Academic Acquisition and Academic Application: A Latent Profile Analysis

Date

2022-06-08

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Abstract

Background: Complex problem-solving (CPS) refers to how an individual strategically explores problems that are nonroutine in a methodical manner. This involves analyzing, applying, synthesizing, and evaluating new information. Individuals charged with crafting curriculum for primary and secondary education are becoming more aware of the difficulty of equipping students not only with a basket of facts, but with the ability to apply these facts to problem-solving, which is a significant challenge considering that students possess a vast array of differences including learning disabilities, attention deficit hyperactivity disorder, speech and language issues, and high intellectual ability, all of which require adjustment in curriculum delivery (Lemons et al., 2018). While education is typically studied from a subject domain perspective, there are fewer studies that explore relationships between acquisition skills and application skills which are the dimensions of CPS. Purpose: This cross-sectional study seeks to employ a person-oriented approach utilizing a data set of 916 primarily White, middle-class children (average age 12.43 years), the majority of whom attend private schools in urban/suburban areas of a large city in Texas. The study focuses on sub-grouping children in the data set using acquisition and application skills to identify the characteristics of these children. Focusing on subgrouping may provide insight into the characteristics that impact CPS ability. Methods: A latent profile analysis (LPA) approach was employed to identify latent profiles of examinees based on academic acquisition and application scores measured by the Woodcock-Johnson-IV Tests of Achievement. This study utilized data gathered within a private practice during completion of a battery of psychoeducational evaluations during the years 2007-2020. To address the research questions, an LPA model was estimated best fitting latent class model that identified sub-groups of children based on academic acquisition and application scores. Then, multinomial logistic regression was used to examine the relationship between the sub-groups and the following individual characteristics: Age, gender, intellectual ability, previous ADHD diagnosis, presence of learning disabilities, and reported speech delay. Results: Results generated by this analysis identified the groups Average, Academic Amblers, Conceptual Leapers, and Floundering in terms of academic achievement. Results also demonstrate that presence of LDs, age, and IQ were statistically significant predictors for group assignment (p=<.001). Conclusion: Students with high IQ may be able to apply skills learned at the academic acquisition level without explicit instruction in order to solve complex problems; however, this does not seem to be the case for exceptional students with average IQ. Explicit instruction on the transference of academic acquisition skills to problem-solving is vital at the curriculum level.

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Keywords

Academic acquisition, Academic application, Academic achievement, Exceptional students, Complex problem-solving

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