Controlling for increased guessing enhances the independence of the Flynn effect from g: The return of the Brand effect

Woodley, Michael A.; Nijenhuis, Jan te; Must, Olev; Must, Anne

doi:10.1016/j.intell.2013.12.004

Cited by 40 publications

(27 citation statements)

References 48 publications

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“…Using these types of guessing strategies might lead to better results regardless of ability level and better results than other students at the same ability level not using these types of strategies (Dodeen 2008). It has been found that the willingness to 404 Stenlund T. et al guess (i.e., risk-taking) has increased over the years, and that changed test-taking behaviors, such as to use guessing and effective elimination processes to increase the odds of choosing a correct answer, even might be a reasonable explanation to the secular gain in measured IQ over time, that is the so-called Flynn effect (Woodley et al 2014). Guessing is, however, not always effective.…”

Section: Risk-takingmentioning

confidence: 99%

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The successful test taker: exploring test-taking behavior profiles through cluster analysis

2017

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To be successful in a high-stakes testing situation is desirable for any test taker. It has been found that, beside content knowledge, test-taking behavior, such as risktaking strategies, motivation, and test anxiety, is important for test performance. The purposes of the present study were to identify and group test takers with similar patterns of test-taking behavior and to explore how these groups differ in terms of background characteristics and test performance in a high-stakes achievement test context. A sample of the Swedish Scholastic Assessment Test test takers (N = 1891) completed a questionnaire measuring their motivation, test anxiety, and risk-taking behavior during the test, as well as background characteristics. A two-step cluster analysis revealed three clusters of test takers with significantly different test-taking behavior profiles: a moderate (n = 741), a calm risk taker (n = 637), and a test anxious risk averse (n = 513) profile. Group difference analyses showed that the calm risk taker profile (i.e., a high degree of risktaking together with relatively low levels of test anxiety and motivation during the test) was the most successful profile from a test performance perspective, while the test anxious risk averse profile (i.e., a low degree of risk-taking together with high levels of test anxiety and motivation) was the least successful. Informing prospective test takers about these insights can potentially lead to more valid interpretations and inferences based on the test scores. Eur J Psychol Educ (2018) shown that for a test taker to be successful when taking a test, it is important to be able to reduce anxiety and sustain motivation (Dodeen et al. 2014;Naylor 1997;Sternberg 1998), as well as using effective test-taking strategies, such as willingness to take risks (Bicak 2013;Bond and Harman 1994;Dodeen 2008). Studies in this area often compare groups of test takers and have for example found that high achievers tend to report using more effective testtaking strategies when compared to low achievers (Stenlund et al. 2017;Ellis and Ryan 2003;Hong et al. 2006;Kim and Goetz 1993), that males are more prone to taking risks when answering test items (see, e.g., Baldiga 2014), and that females and low achievers seem to experience higher levels of test anxiety than males and high achievers (Stenlund et al. 2017;Cassady and Johnson 2002;Naylor 1997). Findings like these can help understand and to some extent possibly explain performance differences that are often observed between manifest groups in achievement tests. Still, considering the consequences of successful test-taking behavior in high-stakes test situations, and assuming that test takers adopt different test-taking behavior, exploring differences across groups, in terms of profiles, and identifying patterns that seem associated with sucessful and less successful test-taking, respectively, might add important knowledge to this area. With this study, we therefore aim at identifying subgroups of test takers with similar patter...

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Section: Risk-takingmentioning

confidence: 99%

“…guess (i.e., risk-taking) has increased over the years, and that changed test-taking behaviors, such as to use guessing and effective elimination processes to increase the odds of choosing a correct answer, even might be a reasonable explanation to the secular gain in measured IQ over time, that is the so-called Flynn effect (Woodley et al 2014).…”

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confidence: 99%

The successful test taker: exploring test-taking behavior profiles through cluster analysis

2017

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“…Woodley, te Nijenhuis, Must, and Must [26] argue that most of the criticism of the MCV rests on two problematic premises. First, it has been made clear by Jensen [1] that one should use fairly representative samples, that a large enough number of tests should be used, and these tests should not all be similar-for instance, only reasoning tests-but must also be diverse in terms of content.…”

Section: Introductionmentioning

confidence: 99%

“…This means that Jensen was well aware of fundamental weaknesses in MCV and he showed that controlling for them strongly increased the value of the resulting correlations between the g vector and the d vector. Dolan's [25] finding that small samples in some cases yield unreliable outcomes comes as no surprise [26].…”

Section: Introductionmentioning

confidence: 99%

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Spearman’s Hypothesis Tested on Black Adults: A Meta-Analysis

Nijenhuis

Hoek

2016

J. Intell.

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Blacks generally score significantly lower on intelligence tests than Whites. Spearman's hypothesis predicts that there will be large Black/White differences on subtests of high cognitive complexity, and smaller Black/White differences on subtests of lower cognitive complexity. Spearman's hypothesis tested on samples of Blacks and Whites has consistently been confirmed in many studies on children and adolescents, but there are many fewer studies on adults. We carried out a meta-analysis where we collected the existing tests of Spearman's hypothesis on adults and collected additional datasets on Black and White adults that could be used to test Spearman's hypothesis. Our meta-analytical search resulted in a total of 10 studies with a total of 15 datapoints, with participants numbering 251,085 Whites and 22,326 Blacks in total. For all these data points, the correlation between the loadings of a general factor that is manifested in individual differences on all mental tests, regardless of content (g) and standardized group differences was computed. The analysis of all 15 data points yields a mean vector correlation of 0.57. Spearman's hypothesis is confirmed comparing Black and White adults. The differences between Black and White adults are strongly in line with those previously found for children and adults; however, because of lack of access to the original data, we could not test for measurement invariance.

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