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Zhongdi Wu; Eric Larson; Makoto Sano; Doris Baker; Nathan Gage; Akihito Kamata – Grantee Submission, 2023
In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…
Descriptors: Prediction, Vocabulary Development, English (Second Language), Second Language Learning
Catarina Vales; Patience Stevens; Anna V. Fisher – Grantee Submission, 2020
Organized semantic representations encoding across- and within-domain distinctions are a hallmark of mature cognition, and understanding how they change with experience and learning is a key endeavor in developmental science. Existing computational modeling studies provide a mechanistic framework for understanding how structured semantic…
Descriptors: Child Development, Semantics, Developmental Stages, Prediction
Goodwin, Amanda P.; Petscher, Yaacov; Tock, Jamie – Grantee Submission, 2021
Background: Middle school students use the information conveyed by morphemes (i.e., units of meaning such as prefixes, root words and suffixes) in different ways to support their literacy endeavours, suggesting the likelihood that morphological knowledge is multidimensional. This has important implications for assessment. Methods: The current…
Descriptors: Morphology (Languages), Morphemes, Middle School Students, Knowledge Level