shifts to English dominance by Time 3. Increases in English over Arabic were observed for language use at home and language-rich activities overtime. Stronger Arabic Time 3 outcomes were predicted by more Arabic and less English use with siblings, more schooling in Arabic, more frequent listening-speaking and extra-curricular activities in Arabic, and more Arabic use with friends. We conclude that the heritage language can be vulnerable even for first-generation bilinguals.

The current study examined the comprehension and production of classifiers, case marking, and morphological passive structures among 414 child Japanese heritage speakers (mean age = 10.01 years; range = 4.02 – 18.18). Focusing on individual differences, we extracted latent experiential factors via the Q-BEx questionnaire (De Cat, Kašćelan, Prévost, Serratrice, Tuller, Unsworth, & The Q.-Be Consortium, 2022), which were then used to predict knowledge and use of these grammatical structures. The findings reveal that: (i) experiential factors such as heritage language (HL) engagement at home and within the community modulate grammatical performance differentially from childhood through adolescence, and (ii) HL proficiency, immersion experiences, and literacy systematically predict HL grammatical outcomes. These results indicate that particular language background factors hold differential significance at distinct developmental stages and that higher proficiency, richer immersion experiences, and literacy engagement in the HL are crucial for the development of core grammatical structures.

A review of the existing techniques for the analysis of three-way data revealed that none were appropriate to the wide variety of data usually encountered in psychological research, and few were capable of both isolating common information and systematically describing individual differences. An alternating least squares algorithm was proposed to fit both an individual difference model and a replications component model to three-way data which may be defined at the nominal, ordinal, interval, ratio, or mixed measurement level; which may be discrete or continuous; and which may be unconditional, matrix conditional, or row conditional. This algorithm was evaluated by a Monte Carlo study. Recovery of the original information was excellent when the correct measurement characteristics were assumed. Furthermore, the algorithm was robust to the presence of random error. In addition, the algorithm was used to fit the individual difference model to a real, binary, subject conditional data set. The findings from this application were consistent with previous research in the area of implicit personality theory and uncovered interesting systematic individual differences in the perception of political figures and roles.

Through external analysis of two-mode data one attempts to map the elements of one mode (e.g., attributes) as vectors in a fixed space of the elements of the other mode (e.g., stimuli). This type of analysis is extended to three-mode data, for instance, when the ratings are made by more individuals. It is described how alternating least squares algorithms for three-mode principal component analysis (PCA) are adapted to enable external analysis, and it is demonstrated that these techniques are useful for exploring differences in the individuals' mappings of the attribute vectors in the fixed stimulus space. Conditions are described under which individual differences may be ignored. External three-mode PCA is illustrated with data from a person perception experiment, designed after two studies by Rosenberg and his associates whose results were used as external information.

The kinds of individual differences in perceptions permitted by the weighted euclidean model for multidimensional scaling (e.g., INDSCAL) are much more restricted than those allowed by Tucker’s Three-mode Multidimensional Scaling (TMMDS) model or Carroll’s Idiosyncratic Scaling (IDIOSCAL) model. Although, in some situations the more general models would seem desirable, investigators have been reluctant to use them because they are subject to transformational indeterminacies which complicate interpretation. In this article, we show how these indeterminacies can be removed by constructing specific models of the phenomenon under investigation. As an example of this approach, a model of the size-weight illusion is developed and applied to data from two experiments, with highly meaningful results. The same data are also analyzed using INDSCAL. Of the two solutions, only the one obtained by using the size-weight model allows examination of individual differences in the strength of the illusion; INDSCAL can not represent such differences. In this sample, however, individual differences in illusion strength turn out to be minor. Hence the INDSCAL solution, while less informative than the size-weight solution, is nonetheless easily interpretable.

Stevens’ power law for the judgments of sensation has a long history in psychology and is used in many psychophysical investigations of the effects of predictors such as group or condition. Stevens’ formulation $\mathit{\Psi }={aP}^n$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\varPsi = {aP}^{n}$$\end{document}, where $\mathit{\Psi }$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\varPsi $$\end{document} is the psychological judgment, P is the physical intensity, and $n$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$n$$\end{document} is the power law exponent, is usually tested by plotting log $(\mathit{\Psi })$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$(\varPsi )$$\end{document} against log (P). In some, but by no means all, studies, effects on the scale parameter, $a$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$a$$\end{document}, are also investigated. This two-parameter model is simple but known to be flawed, for at least some modalities. Specifically, three-parameter functions that include a threshold parameter produce a better fit for many data sets. In addition, direct non-linear computation of power laws often fit better than regressions of log-transformed variables. However, such potentially flawed methods continue to be used because of assumptions that the approximations are “close enough” as to not to make any difference to the conclusions drawn (or possibly through ignorance the errors in these assumptions). We investigate two modalities in detail: duration and roughness. We show that a three-parameter power law is the best fitting of several plausible models. Comparison between this model and the prevalent two parameter version of Stevens’ power law shows significant differences for the parameter estimates with at least medium effect sizes for duration.

Points of view analysis (PVA), proposed by Tucker and Messick in 1963, was one of the first methods to deal explicitly with individual differences in multidimensional scaling, but at some point was apparently superceded by the weighted Euclidean model, well-known as the Carroll and Chang INDSCAL model. This paper argues that the idea behind points of view analysis deserves new attention, especially as a technique to analyze group differences. A procedure is proposed that can be viewed as a streamlined, integrated version of the Tucker and Messick Process, which consisted of a number of separate steps. At the same time, our procedure can be regarded as a particularly constrained weighted Euclidean model. While fitting the model, two types of nonlinear data transformations are feasible, either for given dissimilarities, or for variables from which the dissimilarities are derived. Various applications are discussed, where the two types of transformation can be mixed in the same analysis; a quadratic assignment framework is used to evaluate the results.

An individual differences additive model is discussed which represents individual differences in additivity by differential weighting of additive factors. A procedure for estimating the model parameters for various data measurement characteristics is developed. The procedure is evaluated using both Monte Carlo and real data. The method is found to be very useful in describing certain types of developmental change in cognitive structure, as well as being numerically robust and efficient.