The prediction of phobic behaviour

A 10-point rating scale, a pair comparison forced choice technique and a repertory grid were used to predict phobic behaviour in a standardized avoidance situation. The rating scale and pair comparison technique were significantly more accurate than the grid, but did not differ from each other. The results were seen to be consistent with others demonstrating that simple and economic self-report measures can often be more useful than apparently more sophisticated instruments. The results can also be taken to underline the need for including a variety of measures in validity studies of the repertory grid, and the caution necessary in the clinical application of this same instrument. The generality of the present conclusions to other situations needs, however, to be demonstrated rather than assumed. Social desirability, for example, is not thought to be an important variable in the present situation.     

Adolescent reading skill and engagement with digital and traditional literacies as predictors of reading comprehension

This study investigates the concurrent predictors of adolescent reading comprehension (literal, inferential) for fiction and non‐fiction texts. Predictors were examined from the cognitive (word identification, reading fluency), psychological (gender), and ecological (print exposure) domains. Print exposure to traditional and digital texts was surveyed using a diary method of reading habits. A cross‐sectional sample of 312 students in early (11–13 years) or middle adolescence (14–15 years) participated from a range of SES backgrounds. Word identification emerged as a strong predictor of reading comprehension across adolescence and text genres. Gender effects favouring female students were evident for reading frequency but not for reading skill itself. Reading habits also differed, and comprehension advantages were observed among females for fiction and males for non‐fiction. Age effects emerged for reading frequency, which was lower in middle adolescence. Although more time was spent on digital than on traditional texts, traditional extended text reading was the only reading habit to predict inference‐making in comprehension and to distinguish skilled from less skilled comprehenders. The theoretical and educational implications of these results are discussed.     

Situating Martin Heidegger's claim to a “productive dialogue” with Marxism

This critical review aims to more fully situate the claim Martin Heidegger makes in “Letter on Humanism” that a “productive dialogue” between his work and that of Karl Marx is possible. The prompt for this is Paul Laurence Hemming's recently published Heidegger and Marx: A Productive Dialogue over the Language of Humanism which omits to fully account for the historical situation which motivated Heidegger's seemingly positive endorsement of Marxism. This piece will show that there were significant external factors which influenced Heidegger's claim and that, when seen within his broader corpus, these particular comments in “Letter on Humanism” are evidently disingenuous, given that his general opinion of Marxism can only be described as vitriolic. Any attempt to explore how such a “productive dialogue” could be construed must fully contextualise Heidegger's claim for it. This piece will aim to do that, and more broadly explore Heidegger's general opinion of Marxism.     

Where to look first for an explanation of induction with uncertain categories

Recent research has examined how people predict unobserved features of an object when its category membership is ambiguous. The debate has focused on whether predictions are based solely on information from the most likely category, or whether information from other possible categories is also used. In the present experiment, we compared these category-based approaches with feature conjunction reasoning, where predictions are based on a comparison among exemplars (rather than categories) that share features with a target object. Reasoning strategies were assessed by examining patterns of feature prediction and by using an eye gaze measure of attention during induction. The main findings were (1) the majority of participants used feature conjunction rather than categorical strategies, (2) people predominantly gazed at the exemplars that were most similar to the target object, and (3) although people gazed most at the most probable category to which an object could belong, they also attended to other plausible category alternatives during induction. These findings question the extent to which category-based reasoning is used for induction when category membership is uncertain.     

Exemplar models as a mechanism for performing Bayesian inference

Probabilistic models have recently received much attention as accounts of human cognition. However, most research in which probabilistic models have been used has been focused on formulating the abstract problems behind cognitive tasks and their optimal solutions, rather than on mechanisms that could implement these solutions. Exemplar models are a successful class of psychological process models in which an inventory of stored examples is used to solve problems such as identification, categorization, and function learning. We show that exemplar models can be used to perform a sophisticated form of Monte Carlo approximation known as importance sampling and thus provide a way to perform approximate Bayesian inference. Simulations of Bayesian inference in speech perception, generalization along a single dimension, making predictions about everyday events, concept learning, and reconstruction from memory show that exemplar models can often account for human performance with only a few exemplars, for both simple and relatively complex prior distributions. These results suggest that exemplar models provide a possible mechanism for implementing at least some forms of Bayesian inference.     

Selective attention in human associative learning and recognition memory

Four experiments examined the role of selective attention in a new causal judgment task that allowed measurement of both causal strength and cue recognition. In Experiments 1 and 2, blocking was observed; pretraining with 1 cue (A) resulted in reduced learning about a 2nd cue (B) when those 2 cues were trained in compound (AB+). Participants also demonstrated decreased recognition performance for the causally redundant Cue B, suggesting that less attention had been paid to it in training. This is consistent with the idea that attention is preferentially allocated toward the more predictive Cue A, and away from the less predictive Cue B (e.g., N. J. Mackintosh, 1975). Contrary to this hypothesis, in Experiments 3 and 4, participants demonstrated poorer recognition for the most predictive cues, relative to control cues. A new model, which is based on N. J. Mackintosh's (1975) model, is proposed to account for the observed relationship between the extent to which each cue is attended to, learned about, and later recognized     

Gender swapping and socializing in cyberspace: an exploratory study.

Massively multiplayer online role-playing games (MMORPGs) are one of the most interesting innovations in the area of online computer gaming. Given the relative lack of research in the area, the main aims of the study were to examine (a) the impact of online gaming (e.g., typical playing behavior) in the lives of online gamers, (b) the effect of online socializing in the lives of gamers, and (c) why people engage in gender swapping. A self-selecting sample of 119 online gamers ranging from 18 to 69 years of age (M = 28.5 years) completed a questionnaire. The results showed that just over one in five gamers (21%) said they preferred socializing online to offline. Significantly more male gamers than female gamers said that they found it easier to converse online than offline. It was also found that 57% of gamers had engaged in gender swapping, and it is suggested that the online female persona has a number of positive social attributes in a male-oriented environment.     

The factor structure of the CVLT-C in pediatric epilepsy.

The current study used archival data to evaluate the fit of six latent variable models, originally generated by Donders (1999), for the California Verbal Learning Test-Children's Version (CVLT-C; Delis, Kramer, Kaplan, & Ober, 1994) in a large (N = 289) sample of pediatric epilepsy cases presenting at three tertiary treatment centers. Using confirmatory factor analysis, we found that a model including factors of Attention Span, Learning Efficiency, Free Delayed Recall, Cued Delayed Recall, and Inaccurate Recall demonstrated the best relative fit for our data. These findings are consistent with those reported by Donders (1999) in his reanalysis of the CVLT-C standardization sample data, supporting the validity of this factorial model in pediatric epilepsy populations.