Overclaiming has been described as people's tendency to overestimate their cognitive abilities in general and their knowledge in particular. We discuss four different perspectives on the phenomenon of overclaiming that have been proposed in the research literature: Overclaiming as a result of a) self-enhancement tendencies, b) as a cognitive bias (e.g., hindsight bias, memory bias), c) as proxy for cognitive abilities, and d) as sign of creative engagement. Moreover, we discuss two different scoring methods for an OCQ (signal detection theory vs. familiarity ratings). To distinguish between the different viewpoints of what overclaiming is, we juxtaposed overclaiming, as indicated by claiming familiarity with non-existent terms, with fluid and crystallized intelligence, self-reported knowledge, creativity, faking ability, and personality. Overclaiming was measured with a newly comprised overclaiming questionnaire. Results of several latent variable analyses based upon a multivariate study with 298 participants were: First, overclaiming is neither predicted by honesty-humility nor faking ability and therefore reflects something different than mere self-enhancement tendencies. Second, overclaiming is not predicted by crystallized intelligence, but is highly predictive of self-reported knowledge and, thus, not suitable as an index or a proxy for cognitive abilities. Finally, overclaiming is neither related to divergent thinking and originality, and only moderately predicted by self-reported openness creativity from the HEXACO which means that overclaiming does not reflect creative ability. In sum, our results favor an interpretation of overclaiming as a phenomenon that requires more than self-enhancement motivation, in contrast to the claim that was initially proposed in the literature.
Performance in elementary cognitive tasks is moderately correlated with fluid intelligence and working memory capacity. These correlations are higher for more complex tasks, presumably due to increased demands on working memory capacity. In accordance with the binding hypothesis, which states that working memory capacity reflects the limit of a person’s ability to establish and maintain temporary bindings (e.g., relations between items or relations between items and their context), we manipulated binding requirements (i.e., 2, 4, and 6 relations) in three choice reaction time paradigms (i.e., two comparison tasks, two change detection tasks, and two substitution tasks) measuring mental speed. Response time distributions of 115 participants were analyzed with the diffusion model. Higher binding requirements resulted in generally reduced efficiency of information processing, as indicated by lower drift rates. Additionally, we fitted bi-factor confirmatory factor analysis to the elementary cognitive tasks to separate basal speed and binding requirements of the employed tasks to quantify their specific contributions to working memory capacity, as measured by Recall−1-Back tasks. A latent factor capturing individual differences in binding was incrementally predictive of working memory capacity, over and above a general factor capturing speed. These results indicate that the relation between reaction time tasks and working memory capacity hinges on the complexity of the reaction time tasks. We conclude that binding requirements and, therefore, demands on working memory capacity offer a satisfactory account of task complexity that accounts for a large portion of individual differences in ability.
Overclaiming has been described as people’s tendency to overestimate their cognitive abilities in general and their knowledge in particular. We discuss four different perspectives on the phenomenon of overclaiming that have been proposed in the research literature: Overclaiming as a result of a) self-enhancement tendencies, b) as a cognitive bias (e.g., hindsight bias, memory bias), c) as proxy for cognitive abilities, and d) as sign of creative engagement. Moreover, we discuss two different scoring methods for an OCQ (signal detection theory vs. familiarity ratings). To distinguish between the different viewpoints of what overclaiming is, we juxtaposed overclaiming, as indicated by claiming familiarity with non-existent terms, with fluid and crystallized intelligence, self-reported knowledge, creativity, faking ability, and personality. Overclaiming was measured with a newly comprised overclaiming questionnaire. Results of several latent variable analyses based upon a multivariate study with 298 participants were: First, overclaiming is neither predicted by honesty-humility nor faking ability and therefore reflects something different than mere self-enhancement tendencies. Second, overclaiming is not predicted by crystallized intelligence, but is highly predictive of self-reported knowledge and, thus, not suitable as an index or a proxy for cognitive abilities. Finally, overclaiming is neither related to divergent thinking and originality, and only moderately predicted by self-reported openness creativity from the HEXACO which means that overclaiming does not reflect creative ability. In sum, our results favor an interpretation of overclaiming as a phenomenon that requires more than self-enhancement motivation, in contrast to the claim that was initially proposed in the literature.
Declarative fact knowledge is a key component of crystallized intelligence. It is typically measured with multiple-choice (MC) items. Other response formats, such as open-ended formats are less frequently used, although these formats might be superior for measuring crystallized intelligence. Whereas MC formats presumably only require recognizing the correct response to a question, open-ended formats supposedly require cognitive processes such as searching for, retrieving, and actively deciding on a response from long-term memory. If the methods of inquiry alter the cognitive processes involved, mean-changes between methods for assessing declarative knowledge should come along with changes in the covariance structure. We tested these assumptions in two online studies administering declarative knowledge items in different response formats (MC, open-ended, and open-ended with cues). Item difficulty clearly increases in the open-ended methods although effects in logistic regression models vary slightly across items. Importantly, latent variable analyses suggest that the method of inquiry does not affect what is measured with different response formats. These findings clearly endorse the position that crystallized intelligence does not change as a function of the response format.
In tests of working memory with verbal or spatial materials repeating the same memory sets across trials leads to improved memory performance. This well-established “Hebb repetition effect” could not be shown for visual materials. This absence of the Hebb effect can be explained in two ways: Either persons fail to acquire a long-term memory representation of the repeated memory sets, or they acquire such long-term memory representations, but fail to use them during the working memory task. In two experiments, (N1 = 18 and N2 = 30), we aimed to decide between these two possibilities by manipulating the long-term memory knowledge of some of the memory sets used in a change-detection task. Before the change-detection test, participants learned three arrays of colors to criterion. The subsequent change-detection test contained both previously learned and new color arrays. Change detection performance was better on previously learned compared to new arrays, showing that long-term memory is used in change detection.
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