Intelligens handlar om förmågan att förstå, lösa problem, planera, tänka abstrakt, bearbeta information, tillgodogöra sig ny kunskap, samt förmågan att anpassa sig till sin miljö. Tidigare studier visar att kvällsmänniskor har högre IQ än morgonmänniskor. En orsak är att intelligenta personer är mer progressiva. Studier visar också att det inte finns könsskillnader i IQ. I denna studie undersöks om det finns ett samband mellan intelligens och dygnsrytm, samt mellan intelligens och faktiska sovtider. Ett annat syfte med denna undersökning var att undersöka om det finns skillnader i intelligens mellan män och kvinnor. Experimentet bistod av 250 deltagare, varav 151 kvinnor och 99 män i åldrarna 15-60. Ravens Standard Progressive Matrices användes för att mäta deltagarnas IQ. Morningness-Eveningness Questionnaire (MEQ) användes för att ta reda på deltagarnas dygnsrytm, och deltagarnas faktiska sovtider skrevs i timme och minut. Resultaten visade att kvällsmänniskor har i genomsnitt högre IQ än morgonmänniskor. Ett samband mellan deltagarnas faktiska sovtider och IQ fanns inte. Vidare visade resultaten att det inte finns någon skillnad i IQ mellan män och kvinnor.

MA, Clinical Psychology, Faculty of Humanities, University of the Witwatersrand

No description available.

Thesis (M.SocSc. (Psychology)) - Rhodes University, 2000. / Submitted in partial fulfillment of the requirements for the degree of Master of Social Science (Clinical psychology)

Test bias is a current focus of concern in both education and psychology. No where are the polemics of test bias stronger than in the area of ethnic/racial group differences on measures of intellectual functioning. Th problem of test bias is exacerbated when verbal intelligence tests are administered to students in a language in which they have limited facility and/or cultural reference. This problem is most evident in the United States with Hispanics. This study was designed to evaluate the Raven's Progressive Matrices (RPM) as a measure of non-biased assessment for Mexican-Americans. The RPM was selected because it is a non-verbal intelligence measure. The subjects were 230 Anglo and 230 Mexican-American elementary school children from Douglas, Arizona. The data were evaluated by analysis of regression with the Total Reading and Total Math scores of the Metropolitan Achievement Test (MAT). Both groups were analyzed together to identify any significant slope or intercept differences. All regression analyses were by grade level. Group validity coefficients were also computed for both math and reading by grade level and across grade level. The results of regression analysis indicated no test bias against Mexican-Americans. Slopes were equal at all grade levels. Some intercept variance occurred which would result in bias against Anglos, rather than Mexican-Anericans, if common regression lines were used. Also, validity coefficients of academic prediction for the RPM compared favorably to coefficients of the WISC-R Performance Scale for Mexican-Americans. Limitations of the study and areas of further research are discussed.

The capacity of Raven's Standard Progressive Matrices (SPM) and the Booklet Category Test (BCT) to discriminate between groups of brain-injured, simulated malingering, and normal participants was investigated in this study. Exploratory analyses were also conducted to examine the differences between groups categorized as sophisticated and naive fakers. Clinical decision rules and discriminant function analyses were utilized to identify malingerers. Clinical decision rules ranged in hit rates from 41% to 78%, in sensitivity from 2% to 100%, and in specificity from 86% to 100%. Discriminant functions ranged in hit rates from 81% to 86%, in sensitivity from 68% to 73% and in specificity from 82% to 87%. Overall, the least helpful detection method examined was below chance responding on either measure, while the most efficient was gross errors for SPM.

The Raven’s Coloured Progressive Matrices (CPM) test is used extensively across a wide variety of settings in South Africa, however more appropriate local normative data has yet to be established. The CPM is internationally recognised as a culture-fair test of nonverbal intelligence, designed for use with children between the ages of 5½ and 11½. This pilot study thus sought to establish normative data for this instrument for a population of Xhosa-speaking Primary School children in the peri-urban township area in the Grahamstown region. The booklet version of the test was used and it was administered in group format and according to an alternate method of test administration (using Xhosa instructions) developed by Vass in 1992. The final normative sample consisted of 197 male and 182 female Xhosa-speaking children in Grades Two to Seven (N=379). The results showed (1) a significant effect of age on test scores, where scores increased with age as expected; (2) a consistent tendency for males to outperform females was also noted, however small sample sizes precluded any categorical claims to this effect; (3) no significant effect of education on test scores was observed and finally; (4) and finally, it appeared that the norms generated for this study revealed a tendency to be lower than those obtained by Raven, Court and Raven (1990) during the standardisation of this instrument in the United Kingdom and America. The study concluded that (1) there is an urgent need for more appropriate South African normative data for this test; and (2) that when assessing African children from disadvantaged backgrounds, further research into the effects of cultural and socio-economic factors and gender on non-verbal intelligence (and on performance on this test in particular) is required.

