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

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Title: Using Multivariate Adaptive Regression Splines to Predict Lexical Characteristics' Influence on Word Learning in First through Third Graders
Language: English
Authors: Peters-Sanders, Lindsey (ORCID 0000-0003-2868-7492), Sanders, Houston (ORCID 0000-0003-2201-0093), Goldstein, Howard (ORCID 0000-0003-3270-2739), Ramachandran, Kandethody (ORCID 0000-0002-6332-2758)
Source: Journal of Speech, Language, and Hearing Research. Feb 2023 66(2):589-604.
Availability: American Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
Peer Reviewed: Y
Page Count: 16
Publication Date: 2023
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R324L060023
R324A200179
Document Type: Journal Articles
Reports - Research
Education Level: Early Childhood Education
Elementary Education
Grade 1
Primary Education
Grade 3
Grade 2
Descriptors: Prediction, Grade 1, Grade 3, Elementary School Students, Vocabulary Development, Grade 2, Intervention, Word Frequency, Age Differences, Multivariate Analysis, Teaching Methods, Scores, Validity, Guidelines, Longitudinal Studies, Goodness of Fit, Phonology, Phonemes, Predictor Variables, Learning Processes, Low Income Students, Institutional Characteristics
DOI: 10.1044/2022_JSLHR-22-00165
ISSN: 1092-4388
1558-9102
Abstract: 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. [For the correspoinding grantee submission, see ED628272.]
Abstractor: As Provided
Notes: https://doi.org/10.6084/m9.figshare.16699594.v1
IES Funded: Yes
Entry Date: 2023
Accession Number: EJ1380701
Database: ERIC
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  Data: Using Multivariate Adaptive Regression Splines to Predict Lexical Characteristics' Influence on Word Learning in First through Third Graders
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  Data: <searchLink fieldCode="AR" term="%22Peters-Sanders%2C+Lindsey%22">Peters-Sanders, Lindsey</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2868-7492">0000-0003-2868-7492</externalLink>)<br /><searchLink fieldCode="AR" term="%22Sanders%2C+Houston%22">Sanders, Houston</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2201-0093">0000-0003-2201-0093</externalLink>)<br /><searchLink fieldCode="AR" term="%22Goldstein%2C+Howard%22">Goldstein, Howard</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3270-2739">0000-0003-3270-2739</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ramachandran%2C+Kandethody%22">Ramachandran, Kandethody</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6332-2758">0000-0002-6332-2758</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Speech%2C+Language%2C+and+Hearing+Research%22"><i>Journal of Speech, Language, and Hearing Research</i></searchLink>. Feb 2023 66(2):589-604.
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  Data: American Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
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  Data: 10.1044/2022_JSLHR-22-00165
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  Data: 1092-4388<br />1558-9102
– Name: Abstract
  Label: Abstract
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  Data: 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. [For the correspoinding grantee submission, see ED628272.]
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