INS NYC 2024 Program

Poster	Poster Session 08 Program Schedule 02/16/2024 01:45 pm - 03:00 pm Room: Shubert Complex (Posters 1-60) Poster Session 08: Cognition \| Cognitive Reserve Variables Final Abstract #13 Cognition and Math and Reading Overlap in Community College Students Paul Cirino, University of Houston, Houston, United States Cassidy Salentine, University of Houston, Houston, United States Cristina Boada, University of Houston, Houston, United States Juliana Wall, University of Houston, Houston, United States Category: Learning Disabilities/Academic Skills Keyword 1: pediatric neuropsychology Keyword 2: academic skills Keyword 3: learning Objective: Math and reading are related at the disability level and along the continuum of skill (Cirino, 2022). Cognitive correlates of math and reading in children are well-known separately, with a recent focus on the reason for their overlap. However, less is known about these issues in community college (CC) students despite more than half of post-secondary education occurring at this level. Here we assess cognitive predictors of math and reading (language, working memory, processing speed, nonverbal reasoning, attention) in CC students, outcome overlap, and the extent that predictors account for overlap. We expect all predictors to relate to achievement, with language and working memory as the strongest predictors, and accounting for the most overlap. We also expect more overlap and stronger prediction for complex outcomes (reading comprehension and math applications) relative to foundational skills (word reading and computations). Participants and Methods: Participants were 94 CC students enrolled in their first math class. Approximately half the students were taking developmental coursework. Participants were administered four KTEA-3 measures: Letter-Word Reading, Reading Comprehension, Math Computation, and Math Concepts and Application. Language consisted of Vocabulary (K-BIT-2), and Elision and Rapid Naming subtests of the CTOPP-2. Working memory was assessed with two complex span measures (Symmetry Span and Reading Span). Processing speed was measured with the WAIS-IV, and nonverbal reasoning with the K-BIT-2. Attention was assessed via a researcher-designed continuous performance task and a self-rating scale. Multiple regression assessed cognitive prediction for each achievement measure; and partial correlation evaluated overlap. Results: For computations, all predictors accounted for R²=53% variance; nonverbal reasoning and elision were unique predictors (p<.05). For math applications, R²=58%, with unique prediction for nonverbal reasoning, vocabulary, elision, and symmetry span. For word reading, R²=50%, with unique prediction for vocabulary, elision, and reading span. Finally, for reading comprehension, R²=47%, with unique prediction for vocabulary and nonverbal reasoning. Regarding overlap, computations and word reading correlated r=.50, and math applications and reading comprehension r=.57, which is higher than a recent meta-analysis (Unal et al., 2023). Language was the strongest contributor of overlap; these variables reduced the correlation for foundational achievement by 50%, and for complex achievement, by 32%. Other domains accounted for little overlap, despite significant zero-order correlations. Substantive results were generally similar when covariates were considered. Conclusions: Individual prediction was dominated by language, nonverbal reasoning, and working memory variables. Math and reading performances were strongly related, and language was the strongest predictor of this overlap, which is only partially consistent with extant literature but adds context and generalization for CC students. Attention and processing speed were only weakly related to performance, which may reflect the overlearned nature of these skills at this level. Future work might need to include more malleable factors (e.g., motivation), as well as broader views of achievement (e.g., course grades).

Poster

02/16/2024
01:45 pm - 03:00 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 08: Cognition | Cognitive Reserve Variables

Final Abstract #13

Cognition and Math and Reading Overlap in Community College Students

Paul Cirino, University of Houston, Houston, United States
Cassidy Salentine, University of Houston, Houston, United States
Cristina Boada, University of Houston, Houston, United States
Juliana Wall, University of Houston, Houston, United States

Category: Learning Disabilities/Academic Skills

Keyword 1: pediatric neuropsychology
Keyword 2: academic skills
Keyword 3: learning

Objective:

Math and reading are related at the disability level and along the continuum of skill (Cirino, 2022). Cognitive correlates of math and reading in children are well-known separately, with a recent focus on the reason for their overlap. However, less is known about these issues in community college (CC) students despite more than half of post-secondary education occurring at this level. Here we assess cognitive predictors of math and reading (language, working memory, processing speed, nonverbal reasoning, attention) in CC students, outcome overlap, and the extent that predictors account for overlap. We expect all predictors to relate to achievement, with language and working memory as the strongest predictors, and accounting for the most overlap. We also expect more overlap and stronger prediction for complex outcomes (reading comprehension and math applications) relative to foundational skills (word reading and computations).

Participants and Methods:

Participants were 94 CC students enrolled in their first math class. Approximately half the students were taking developmental coursework. Participants were administered four KTEA-3 measures: Letter-Word Reading, Reading Comprehension, Math Computation, and Math Concepts and Application. Language consisted of Vocabulary (K-BIT-2), and Elision and Rapid Naming subtests of the CTOPP-2. Working memory was assessed with two complex span measures (Symmetry Span and Reading Span). Processing speed was measured with the WAIS-IV, and nonverbal reasoning with the K-BIT-2. Attention was assessed via a researcher-designed continuous performance task and a self-rating scale. Multiple regression assessed cognitive prediction for each achievement measure; and partial correlation evaluated overlap.

Results:

For computations, all predictors accounted for R²=53% variance; nonverbal reasoning and elision were unique predictors (p<.05). For math applications, R²=58%, with unique prediction for nonverbal reasoning, vocabulary, elision, and symmetry span. For word reading, R²=50%, with unique prediction for vocabulary, elision, and reading span. Finally, for reading comprehension, R²=47%, with unique prediction for vocabulary and nonverbal reasoning. Regarding overlap, computations and word reading correlated r=.50, and math applications and reading comprehension r=.57, which is higher than a recent meta-analysis (Unal et al., 2023). Language was the strongest contributor of overlap; these variables reduced the correlation for foundational achievement by 50%, and for complex achievement, by 32%. Other domains accounted for little overlap, despite significant zero-order correlations. Substantive results were generally similar when covariates were considered.

Conclusions:

Individual prediction was dominated by language, nonverbal reasoning, and working memory variables. Math and reading performances were strongly related, and language was the strongest predictor of this overlap, which is only partially consistent with extant literature but adds context and generalization for CC students. Attention and processing speed were only weakly related to performance, which may reflect the overlearned nature of these skills at this level. Future work might need to include more malleable factors (e.g., motivation), as well as broader views of achievement (e.g., course grades).