Similarity,distance, and categorization: A discussion of Smith’s (2006) warning about “colliding parameters”

The idea that categorization decisions rely on subjective impressions of similarities between stimuli has been prevalent in much of the literature over the past 30 years and has led to the development of a large number of models that apply some kind of decision rule to similarity measures. A recent article by Smith (2006) has argued that thesesimilarity—choice models of categorization have a substantial design flaw, in which the similarity and the choice components effectively cancel one another out. As a consequence of this cancellation, it is claimed, the relationship between distance and category membership probabilities is linear in these models. In this article, I discuss these claims and show mathematically that in those cases in which it is sensible to discuss the relationship between category distance and category membership at all, the function relating the two is approximately logistic. Empirical data are used to show that a logistic function can be observed in appropriate contexts.     

On the interaction between exemplar-based concepts and a response scaling process

An analysis of the “response scaling” parameter in the Generalized Context Model is presented. In light of the existing debate over the behavior of the model when this parameter is included, three different interpretations are discussed, in order to illustrate the effect of the parameter at the decision level, the category similarity level, and the representational structure level.     

Dynamics of Flow: A Nonlinear Perspective

The aims of this study are to consider the experience of flow from a nonlinear dynamics perspective. The processes and temporal nature of intrinsic motivation and flow, would suggest that flow experiences fluctuate over time in a dynamical fashion. Thus it can be argued that the potential for chaos is strong. The sample was composed of 20 employees (both full and part time) recruited from a number of different organizations and work backgrounds. The Experience Sampling Method (ESM) was used for data collection. Once obtained the temporal series, they were subjected to various analyses proper to the complexity theory (Visual Recurrence Analysis and Surrogate Data Analysis). Results showed that in 80% of the cases, flow presented a chaotic dynamic, in that, flow experiences delineated a complex dynamic whose patterns of change were not easy to predict. Implications of the study, its limitations and future research are discussed.     

Do Additional Features Help or Hurt Category Learning? The Curse of Dimensionality in Human Learners

The curse of dimensionality, which has been widely studied in statistics and machine learning, occurs when additional features cause the size of the feature space to grow so quickly that learning classification rules becomes increasingly difficult. How do people overcome the curse of dimensionality when acquiring real‐world categories that have many different features? Here we investigate the possibility that the structure of categories can help. We show that when categories follow a family resemblance structure, people are unaffected by the presence of additional features in learning. However, when categories are based on a single feature, they fall prey to the curse, and having additional irrelevant features hurts performance. We compare and contrast these results to three different computational models to show that a model with limited computational capacity best captures human performance across almost all of the conditions in both experiments.     

Effect of variance ratio on ANOVA robustness: Might 1.5 be the limit?

Inconsistencies in the research findings on F-test robustness to variance heterogeneity could be related to the lack of a standard criterion to assess robustness or to the different measures used to quantify heterogeneity. In the present paper we use Monte Carlo simulation to systematically examine the Type I error rate of F-test under heterogeneity. One-way, balanced, and unbalanced designs with monotonic patterns of variance were considered. Variance ratio (VR) was used as a measure of heterogeneity (1.5, 1.6, 1.7, 1.8, 2, 3, 5, and 9), the coefficient of sample size variation as a measure of inequality between group sizes (0.16, 0.33, and 0.50), and the correlation between variance and group size as an indicator of the pairing between them (1, .50, 0, ?.50, and ?1). Overall, the results suggest that in terms of Type I error a VR above 1.5 may be established as a rule of thumb for considering a potential threat to F-test robustness under heterogeneity with unequal sample sizes.     

Information and communication technologies in teaching applied and experimental designs

In this work, an innovative teaching model applied to methodological contents in psychology is presented. The proposed didactic model includes Information and Communication Technologies (ICT), such as CD-ROMs, web sites and Internet. These resources complement class attendance. In the classes the students are informed, guided and oriented so that they are able to obtain information and reorganize it in a coherent way. The aim of this article is to find out the students' learning preferences and estimate the incorporation of ICT, by means of the ETIM (Evaluation of Teaching Innovation Model) questionnaire. The results show that the students are aware of the need to consult other materials and that ICT helps students to understand the subject from various perspectives. In this way, the students become more autonomous in acquiring learning results.     

Training higher education students in mathematics learning strategies

The present research focuses on the design and testing of a training program in learning strategies for Mathematics in Higher Education students. This research displays a quasiexperimental-sequential design with a non-equivalent control group. The research aims at revealing the effect of this training program both on the student's competence in learning strategies and on academic performance in this curricular area. There have been 176 students taking part in this research (74 students forming the experimental group and 72 forming the control group). The obtained results permit to assess the program efficiency as regards both trained strategies handling and specific performance improvement.     

Common and distinctive features in stimulus similarity: A modified version of the contrast model

Featural representations of similarity data assume that people represent stimuli in terms of a set of discrete properties. In this article, we consider the differences in featural representations that arise from making four different assumptions about how similarity is measured. Three of these similarity models— the common features model, the distinctive features model, and Tversky’s seminal contrast model—have been considered previously. The other model is new and modifies the contrast model by assuming that each individual feature only ever acts as a common or distinctive feature. Each of the four models is tested on previously examined similarity data, relating to kinship terms, and on a new data set, relating to faces. In fitting the models, we have used the geometric complexity criterion to balance the competing demands of data-fit and model complexity. The results show that both common and distinctive features are important for stimulus representation, and we argue that the modified contrast model combines these two components in a more effective and interpretable way than Tversky’s original formulation.     

Relation between resilience and personality traits: The role of hopelessness and age

Resilience refers to the process by which individuals use the ability to cope with challenges to successfully adapt to adverse situations, inclining towards the future and hope. The main aim of this study was to analyze the relation between resilience, personality traits, and hopelessness. Furthermore, we conducted comparisons between two age groups: young and older adults. The sample comprised 439 Spanish participants (66.7% women; M = 43.73, SD = 26.41; age range = 18–98 years). The Connor–Davidson Resilience Scale, NEO-Five Factor Inventory, and Beck Hopelessness Scale were used to measure the main study variables. The results revealed a negative relation between resilience and neuroticism, and a positive association with the other personality traits. Additionally, levels of resilience were found to be negatively related to hopelessness. The group of older adults showed significantly lower resilience levels than the young adults, although age was not a significant predictor of resilience. Neuroticism, extraversion, openness, and hopelessness were the only predictors of resilience for the current study. This work contributes to the study of resilience and related factors, by attempting to understand the role of resilience and resistance to risk and how individuals tackle challenges over time, with important implications for mental health.