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Journal articles on the topic 'Slosson Intelligence Test'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 August 2024

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1

Karnes, Frances A., James E. Whorton, Billie Bob Currie, and Steven W. Cantrall. "Correlations of Scores on the WISC—R, Stanford-Binet, the Slosson Intelligence Test, and the Developing Cognitive Abilities Test for Intellectually Gifted Youth." Psychological Reports 58, no. 3 (1986): 887–89. http://dx.doi.org/10.2466/pr0.1986.58.3.887.

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For a sample of 173 intellectually gifted students, percentiles from the Developing Cognitive Abilities Test were correlated with IQs from the Wechsler Intelligence Scale for Children—Revised, Stanford-Binet, and Slosson Intelligence Test—Revised. Although the coefficients of the WISC—R and Slosson with the DCAT tended to be significant, they were too low to have practical meaning and those with Stanford-Binet IQs were nonsignificant.

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2

Alston, Reginald J. "A Concurrent Validity Study of the APTCOM's General Intelligence Scale: A Pilot Investigation." Journal of Applied Rehabilitation Counseling 21, no. 1 (1990): 32–34. http://dx.doi.org/10.1891/0047-2220.21.1.32.

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The general intelligence scale of the APT/COM computer-assisted vocational evaluation system was investigated for concurrent validity, using the Slosson Intelligence Test as the criterion. Fifteen university students with disabilities served as subjects in this pilot study. It was found that the APTICOM's intelligence scale is significantly correlated to the Slosson Intelligence Test. Implications for rehabilitation research and practice are discussed.

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3

Williams, Thomas O., Ronald C. Eaves, Suzanne Woods-Groves, and Gina Mariano. "Stability of Scores for the Slosson Full-Range Intelligence Test." Psychological Reports 101, no. 1 (2007): 135–40. http://dx.doi.org/10.2466/pr0.101.1.135-140.

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The test-retest stability of the Slosson Full-Range Intelligence Test by Algozzine, Eaves, Mann, and Vance was investigated with test scores from a sample of 103 students. With a mean interval of 13.7 mo. and different examiners for each of the two test administrations, the test-retest reliability coefficients for the Full-Range IQ, Verbal Reasoning, Abstract Reasoning, Quantitative Reasoning, and Memory were .93, .85, .80, .80, and .83, respectively. Mean differences from the test-retest scores were not statistically significantly different for any of the scales. Results suggest that Slosson scores are stable over time even when different examiners administer the test.

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4

Sattler, Jerome M., Dene E. Hilson, and Theron M. Covin. "Comparison of Slosson Intelligence Test—Revised Norms and Peabody Picture Vocabulary Test—Revised with Black Headstart Children." Perceptual and Motor Skills 60, no. 3 (1985): 705–6. http://dx.doi.org/10.2466/pms.1985.60.3.705.

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Slosson Intelligence Test IQs (revised norms) and Peabody Picture Vocabulary Test—Revised (PPVT-R, Form L) standard scores for 100 black rural Headstart children were correlated and then compared by use of a one-way design for repeated measures. Although the correlation of .48 between the two tests was significant, Slosson IQs ( M = 100.27, SD = 14.82) were significantly higher than PPVT-R scores ( M = 74.80, SD = 14.23). These results suggest that the two instruments are not equivalent. There is a need for further research with these two instruments with black and with white children.

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5

Myers, Meyer, John C. Brantley, Lisbet Nielsen, Gary Cowan, and Cynthia Howard. "Software Review: Slosson Intelligence Test Computer Report (SIT-CR)." Journal of Psychoeducational Assessment 8, no. 4 (1990): 556–57. http://dx.doi.org/10.1177/073428299000800413.

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6

WILLIAMS, THOMAS O. "STABILITY OF SCORES FOR THE SLOSSON FULL-RANGE INTELLIGENCE TEST." Psychological Reports 101, no. 5 (2007): 135. http://dx.doi.org/10.2466/pr0.101.5.135-140.

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7

Jaffar, Rabia, and Amena Zehra Ali. "Examining Ease and Challenges in Tele-Assessment of Children Using Slosson Intelligence Test." Vol. 36 No. 4 (2021) 36, no. 4 (2021): 555–70. http://dx.doi.org/10.33824/pjpr.2021.36.4.30.

