When Complexity Is Your Friend: Modeling the Complex Problem Space of Vocabulary

Abstract

The history of vocabulary research has specified a rich and complex construct, resulting in calls for vocabulary research, assessment, and instruction to take into account the complex problem space of vocabulary. At the intersection of vocabulary theory and assessment modeling, this paper suggests a suite of modeling techniques that model the complex structures present in vocabulary data in ways that can build an understanding of vocabulary development and its links to instruction. In particular, we highlight models that can help researchers and practitioners identify and understand construct-relevant and construct-irrelevant aspects of assessing vocabulary knowledge. Drawing on examples from recent research and from our own three-year project to develop a standardized measure of language and vocabulary, we present four types of confirmatory factor analysis (CFA) models: single-factor, correlated-traits, bi-factor, and tri-factor models. We highlight how each of these approaches offers particular insights into the complex problem space of assessing vocabulary in ways that can inform vocabulary assessment, theory, research, and instruction. Examples include identifying construct-relevant general or specific factors like skills or different aspects of word knowledge that could link to instruction while at the same time preventing an overly-narrow focus on construct-irrelevant factors like task-specific or word-specific demands. Implications for theory, research, and practice are discussed.

Monster, P.I.: Validation Evidence for an Assessment of Adolescent Language That Assesses Vocabulary Knowledge, Morphological Knowledge, and Syntactical Awareness

“…But performance also is unique, reflecting distinct aspects of language that are likely differentially important to making meaning. This idea of using modeling techniques to use the complexity of a construct like language to provide additional understandings and instructional guidelines is highlighted by Goodwin et al (2018). Our language model considers construct-relevant versus construct-irrelevant variance when modeling.…”

Multidimensional morphological assessment for middle school students

“…Overall, the complexity of morphological knowledge has been seen as a challenge in terms of defining, assessing and identifying the role of morphological knowledge in literacy outcomes, specifically reading comprehension (Nagy et al, 2014). In contrast, Goodwin et al (2018) suggest that this complexity can be an asset in that when channelled via the appropriate modelling technique, the complexity of morphological knowledge can build deeper understandings of the construct, its relationship to outcomes and links to instruction. This can be performed by identifying construct-relevant versus construct-irrelevant variance, which related to morphology would involve morphological skills that could be instructionally relevant.…”

From the Editors

“…What is novel is that the researchers specifically contrasted the roles of morphological awareness and morphological analysis, the first referring to the awareness of and ability to manipulate morphemes (units of meaning) in language and the second referring to the use of morphemes to infer the meaning of unfamiliar morphologically complex (multimorphemic) words. In other words, these authors build on other work suggesting the multidimensionality of morphological awareness (Goodwin, Petscher, Carlisle, & Mitchell, ; Goodwin et al., ) to show that analysis versus use and application could be differentially supportive. Controlling for word reading, vocabulary, phonological awareness, nonverbal ability, and age, multivariate autoregressive path analysis revealed that morphological analysis, but not morphological awareness, predicted gains in reading comprehension.…”