Using Multivariate Adaptive Regression Splines to Predict Lexical Characteristics' Influence on Word Learning in First through Third Graders

• Published in: Grantee Submission Vol. 66; no. 2; pp. 589 - 604
• Main Authors: Peters-Sanders, Lindsey, Sanders, Houston, Goldstein, Howard, Ramachandran, Kandethody
• Format: Journal Article
• Language: English
• Published: United States 13.02.2023
• Subjects: Age Differences; Child; Elementary School Students; Goodness of Fit; Grade 1; Grade 2; Grade 3; Guidelines; Humans; Institutional Characteristics; Intervention; Learning; Learning Processes; Longitudinal Studies; Low Income Students; Multivariate Analysis; Phonemes; Phonetics; Phonology; Predictor Variables; Scores; Teaching Methods; Validity; Verbal Learning; Vocabulary; Vocabulary Development; Word Frequency
• ISSN: 1092-4388; 1558-9102
• DOI: 10.1044/2022_JSLHR-22-00165

Purpose: Identifying appropriate targets for vocabulary instruction and determining the optimal sequence for instruction continue to be a challenge. The purpose of this study is to investigate how previously studied lexical characteristics collectively influence children's word learning. Method: A secondary data analysis was conducted using the word learning results of 350 first-, second-, and third-grade students who participated in an investigation examining the effects of a supplemental vocabulary intervention. We investigated the influence of the following lexical characteristics on the learning of 377 words: word frequency, level of concreteness, phonotactic probabilities, neighborhood density, and age of acquisition using multivariate adaptive regression splines (MARS). Results: MARS modeled the influence lexical characteristics had on word learning and determined the relative importance of each variable for each grade-level model. Results revealed age of acquisition was the most important factor related to word learning in all grades, but contributions of other lexical characteristics and their level of importance differed across models. All respective models fit well, with root-mean-square error values ranging from 0.11 to 0.15 and generalized cross validation scores of 0.01 and 0.03. Conclusions: Nuanced information from the MARS analysis provides insights into how lexical characteristics affect word learning differently for children in different grade levels. This information is key to understanding the vocabulary acquisition of school-aged children. The findings from this research have the potential to inform the development of a word selection framework that will organize vocabulary targets into an appropriate sequence based on relevant predictors.