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As the world came to terms with the longevity of the COVID-19 crisis, there came a mass migration towards tele-health services which included tele-assessments. Practitioners argued that delaying assessments would mean a delay in provision of services. Therefore wherever possible, assessment procedures were modified to cater to an online setting including assessment of cognitive abilities. With its many advantages tele-assessment brings many unpredictable challenges. In this study we tried to explore those by administering the Slosson Intelligence Test-third edition (Slosson, 2006) on a sample of 29 school going children ranging in age from 6 to 16 years old, via Zoom. Observations were divided into two categories, that is, logistical and practical. Results showed that technology improves accessibility of services and solves many logistical problems such as availability of testing venues, and makes communication easier. However, practicality was hindered as the testing environment was less controlled and factors such as internet disruptions, limitations in observations, and presence of other people and things in the household may adversely affect the scores. Moreover, virtual fatigue could be a factor that practitioners need to consider.

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8

Clark, Priscilla, R. Steve McCallum, Ron P. Edwards, and Lee K. Hildman. "Use of the slosson intelligence test in screening of gifted children." Journal of School Psychology 25, no. 2 (1987): 189–92. http://dx.doi.org/10.1016/0022-4405(87)90029-x.

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9

Tomsic, Margie, and Richard J. Rankin. "Selecting gifted children with the Slosson Intelligence Test: 1981 vs. 1961 norms." Psychology in the Schools 22, no. 1 (1985): 102–3. http://dx.doi.org/10.1002/1520-6807(198501)22:1<102::aid-pits2310220120>3.0.co;2-e.

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10

Erford, Bradley T., and Deborah Pauletta. "Psychometric Analysis of Young Children’s Responses to the Slosson Intelligence Test-Primary (SIT-P)." Measurement and Evaluation in Counseling and Development 38, no. 3 (2005): 130–40. http://dx.doi.org/10.1080/07481756.2005.11909774.

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11

Flynt, Samuel W., Janet S. Warren, Rhonda C. Morton, and Furman H. Smith. "EXAMINING THE QUESTION OF GENDER BIAS IN THE SLOSSON INTELLIGENCE TEST IN RELATION TO READING." Reading Psychology 18, no. 3 (1997): 237–48. http://dx.doi.org/10.1080/0270271970180302.

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12

Hunter, Maxwell W., and Joan B. Ballash. "Comparison of the Slosson Intelligence Test and the Stanford-Binet Intelligence Scale, Fourth Edition, with Children Referred for Psychoeducational Assessment." Diagnostique 16, no. 1 (1990): 10–14. http://dx.doi.org/10.1177/153450849001600102.

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13

Eaves, Ronald C., Gloria Campbell-Whatley, Caroline Dunn, AmySue Reilly, and Carbestha Tate-Braxton. "Comparison of the Slosson Full-Range Intelligence Test and Teacher Judgments as Predictors of Students' Academic Achievement." Journal of Psychoeducational Assessment 12, no. 4 (1994): 381–92. http://dx.doi.org/10.1177/073428299401200408.

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14

Prewett, Peter N., and Diane B. Fowler. "Predictive validity of the Slosson Intelligence Test with the WISC-R and the WRAT-R level 1." Psychology in the Schools 29, no. 1 (1992): 17–21. http://dx.doi.org/10.1002/1520-6807(199201)29:1<17::aid-pits2310290104>3.0.co;2-e.

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15

Osisanya, Ayo, Kelechi Lazarus, and Abiodun Adewunmi. "Manifestations of Dyslexia and Dyscalculia." Journal of International Special Needs Education 16, no. 1 (2013): 40–52. http://dx.doi.org/10.9782/2159-4341-16.1.40.

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This study examined the prevalence of dyslexia and dyscalculia among persons with academic deficits in English Language and Mathematics in public primary schools in Ibadan metropolis. A correlational survey study, sampling 477 pupils who were between the ages of eight and 12 years, and in 4th and 5th grades with the use of four research instruments- the Myklebust Pupil Rating Scale (MPRS), the Slosson Intelligence Test- Revised Third Edition (SIT-R3), the Test of Pupil Reading Abilities Test (TPRA) and the Mathematical Abilities Test (MAT) was adopted. It was discovered that dyslexia and dyscalculia were prevalent among pupils with academic deficits in English Language and Mathematics, and that pupils with both dyslexia and dyscalculia are in the larger percentage. It was also discovered that learning disabilities, dyslexia and dyscalculia were not peculiar to any gender. Persons with academic deficits in English language and mathematics should be screened for either dyslexia or dyscalculia, even both. Also, they should be taught according to a carefully developed Individualized Education Plan.