Arising out of a need, expressed by Clinical Psychologists in the Grahamstown region, for the fair assessment of secondary School African pupils, norms for the Raven's Standard Progressive Matrices (SPM) were established. Two methods of presentation were used, the first using the original instructions of John Raven translated into the students' first language of Xhosa, hence-forth referred to as the Alternate sample. The second method of presenting the instructions was adapted, to include the use of visual aids and active participation in the instruction phase of the test, hence-forth referred to as the Normative sample. In addition to the establishment of norms, the two methods of test presentation were investigated to see if the method of presentation had an effect on the results of the Raven's SPM. The population was drawn from the three African Secondary Schools in the Grahamstown municipality. The total population consisted of 3 232 students. Classes were randomly sampled across the three schools, with the average age of the Normative sample being 19.3 years. The sample consisted of 812 pupils, 711 in the Normative sample and 101 in the Alternate Sample. The following results and conclusions arose from the study: 1) Norms generated were considerably lower than previously established norms in similar studies. 2) t-Test results indicated that the method of test presentation on the Raven's SPM is important when assessing students that may be regarded as 'disadvantaged'. 3) Respondents scored significantly higher when the method of presenting the instructions ensured a greater understanding of the task demanded of the respondents. 4) The analyses of covariance indicate that male subjects score significantly higher than female subjects, and that there is a significant difference between the ages and educational standard, on the scores of the Raven's SPM. 5) The differences found contradict previous findings using the test, and question the cultural fairness of the test.

The link between speech-in-noise recognition and cognition has been researched extensively over the years, and the purpose of this thesis was to add to this field. Data from a sample of 394 participants from the n200 database (Rönnberg et al., 2016) was used to calculate the correlation between their performance on a speech-in-noise test and their score on a test measuring fluid intelligence. The speech-in-noise test consisted of matrix sentences with 4-talker babble as noise and fluid intelligence was represented by the score on a Raven’s Progressive Matrices test. Around half of the participants (n = 199) had documented hearing loss and were hearing aid users, while the rest were participants with normal hearing. The overall correlation between speech-in-noise recognition and fluid intelligence was -.317, which shows that a better (lower) score on the speech-in-noise test is correlated to a better score in the Raven’s test. The same type of correlation was calculated within the two different groups, and the results showed correlation of -.338 for the group without hearing loss and one of -.303 for the group with hearing loss. The results indicate that there is a weak to moderate correlation between speech-in-noise and fluid intelligence, and they support the theory that cognitive processing is related to speech perception in all people, regardless of hearing status.

Much of cognitive science research and almost all of AI research into problem solving has focused on the use of verbal or propositional representations. However, there is significant evidence that humans solve problems using different representational modalities, including visual or iconic ones. In this dissertation, I investigate visual problem solving from the perspectives of autism, psychometrics, and AI. Studies of individuals on the autism spectrum show that they often use atypical patterns of cognition, and anecdotal reports have frequently mentioned a tendency to "think visually." I examined one precise characterization of visual thinking in terms of iconic representations. I then conducted a comprehensive review of data on several cognitive tasks from the autism literature and found numerous instances indicating that some individuals with autism may have a disposition towards visual thinking. One task, the Raven's Progressive Matrices test, is of particular interest to the field of psychometrics, as it represents one of the single best measures of general intelligence that has yet been developed. Typically developing individuals are thought to solve the Raven's test using largely verbal strategies, especially on the more difficult subsets of test problems. In line with this view, computational models of information processing on the Raven's test have focused exclusively on propositional representations. However, behavioral and fMRI studies of individuals with autism suggest that these individuals may use instead a predominantly visual strategy across most or all test problems. To examine visual problem solving on the Raven's test, I first constructed a computational model, called the Affine and Set Transformation Induction (ASTI) model, which uses a combination of affine transformations and set operations to solve Raven's problems using purely pixel-based representations of problem inputs, without any propositional encoding. I then performed four analyses using this model. First, I tested the model against three versions of the Raven's test, to determine the sufficiency of visual representations for solving this type of problem. The ASTI model successfully solves 50 of the 60 problems on the Standard Progressive Matrices (SPM) test, comparable in performance to the best computational models that use propositional representations. Second, I evaluated model robustness in the face of changes to the representation of pixels and visual similarity. I found that varying these low-level representational commitments causes only small changes in overall performance. Third, I performed successive ablations of the model to create a new classification of problem types, based on which transformations are necessary and sufficient for finding the correct answer. Fourth, I examined if patterns of errors made on the SPM can provide a window into whether a visual or verbal strategy is being used. While many of the observed error patterns were predicted by considering aspects of the model and of human behavior, I found that overall error patterns do not seem to provide a clear indicator of strategy type. The main contributions of this dissertation include: (1) a rigorous definition and examination of a disposition towards visual thinking in autism; (2) a sufficiency proof, through the construction of a novel computational model, that visual representations can successfully solve many Raven's problems; (3) a new, data-based classification of problem types on the SPM; (4) a new classification of conceptual error types on the SPM; and (5) a methodology for analyzing, and an analysis of, error patterns made by humans and computational models on the SPM. More broadly, this dissertation contributes significantly to our understanding of visual problem solving.