A Structural Equation Model for the School Reinforcement Survey Schedule: Italian and American Early Adolescents

Holmes, George R.; Galeazzi, Aldo; Franceschina, Emilio; McNulty, George F.; Forand, Angela Q.; Stader, Sandra R.; Myers, deRosset; Wright, Harry H.

doi:10.1023/b:jobe.0000023659.05536.03

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Besides, promax oblique rotation was used since there was no basis for assuming that the latent variables should not be correlated. A similar approach was adopted in [69]. Hence, after performing the EFA and using the promax rotation, we identified 11 constructs composed by a total of 53 variables with significant factor loadings.…”

Section: ) Factor Analysismentioning

confidence: 99%

Measuring Critical Success Factors for Six Sigma in Higher Education Institutions: Development and Validation of a Surveying Instrument

et al. 2020

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Critical success factors are key elements that enable the success of projects. This research work proposes the design and validation of an instrument to evaluate the implementation of six sigma critical success factors during improvement projects in higher education institutions. Eleven critical success factors were selected from the literature on the six sigma methodology, including managerial participation and commitment, six sigma linkage with the institutional strategy, six sigma linkage with suppliers, communication, and team member selection, among others. The instrument was validated among Mexican higher education institutions, from which 743 surveys were collected. Namely, the instrument was administered to experienced improvement project developers. Then, the collected data were analyzed, first by means of an exploratory factor analysis, and later with a confirmatory factor analysis using software program SPSS Amos R. Our results demonstrate that the proposed instrument is statistically valid, so it can be used by higher education institutions to evaluate how Six Sigma critical success factors are handled during improvement projects development. Similarly, the survey can help universities detect areas of opportunity when adopting the six sigma methodology and fit models to evaluate how critical success factors interact among them to achieve the expected results of improvement projects. INDEX TERMS Confirmatory factor analysis, construct validation, higher education, improvement projects, six sigma.

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Section: ) Factor Analysismentioning

confidence: 99%

Measuring Critical Success Factors for Six Sigma in Higher Education Institutions: Development and Validation of a Surveying Instrument

et al. 2020

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“…It is possible that some privileges are more desirable for particular youth within the residential setting. Researchers have identified some group differences in preference between genders, cultures (Italian, Japanese, and American), and ages (e.g., Galeazzi, Franceschina, Cautela, Holmes, & Sakano, 1998;Holmes et al, 2004;Pellegrini, 1992). For example, in a study examining preference for play, Pellegrini (1992) found that younger boys were more likely to prefer playing outdoors than older boys or girls.…”

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confidence: 99%

Group-Based Preference Assessment for Children and Adolescents in a Residential Setting: Examining Developmental, Clinical, Gender, and Ethnic Differences

Volz

Cook

2009

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This study examines developmental, clinical, gender, and ethnic group differences in preference in residentially placed children and adolescents. In addition, this study considers whether residentially placed youth prefer stimuli currently being used as rewards as part of a campuswide token economy system and whether youth would identify preferred stimuli that are not currently offered. The article discusses a survey devised specifically for the purpose of this study. Stimuli currently offered as rewards are listed and rated on a 5-point Likert-type scale. Results indicate that the majority of stimuli available within the token economy system were rated as preferred. Also, significant developmental, clinical, gender, and ethnic group differences are found, indicating the benefit of considering group-level characteristics when designing and implementing a groupwide token economy system. The implications of the results and directions for future research are discussed.

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A Structural Equation Model for the School Reinforcement Survey Schedule: Italian and American Early Adolescents

Cited by 2 publications

References 14 publications

Measuring Critical Success Factors for Six Sigma in Higher Education Institutions: Development and Validation of a Surveying Instrument

Measuring Critical Success Factors for Six Sigma in Higher Education Institutions: Development and Validation of a Surveying Instrument

Group-Based Preference Assessment for Children and Adolescents in a Residential Setting: Examining Developmental, Clinical, Gender, and Ethnic Differences

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