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16

Klein, Nancy, Maureen Hack, John Gallagher, and Avroy A. Fanaroff. "Preschool Performance of Children with Normal Intelligence Who Were Very Low-Birth-Weight Infants." Pediatrics 75, no. 3 (1985): 531–37. http://dx.doi.org/10.1542/peds.75.3.531.

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Children who were very low-birth-weight infants (&lt; 1,500 g), beneficiaries of modern neonatal intensive care, are now of school age. To evaluate their school performance 80 children born in 1976 who had very low-birth-weight (mean birth weight 1.2 kg, mean gestational age 30 weeks) were examined at age 5 years. Sixty-five children were neurologically intact and had normal IQ (≥85) on the Stanford-Binet; five children were neurologically abnormal and ten had IQ below 85. Of the 65 children with normal intelligence and no neurologic impairments, 46 were single births and enrolled in preschool. These 46 children were matched by race, sex, and family background with classmate control children who had been born at full term. Outcome measurements included the Slosson Intelligence Test, the Woodcock-Johnson Psycho-Educational Battery (including subscales of Picture Vocabulary, Spatial Relations, Memory for Sentences, Visual Auditory Learning, Quantitative Concepts, and Blending) and the Beery Developmental Test of Visual-Motor Integration. No significant differences in IQ were found between children who were very low-birth-weight infants and control children; however, children who were very low-birth-weight infants performed significantly less well on the Spatial Relations subtest of the Woodcock-Johnson and on the Visual-Motor Integration test. Similar results were found for nine sets of twins and their control children. Recognition of these perceptual and visual-motor problems may permit appropriate early remedial intervention and prevent the compounding of these difficulties.

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17

Sattler, Jerome M., and Theron M. Covin. "Comparison of the slosson intelligence test, revised norms, and WISC-R for children with learning problems and for gifted children." Psychology in the Schools 23, no. 3 (1986): 259–64. http://dx.doi.org/10.1002/1520-6807(198607)23:3<259::aid-pits2310230306>3.0.co;2-i.

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18

Bell, Nancy L., Marggi Rucker, A. J. Finch, and Joanne Alexander. "Concurrent validity of the Slosson full-range intelligence test: Comparison with the Wechsler intelligence scale for children–third edition and the Woodcock Johnson tests of achievement–revised." Psychology in the Schools 39, no. 1 (2001): 31–38. http://dx.doi.org/10.1002/pits.10002.

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19

Khan, Arooj Karim, Aasma Yousaf, Sharmeen Aslam Tarer, and Rukhsana Kausar. "THE SPEECH SOUND ERRORS AND LITERACY SKILLS IN CHILDREN WITH OROFACIAL CLEFTS." PAFMJ 71, no. 6 (2021): 1976–80. http://dx.doi.org/10.51253/pafmj.v6i6.4044.

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Objective: To investigate the speech sound errors and literacy skills in children with orofacial clefts (cleft palate& cleft lip and palate). Study Design: Comparative cross-sectional study. Place and Duration of Study: Centre for Clinical Psychology, University of the Punjab, Lahore, from Mar 2016 to Feb 2017. Methodology: A sample of 42 participants (cleft lip & palate: n=18 and cleft palate: n=24) was collected. Two stage sampling strategy was used. Each child was individually screened through Slosson intelligence test revised checklist of orofacial cleft and diagnostic statistical Manual-V checklist. Then children were provided with assessment measures which included demographic informational questionnaire, community developed VPI Screener, word list for articulation and phonological processes, annual status of education report (ASER) and curriculum-based measurement (Written Expression). Manual SODA (substitution, omission, distortion and addition) analysis was done to know about the type of speech sound errors. Results: Independent sample t-test was used to compare the differences of speech sound errors (52.11 ± 25.08), (47.29 ± 25.38), reading skills (3.67 ± 1.14), (3.75 ± 1.26) and writing skills (14.61 ± 13.49), (25.14 ± 29.16) in cleft lip & palate and cleft palate respectively, indicated that there were no differences; with p-value: p=0.54, 0.83, 0.13. Conclusion: Results indicated no significant differences in speech sound errors, reading, writing skills and resonance between children with cleft lip & palate and cleft palate.

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20

Fakolade, Olufemi Aremu, and Oloruntoba Bamidele. "SELF-ESTEEM AND PEER INFLUENCE AS PREDICTORS OF LEARNING OUTCOMES IN MATHEMATICS AMONG HIGH ABILITY STUDENTS IN IBADAN, OYO STATE, NIGERIA." Sokoto Educational Review 17, no. 2 (2017): 13. http://dx.doi.org/10.35386/ser.v17i2.33.

