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The four dominant theories of reasoning from conditionals are translated into formal models: The theory of mental models (Johnson-Laird, P. N., & Byrne, R. M. J. (2002). Conditionals: a theory of meaning, pragmatics, and inference. Psychological Review, 109, 646-678), the suppositional theory (Evans, J. S. B. T., & Over, D. E. (2004). If. Oxford: Oxford University Press), a dual-process variant of the model theory (Verschueren, N., Schaeken, W., & d'Ydewalle, G. (2005). A dual-process specification of causal conditional reasoning. Thinking & Reasoning, 11, 278-293), and the probabilistic theory (Oaksford, M., Chater, N., & Larkin, J. (2000). Probabilities and polarity biases in conditional inference. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 883-899). The first three theories are formalized as multinomial models. The models are applied to the frequencies of patterns of acceptance or rejection across the four basic inferences modus ponens, acceptance of the consequent, denial of the antecedent, and modus tollens. Model fits are assessed for two large data sets, one representing reasoning with abstract, basic conditionals, the other reflecting reasoning with pseudo-realistic causal and non-causal conditionals. The best account of the data was provided by a modified version of the mental-model theory, augmented by directionality, and by the dual-process model.
Between reasoning
(2006)
In two experiments we investigated three-term reasoning with spatial relational assertions using the preposition between as compared to projective prepositions (such as to the left of). For each kind of assertion we distinguish the referent expression (i.e., the grammatical subject) from the relatum expression (i.e., the internal argument of the preposition; e.g., [The hedgehog](referent)_(expression) is to the left of [the frog](relatum)_(expression); [the snake](referent)_(expression) is between [the donkey and the deer](relatum)_(expression)). Previous research has shown that integrating premises with projective prepositions is easier (a) when the relatum expression of the second premise denotes an element already given by the first premise (relatum = given), and (b) when the term denoting a given element precedes the term denoting a new element (given - new). Experiment 1 extended this finding to second premises with the preposition between. In Experiment 2, between figured in the first premise. In this case, participants built an initial preferred model already from the first premise, although such a premise is indeterminate with respect to the array that it describes. Since there is no need left for integrating the second premise, this premise is instead used to verify the initial model and to modify it when necessary. A further investigation of conclusion evaluation times showed that conclusions were evaluated faster when they first mentioned the element that was included most recently into the mental model of the premises. The use of premises with between permitted the separation of recency of model inclusion from recency of appearance of an element in a premise.
Lower P300 amplitude in eight-year-old offspring of alcoholic fathers with a delinquent history
(2006)
The aim of the present study was to investigate the P300 amplitude as a possible vulnerability marker in children of alcoholic (COA) fathers with and without paternal delinquency. Event-related potentials (ERPs) of 122 children aged 8 years (63 boys, 59 girls) were compared depending on father's alcoholism subtype: 30 COAs without paternal delinquency, 10 COAs with paternal delinquency, and 82 children of non-alcoholic and non-delinquent fathers. ERPs were recorded from Fz, Cz, and Pz, using an auditory oddball paradigm. Sinus tones of 60 dB HL were presented binaurally at 1,000 Hz (standard stimulus) and 2,000 Hz (target stimulus), at a relative frequency ratio of 80:20. Two trial blocks of 250 stimuli each were collected. Results indicated that only COAs with paternal delinquency displayed significant differences from the control group, characterized by reduced P300 amplitude at frontal site and in the second trial block. Thus, the combination of fathers' alcoholism and delinquency was more likely to relate to attenuated P300 amplitude in the offspring than paternal alcoholism alone. Our results suggest that both alcoholic and delinquent family history appear to play a role in P300 amplitude reduction in the offspring.
Adipositas
(2006)
Motivationsdiagnostik
(2006)
Bewältigungsmuster im Lehramtsstudium : eine Untersuchung an der Universität Münster und Potsdam
(2006)
Bezugsnorm-Orientierung
(2006)
Bezugsnormorientierung
(2006)
Psychologia motywacji
(2006)
Motivation
(2006)
What makes computer users spend their free time working with the computer? Are there different types of users and, if so, in what ways do they differ? N = 271 subjects took part in an online survey concerning the incentives for computer use in free time. Selected mailing lists were used to identify highly committed users (A4 3.9 hours of free time a day spent working with computers). The following incentive factors were found for these users: community/ affiliation; sense of competence; flexibility/utility; avoidance of boredom; rebellious tendency to illegality. Depending on their favorite use of the computer, three types of users were found: Purposeful users (58%), hackers (entering other networks without intention to cause damage) (22%), and crackers (entering other networks with intention to cause damage) (20%). There are significant differences in the incentive profiles of these types of users. Hacking and cracking, but not purposeful use, are correlated with flow experience and positive activation. These findings are not representative for all leisure time computer users. They refer to a sample of highly committed users who can be reached in special associations (e.g., relevant student networks, the Chaos Computer Club)
Paradigms used to study the time course of the redundant signals effect (RSE; J. O. Miller, 1986) and temporal order judgments (TOJs) share many important similarities and address related questions concerning the time course of sensory processing. The author of this article proposes and tests a new aggregate diffusion-based model to quantitatively explain both the RSE and TOJs and the relationship between them. Parametric data (13 stimulus onset asynchronies) from an experiment with pairs of visual stimuli (626-nm LEDs) confirm that, relative to central signals (3 degrees), peripheral signals (35 degrees) yield slower reaction times, more strongly modulated RSE time-course functions, and flatter TOJ psychometric functions. All of these qualitative features are well captured, even in quantitative detail, by the aggregate diffusion model.
A study with 114 young adults investigated the correlations of intelligence factors and working-memory capacity with reaction time (RT) tasks. Within two sets of four-choice RT tasks, stimulus-response compatibility was varied over three levels: compatible, incompatible, and arbitrary mappings. Two satisfactory measurement models for the RTs could be established: A general factor model without constraints on the loadings and a nested model with two correlated factors, distinguishing compatible from arbitrary mappings, with constraints on the loadings. Structural models additionally including factors for working memory and intelligence showed that the nested model with correlated factors is superior in fit. Working-memory capacity and fluid intelligence were correlated strongly with the nested factor for the RT tasks with arbitrary mappings, and less with the general RT factor. The results support the hypothesis that working memory is needed to maintain arbitrary bindings between stimulus representations and response representations, and this could explain the correlation of working-memory capacity with speed in choice RT tasks
In our cognitive motivational process model (Vollmeyer & Rheinberg, Zeitschrift für Pädagogische Psychologie, 12:11–23, 1998) we assume that initial motivation affects performance via motivation during learning and learning strategies. These variables are also central for self-regulation theories (e.g., M. Boekaerts, European Psychologist, 1:100–122, 1996). In this article we discuss methods with which the model can be tested. Initial motivation with its four factors challenge, probability of success, interest, and anxiety was measured with the Questionnaire on Current Motivation (QCM; Rheinberg, Vollmeyer, & Burns, Diagnostica, 47:57–66, 2001). As an indicator for the functional state we assessed flow with the FKS (Rheinberg, Vollmeyer, & Engeser, Diagnostik von Motivation und Selbstkonzept [Diagnosis of Motivation and Self-Concept], Hogrefe, Göttingen, Germany, 261–279, 2003). We also used different tasks, including a linear system, a hypermedia program, and university-level classes. In general, our methods are valid and with them we found support for our model.