Latent profiles of problem behavior within learning, peer, and teacher contexts: Identifying subgroups of children at academic risk across the preschool year

Bulotsky‐Shearer, Rebecca J.; Bell, Elizabeth R.; Domínguez, Ximena

doi:10.1016/j.jsp.2012.08.001

Cited by 51 publications

(37 citation statements)

References 80 publications

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“…Consistent with short-term studies linking social withdrawal with low levels of learning engagement and reduced academic attainment during the preschool years (Bulotsky-Shearer et al, 2012;Fantuzzo et al, 2003;Konold & Pianta, 2005), the present study demonstrated a unique pathway between social withdrawal and literacy skills across three academic years at the start of elementary school. The present model mirrors and supports findings that suggest that social withdrawal may be related to academic skills and learning behaviors at school entry (Dominguez et al, 2010;Luo, Hughes, Liew, & Kwok, 2009).…”

Section: Developmental Modelsupporting

confidence: 89%

“…In other words, the literacy skills that children had as they started school did not affect their subsequent social withdrawal. One reason for the failure to confirm this hypothesis may have been that the composite items used in the present investigation do not assess emotional states in a manner comparable with other studies (Grills‐Taquechel, Fletcher, Vaughn, & Stuebing, ; Ladd et al., ), and that bidirectional effects would have been better captured with more direct assessments of social withdrawal.…”

Section: Discussionmentioning

confidence: 64%

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Kindergarten Social Withdrawal and Reading Achievement: A Cross-Lagged Path Model for at-Risk Learners

et al. 2016

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The association between social withdrawal, school adjustment, and academic functioning in preschool and school entry is well‐established. Children who experience social withdrawal in primary grades are at risk for decreased academic performance. The bidirectional relationships among early literacy and social withdrawal in primary grades have not been examined to date. The present study used a cross‐lagged model to examine the relationship between social withdrawal and early literacy skills from kindergarten to second grade (N = 137). Results indicated that kindergarten social withdrawal predicted second grade reading achievement after controlling for prior literacy skill acquisition. Bidirectional influence hypotheses were not confirmed in the present study.

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Section: Developmental Modelsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 64%

Kindergarten Social Withdrawal and Reading Achievement: A Cross-Lagged Path Model for at-Risk Learners

et al. 2016

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“…This procedure estimates the probability of profile membership and the regression coefficients of the covariates simultaneously, thereby overcoming the potential bias that is caused by poor entropies in directly using the most likely profile membership as a grouping variable (Masyn, 2013). Since the outcome variable (i.e., the latent profile) is categorical, this procedure conducts a (multinomial) logistic regression with one profile as the reference group (Bulotsky-Shearer, Bell, & Dominguez, 2012). We finally added students' CIL achievement as a distal outcome to the LPA regression model (Figure 1).…”

Section: Latent Profile Analysis With Regression and A Distal Outcomementioning

confidence: 99%

Students' profiles of ICT use: Identification, determinants, and relations to achievement in a computer and information literacy test

Scherer

Rohatgi

Hatlevik

2017

Computers in Human Behavior

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Current debates on students' use of information and communication technology (ICT) have brought to attention profiles and purposes of ICT use in either school-related or recreational contexts. Examining these two contexts at the same time, the present study seeks to identify student profiles of ICT use on the basis of the Norwegian International Computer and Information Literacy Study (ICILS) 2013 data (N = 2,426). In order to explore profiles of ICT use in schools and at home for different purposes such as recreation, study purposes, exchanging information, and social communication, we take a person-centered approach and apply latent profile analysis. These analyses revealed two independent user profiles and showed that background characteristics (i.e., gender, immigration status) and motivational constructs (i.e., self-efficacy, interest, and enjoyment in ICT) play a significant role in determining profile membership. Significant differences between the user profiles in students' computer and information literacy test performance did not exist. Given that the coverage of ICT at home and in schools has increased substantially over the last decades, the identification of user profiles informs teachers and parents about whether or not students exploit these opportunities to the same extent. Implications for future research and practice are discussed.

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“…For example, latent profile analysis has been used to identify different types of at-risk children, based on their similarities in problem behaviors, such as socially and academically disruptive children and socially and academically disengaged children (Bulotsky-Shearer, Bell, & Domínguez, 2012). Subsequent analyses revealed a relation between at-risk profiles and learning trajectories, providing insight into how children with distinct combinations of problem behaviors have different academic growth patterns.…”

Section: Latent Class and Latent Profile Models: New Ways To Understamentioning

confidence: 99%

Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis

Hickendorff

Edelsbrunner

McMullen

et al. 2018

Learning and Individual Differences

198

118

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Highlights• learning is often multidimensional, heterogeneous, and discontinuous• traditional statistical analyses are limited in capturing this complexity• latent class and latent profile models identify subgroups of learners• latent transition models characterize discontinuous, non-linear, learning paths• these models contribute to our understanding of learning and individual differences 3 Informative Tools for Characterizing Individual Differences in Learning: Latent Class, Latent Profile, and Latent Transition AnalysisThis article gives an introduction to latent class, latent profile, and latent transition models for researchers interested in investigating individual differences in learning and development. The models allow analyzing how the observed heterogeneity in a group (e.g., individual differences in conceptual knowledge) can be traced back to underlying homogeneous subgroups (e.g., learners differing systematically in their developmental phases). The estimated parameters include a characteristic response pattern for each subgroup, and, in the case of longitudinal data, the probabilities of transitioning from one subgroup to another over time. This article describes the steps involved in using the models, gives practical examples, and discusses limitations and extensions. Overall, the models help to characterize heterogeneous learner populations, multidimensional learning outcomes, nonlinear learning pathways, and changing relations between learning processes. The application of these models can therefore make a substantial contribution to our understanding of learning and individual differences.

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Latent profiles of problem behavior within learning, peer, and teacher contexts: Identifying subgroups of children at academic risk across the preschool year

Cited by 51 publications

References 80 publications

Kindergarten Social Withdrawal and Reading Achievement: A Cross-Lagged Path Model for at-Risk Learners

Kindergarten Social Withdrawal and Reading Achievement: A Cross-Lagged Path Model for at-Risk Learners

Students' profiles of ICT use: Identification, determinants, and relations to achievement in a computer and information literacy test

Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis

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