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Academic underachievement has become a syndrome especially among high ability learners in Mathematics. This is due to some identified factors which include self-esteem and peer influence of the high ability learners. This study therefore investigated how self-esteem and peer influence can predict the learning outcomes in Mathematics of high ability learners in Ibadan, Oyo State. The survey design of the ex-post facto type was employed in this study. Purposive sampling technique was used to select twenty (20) secondary school out of which 200 high ability learners were randomly selected. Instruments used: Slosson intelligence test (r=0.81); Peer influence inventory (r=0.72); Self-esteem scale (r=0.72) and Mathematics achievement test (r=0.85). The study lasted for eight weeks. Data were analysed using Pearson’s Product Moment Correlation and Multiple Regression Analysis at 0.05 level of significance. There were positive relationship between learning outcomes in Mathematics with self-esteem (r=2.3); peer influence (r=2.2). There was a significant joint contribution of the independent variables to the dependent variable of learning outcomes in Mathematics. [F(2,197)=7.64; R2=0.072] accounting for 6.3% of its variance. Self-esteem (β=2.6; t=2.176) and peer influence (β=1.6; t=2.114) had a relative contribution on the learning outcomes in Mathematics of highly ability learners. Thus, self-esteem and peer influence were found to be effective predictors of learning outcomes in mathematics of high ability learners. It is therefore recommended that self-esteem of the high ability learners needs to be enhanced through various programmes especially by the school counsellors. Also, parents and wards should support their children by advising them on the type of friends they keep. With this in place, the high ability learners will perform better in Mathematics.

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21

Siegel, Patricia T., Richard Clopper, and Brian Stabler. "The Psychological Consequences of Turner Syndrome and Review of the National Cooperative Growth Study Psychological Substudy." Pediatrics 102, Supplement_3 (1998): 488–91. http://dx.doi.org/10.1542/peds.102.s3.488.

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Objective. To present longitudinal data on the psychological profile of a cohort of girls with and without Turner syndrome (TS) treated for 3 years with growth hormone (GH). Methods. Among a sample of 283 children with short stature, 37 girls with TS were recruited at 27 US medical centers. Of the original cohort, 22 girls with TS, 13 girls with isolated growth hormone deficiency (GHD), and 12 girls with idiopathic short stature were followed through 3 years of GH therapy. All were school-age, were below the 3rd percentile for height, had low growth rates, and were naive to GH therapy. Psychological tests (the Wide Range Achievement Test and the Slosson Intelligence Test) were administered to the clinical groups within 24 hours of their first GH injection and yearly thereafter. Control subjects were 25 girls with normal stature matched for age and socioeconomic status, who were tested only at baseline. One parent of each subject also completed the Child Behavior Checklist for that subject. Results. At baseline, the clinical groups had more internalizing behavioral problems, had fewer friends, and participated in fewer activities than did the control subjects. The groups did not differ in mean IQ or academic achievement, but the TS group did have more problems in mathematics achievement. Height and growth rate significantly increased in the clinical groups over the 3 years of GH therapy, but IQ and achievement scores did not. Significant linear reductions were noted in both Internalizing and Externalizing Behavior Problems after GH treatment, with the TS group having fewer behavior problems before and after GH treatment than did the GHD–idiopathic short stature group. Decreases in specific Child Behavior Checklist subscales, including attention, social problems, and withdrawal, also were seen in the clinical groups after GH therapy. Conclusions. The comprehensive treatment of girls with TS should include educational and behavioral interventions in addition to traditional medical therapies.

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22

Komarudin, Komarudin. "The Relationship Between Intelligence and Learning Motivation on Childrens With Special Need in Inclusive Elementary School." GUIDENA: Jurnal Ilmu Pendidikan, Psikologi, Bimbingan dan Konseling 7, no. 1 (2017). http://dx.doi.org/10.24127/gdn.v7i1.806.

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The research aimed to find out the corelation between intelligence and learning motivation in children with special need in inclusion elementary school. The data collecting technique used the learning motivation scale and Slosson Full Range Intelligence Test (S-FRIT). The data were analysed by used product moment correlation technique with SPSS 16. The data analysis result was correlation coefficient was 0.581 with a significance level of 0.000 (p <0.05). It meant there was positive correlation between intelligence and learning motivation. The higher level of intelligence, the learning motivation is also higher; conversely the lower level of intelligence, the learning motivation is also lower. The coefficient determination was 0.337 contributing intelligence to improvement learning motivation was 33.70%. This suggests that 66.30% learning motivation subjects influenced by other factors which not included in this research.

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