PSYCH 655 Week 4 Intelligence and Achievement Tests Example

An Average Reasoning Score and a Fourth-Grade Reading Level: Intelligence and Achievement Testing for a Rehabilitation Client

[Student Name]

University of Phoenix

PSYCH/655: Psychometrics

Week 4 Assignment

[Instructor Name]

[Date]

The vocational rehabilitation office, its client and test results are composites written for a model paper; research findings come from the sources listed.

Intelligence and achievement tests are among the most widely used and most debated psychological instruments. They measure different things, and their results must be read in light of a person's history. Ms. Ortega's evaluation shows why the two must be read side by side.

The Case

Ms. Ortega, thirty-four, worked for twelve years as a line cook in Albuquerque restaurants until a back injury made long shifts on her feet impossible. She grew up in a farming community in southern New Mexico, spoke Spanish at home and left high school at sixteen to help support her family after her father's illness. She is fluent in English and reads Spanish well. She hopes to become a pharmacy technician, which requires a certificate program and passing a national certification exam. Her counselor asked for testing to understand her strengths and the supports she might need.

I administered an individual intelligence test and an achievement battery in English, after confirming her English proficiency for testing. Her verbal comprehension and fluid reasoning index scores were 98 and 103, both average; her working memory index was 94; her processing speed index was 86, low average. On the achievement battery, her reading comprehension standard score was 78, about a fourth-grade equivalent, and her math computation was 92.

What Intelligence Tests Measure

Deary (2012) reviewed research on intelligence and described a consistent finding: scores on diverse cognitive tests correlate positively, giving rise to a general factor of intelligence, g, which accounts for a substantial share of individual differences, alongside more specific abilities. Intelligence scores are relatively stable from childhood to old age, partly heritable, influenced by environment and education and associated with educational and occupational outcomes and with health and longevity. Deary also noted that much remains unknown about the biological basis of intelligence differences.

How Abilities Are Organized

McGrew (2009) summarized the Cattell-Horn-Carroll model, which integrates Cattell and Horn's theory of fluid and crystallized intelligence with Carroll's three-stratum model based on a massive factor analysis of cognitive tests. The model places a general factor at the top, about ten broad abilities in the middle, including fluid reasoning, comprehension-knowledge, short-term memory, visual processing, long-term storage and retrieval, processing speed and reading and writing, and many narrow abilities below. McGrew argued that the model provides a common language for test development and interpretation.

Most modern intelligence and achievement tests are built or interpreted with this structure. Ms. Ortega's index scores map onto broad abilities: fluid reasoning, comprehension-knowledge, working memory and processing speed. Reading achievement falls under a separate broad ability, reading and writing, which depends heavily on instruction.

Ability Versus Achievement

Intelligence tests estimate how readily a person reasons, solves new problems and learns; achievement tests measure what a person has already learned through instruction. The two are related, but achievement depends heavily on opportunity. Ms. Ortega's average reasoning and low reading achievement are consistent with interrupted schooling and limited opportunity to build English reading skills, rather than with a general limitation in learning ability. A specific learning disability in reading is possible, but her history of interrupted education and second-language learning makes opportunity a more likely primary explanation, and she reports no childhood reading difficulties in Spanish.

Her reasoning scores describe how she learns; her reading score describes how much schooling she missed.

Interpreting the Profile Carefully

Index scores carry measurement error. With a standard error of about 4 points, Ms. Ortega's verbal comprehension score of 98 could plausibly sit anywhere from about 90 to 106 if she were tested again. The difference between her fluid reasoning and processing speed, 17 points, exceeds what would be expected by chance and is relatively uncommon, but low processing speed can reflect slow, careful responding, unfamiliarity with timed paper tasks or pain during testing, as she shifted position often. I treated it as a possible weakness to watch, not a firm conclusion.

What Intelligence Predicts

Strenze (2007) meta-analyzed longitudinal studies relating intelligence measured early in life to later educational attainment, occupational level and income. Intelligence was a solid predictor, with correlations of about .56 for education, .45 for occupation and .23 for income, comparable to or stronger than parental socioeconomic status and school grades. Strenze emphasized that these are average relationships and that many other factors shape individual success.

For Ms. Ortega, average reasoning suggests she can learn the content of a technician program; the main barrier is reading, which affects both coursework and the certification exam.

Group Tests and Individual Tests

The office sometimes uses brief group-administered ability screens to decide who needs a full evaluation. Group tests are efficient but rely heavily on reading instructions and answering under time pressure, which would have underestimated Ms. Ortega's reasoning. Individual tests allow the examiner to read instructions aloud, observe effort and fatigue and adjust pacing within the rules. For clients with limited formal schooling, an individual test gives a more accurate picture, and the office now skips the group screen for clients who report leaving school early.

How the Results Were Shared

Test results can shape how people see themselves. I met with Ms. Ortega to explain the scores in plain terms, emphasizing that her reasoning was in the average range for adults, that reading is a skill learned through instruction and that the gap reflected missed schooling. She said she had always believed she was "not smart" because she struggled with reading in English, and that the explanation made her more willing to try a training program. Communicating results this way is part of using tests responsibly, not an afterthought.

Fairness Considerations

Testing a bilingual adult in English raises questions about whether verbal scores underestimate her ability. Her verbal comprehension score was average despite English being her second language, which suggests her ability may be at least as high as measured. Norms were based on U.S. adults, including bilingual adults, but not specifically on people with interrupted schooling.

Math and Other Strengths

Her math computation score of 92, within the average range, matters for a pharmacy technician, whose work includes dosage calculations and inventory counts. Combined with average reasoning and years of fast, accurate work in a busy kitchen, it suggests that the quantitative side of the training will be manageable once reading support is in place.

Recommendations

I recommended enrolling Ms. Ortega in an adult education reading program for six months, focused on vocabulary and comprehension of technical and medical texts, followed by the pharmacy technician program with accommodations such as extended time on exams if eligible. Her counselor arranged both, and Ms. Ortega said that knowing her reasoning was average changed how she saw herself.

Conclusion

Intelligence and achievement tests measure different things. Ms. Ortega's average reasoning and low reading achievement reflect interrupted schooling more than limited ability. Research on intelligence, its structure and its predictive power supports interpreting her profile carefully and investing in reading skills before technical training.

References

Deary, I. J. (2012). Intelligence. Annual Review of Psychology, 63, 453-482. https://doi.org/10.1146/annurev-psych-120710-100353

McGrew, K. S. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence, 37(1), 1-10. https://doi.org/10.1016/j.intell.2008.08.004

Strenze, T. (2007). Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence, 35(5), 401-426. https://doi.org/10.1016/j.intell.2006.09.004