scholarly journals Promoting children's learning and development in conflict-affected countries: Testing change process in the Democratic Republic of the Congo

2016 ◽  
Vol 29 (1) ◽  
pp. 53-67 ◽  
Author(s):  
J. Lawrence Aber ◽  
Carly Tubbs ◽  
Catalina Torrente ◽  
Peter F. Halpin ◽  
Brian Johnston ◽  
...  
Keyword(s):  
Classroom Environment ◽  
Structural Equation ◽  
Democratic Republic ◽  
Theory Of Change ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Learning And Development ◽  
Children’S Learning ◽  
Republic Of The Congo ◽  
Children's Learning

AbstractImproving children's learning and development in conflict-affected countries is critically important for breaking the intergenerational transmission of violence and poverty. Yet there is currently a stunning lack of rigorous evidence as towhetherandhowprograms to improve learning and development in conflict-affected countries actually work to bolster children's academic learning and socioemotional development. This study tests a theory of change derived from the fields of developmental psychopathology and social ecology about how a school-based universal socioemotional learning program, the International Rescue Committee's Learning to Read in a Healing Classroom (LRHC), impacts children's learning and development. The study was implemented in three conflict-affected provinces of the Democratic Republic of the Congo and employed a cluster-randomized waitlist control design to estimate impact. Using multilevel structural equation modeling techniques, we found support for the central pathways in the LRHC theory of change. Specifically, we found that LRHC differentially impacted dimensions of the quality of the school and classroom environment at the end of the first year of the intervention, and that in turn these dimensions of quality were differentially associated with child academic and socioemotional outcomes. Future implications and directions are discussed.

Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

2019 ◽  
Vol 50 (1) ◽  
pp. 24-37
Author(s):  
Ben Porter ◽  
Camilla S. Øverup ◽  
Julie A. Brunson ◽  
Paras D. Mehta
Keyword(s):  
Structural Equation Modeling ◽  
Social Relations ◽  
Latent Variables ◽  
Structural Equation ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Complete Understanding ◽  
Social Relations Model ◽  
Flexible Framework ◽  
Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

Impulsivity, Affect, and Stress in Daily Life: Examining a Cascade Model of Urgency

2019 ◽  
Author(s):  
Brinkley M. Sharpe ◽  
Leonard Simms ◽  
Aidan G.C. Wright
Keyword(s):  
Negative Affect ◽  
Structural Equation ◽  
Psychiatric Patients ◽  
Cascade Model ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Daily Stress ◽  
Daily Diary Study ◽  
Daily Affect ◽  
Multilevel Structural Equation

Using multilevel structural equation modeling, we examined within- and between-person predictors of daily impulsivity, with a particular focus on testing a cascade model of affect and daily stress in a 100-day daily diary study of 101 psychiatric patients with personality disorder diagnoses. On average (i.e., fixed effect), within-person increases in daily stress were associated with increased daily impulsivity, both independently and as accounted for by positive associations with increased negative and positive affect. Higher Personality Inventory for DSM-5 (PID-5) Impulsivity scores were associated with amplified within-person links between impulsivity and daily stress and negative affect, but not the links between daily stress and either positive or negative affect. The results of this cascade model are consistent with the hypothesized link between daily affect and stress and daily impulsivity while providing further evidence for the validity of the PID-5 Impulsivity scale and its ability to predict daily impulsivity above and beyond fluctuations in affect and stress.

Learning at work: a model of learning and development for younger workers

2020 ◽  
pp. 1-20
Author(s):  
Robyn Mason ◽  
David Brougham
Keyword(s):  
Structural Equation ◽  
Social Cognitive ◽  
Cognitive Theory ◽  
Work Environments ◽  
Equation Modeling ◽  
Learning And Development ◽  
Baby Boomer Generation ◽  
Younger Workers ◽  
Learning At Work ◽  
Work Environment Factors

Abstract In rapidly changing work environments, individuals need a willingness and ability to learn new skills and knowledge to contribute to their organization's goals and their own employability. As the baby-boomer generation begins to exit the workplace, organizations need to pay attention to developing the capability of younger, novice workers who will increasingly comprise the core workforce of the future. The present study, grounded in social cognitive theory, develops and examines a model of learning and development for younger workers. In total, 1,732 employees in New Zealand aged 16–24 years completed a survey relating to their perceptions, beliefs, and intentions regarding learning and development. The results from structural equation modeling show that individual and work-environment factors both influence younger workers' developmental intentions but affect this through different pathways. The study contributes to a better understanding of the development process for younger workers and offers implications for management based on these findings.

The Role of an Empowering Motivational Climate on Pupils’ Concentration and Distraction in Physical Education

2021 ◽  
pp. 1-11
Author(s):  
Maxime Mastagli ◽  
Aurélie Van Hoye ◽  
Jean-Philippe Hainaut ◽  
Benoît Bolmont
Keyword(s):  
Physical Education ◽  
Negative Affect ◽  
Structural Equation ◽  
Psychological Needs ◽  
Motivational Climate ◽  
Need Satisfaction ◽  
Basic Psychological Needs ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Positive And Negative Affect

Purpose: The present study investigated the relationship between an empowering motivational climate and pupils’ concentration and distraction in physical education, mediated by basic psychological needs satisfaction and by positive and negative affect. Method: The participants were 425 French pupils (Mage = 15.36, SDage = 0.82) from 21 high schools, who filled in a questionnaire regarding the study variables. This cross-sectional study used multilevel structural equation modeling to examine the hypothesized relationships. Results: Good fit indices were found in the data from the theoretical model. An empowering motivational climate was found to be related to concentration. Competence need satisfaction was related to concentration and distraction. This association was mediated by positive and negative affect, which in turn was related to concentration and distraction. Conclusion: Teachers can improve pupils’ concentration and positive affect and reduce distraction and negative affect by supporting an empowering motivational climate and fostering competence need satisfaction.

scholarly journals Analyzing Organizational Growth in Repeated Cross-Sectional Designs Using Multilevel Structural Equation Modeling

Methodology ◽  
2017 ◽  
Vol 13 (3) ◽  
pp. 83-97 ◽  
Author(s):  
Jan Hochweber ◽  
Johannes Hartig
Keyword(s):  
Structural Equation Modeling ◽  
Growth Curve ◽  
Cross Sections ◽  
Structural Equation ◽  
Organizational Level ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Organizational Growth ◽  
Multilevel Structural Equation ◽  
Level Variable

Abstract. In repeated cross-sections of organizations, different individuals are sampled from the same set of organizations at each time point of measurement. As a result, common longitudinal data analysis methods (e.g., latent growth curve models) cannot be applied in the usual way. In this contribution, a multilevel structural equation modeling approach to analyze data from repeated cross-sections is presented. Results from a simulation study are reported which aimed at obtaining guidelines on appropriate sample sizes. We focused on a situation where linear growth occurs at the organizational level, and organizational growth is predicted by a single organizational level variable. The power to identify an effect of this organizational level variable was moderately to strongly positively related to number of measurement occasions, number of groups, group size, intraclass correlation, effect size, and growth curve reliability. The Type I error rate was close to the nominal alpha level under all conditions.

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