The most widely used multivariate statistical models in the social and behavioral sciences involve linear structural relations among observed and latent variables. In practice, these variables are generally nonnormally distributed, and hence classical multivariate analysis, based on multinormal error-free variables having no simultaneous interrelations, is not adequate to deal with such data. Since structural relations among variables imply a structure for the multivariate product moments of the variables, general methods for the analysis of mean and covariance structures have been proposed to estimate and test particular model structures. Unfortunately, extant statistical tests, such as the likelihood ratio test (LRT) and a test based on asymptotically distribution free (ADF) covariance structure analysis, have been found to be virtually useless in practical model evaluation at finite sample sizes with nonnormal data. For example, in one condition of a simulation on confirmatory facto...

The concept of deep learning is not new to higher education. However, deep learning has drawn more attention in recent years as institutions attempt to tap their student’s full learning potential. To more fully develop student talents, many campuses are shifting from a traditional passive, instructor-dominated pedagogy to active, learner-centered activities. Using exploratory and confirmatory factor analysis on multiple years of data from the National Survey of Student Engagement, this study examines the structure and characteristics of items about student uses of deep approaches to learning. Institutions and researchers can use the resulting scales to assess and investigate deep approaches to learning. Deep Approaches to Learning 3 Measuring Deep Approaches to Learning Using the National Survey of Student Engagement Colleges and universities are devoting substantial effort to design active, learner-centered teaching and learning environments. Findings from the National Survey of Student Engagement

This paper reports on time 1 data only (time 2 data will not be available until 2003). Three government office buildings in two cities were surveyed, with a total of 419 employees and their workstations participating. While research staff conducted extensive measurements of ventilation, temperature, noise, lighting, and descriptive characteristics of the workstation, the workstation occupant completed a 27-item questionnaire on a handheld computer. The questionnaire included 18 individual ratings of satisfaction with environmental features, a 2-item index of overall environmental satisfaction, and a 2-item index of job satisfaction. This paper reports on the methodology and on analyses of the underlying factor structure of the 18 individual environmental features ratings, and of a model incorporating environmental and job satisfaction in relation to these ratings. Relationships between environmental features ratings and characteristics of the workstations, and specific relationships to other physical conditions in the workstation, will follow in subsequent papers. The sample was divided into two random groups for exploratory and confirmatory factor analysis. Exploratory factor analysis using oblimin rotation revealed three factors, interpreted as Satisfaction with Privacy, Satisfaction with Lighting and Satisfaction with Ventilation. Confirmatory factor analysis using structural equation modelling (on EQS) supported the three-factor model. The variables loading on each latent variable are as follows: Satisfaction with Privacy: [satisfaction with...] visual privacy, conversational privacy, amount of noise from others' conversations, amount of background noise; amount of distraction, workstation size, degree of enclosure, ability to alter conditions; distance between cowo...

As the Web becomes a part of peoples ’ everyday lives, there is a growing need to understand user behaviour on the Web. Recently, the flow construct has been proposed as important for understanding the nature of user online experience. Researchers assert that the benefits of flow online include increased learning, exploratory and positive behavior, positive subjective experience, and perceived sense of control over their interaction. Overall, flow could affect outcomes such as navigation patterns and repeat visits on commercial Web sites. Although widely studied over the past years, a review of the literature indicates discrepancies among various flow models and some unclear conceptualization and operationalization of the construct. This paper examined flow according to two specific conceptualizations with respect to its measurement, and tests each conceptualization in an identical nomological network. The results indicate that there is better fit of a reflective flow model compared with a formative flow model to the study data. The results of the study may aid in the understanding of the relationships between the higher order flow construct and its first order dimensions, which may help inform system designers to better assess flow and, thus, be more conducive to flow. Keywords: Computer-Mediated Environment, Flow, Multidimensionality, Web 1.

This research examines a model of school violence and disruption using structural equation modeling. Data are analyzed from the 1995 School Crime Supplement to the National Crime Victimization Survey which includes 9,954 completed interviews of students age 12 to 19 in schools across the United States. Students were asked questions about school rules and procedures, knowledge of and personal experience with violence against students and teachers, accessibility of drugs, gang presence, other violence or disruption in the school, as well as individual fear relating to being victimized and self-protective actions they had taken. The analysis used a subset of 6947 subjects, age, 12 to 19, all of whom attended public schools for at least five of the last six months prior to the survey. A construct of "System of Law " included a composite (derived) measured variable for student knowledge of school rules and consequences for infractions along with another composite measured variable demonstrating implementation of rules. The "System of Law " construct was shown to lead to less disorder. On the other hand, a construct of "Secure Building, " that included composite measured variables showing physical (metal detectors, locked doors, etc.) and personnel-based (security guards, etc.) actions to run a secure building, led to more disorder. Implications for school policy and future research are discussed. School violence and disruption is a major concern of parents, students, educators, political leaders and others in the community. The public's understanding of school violence and disruption is a function of fact and perception. Furlong and Morrison (1994) report that data gathering methods to assess school violence vary considerably and that perceived violence is consistently reported at higher levels than self-reports of violent incidents. Methodologically, studies on school violence usually take a [confirmatory] hypothesis verification approach. That is, school violence is assumed to exist and survey questions elicit responses that confirm its existence.

Children raised in economic poverty have below average development of language and are over represented among children with reading difficulties. What is the relation between language and literacy development for this population? Do children from low-income families fail at reading for the same reasons as children from middle-class families? Are there subgroups of children among readers from low-income backgrounds whose reading is impaired because of unique disabilities? Results from longitudinal research with a large sample of children in poverty support the conclusions that a) the connection between language and literacy skills is present strongly during the pre-kindergarten period but language and literacy develop independently during the first years of formally learning to read; b) the same skills factors predict reading success and failure in a low-income sample as have been identified for middle-income samples; c) a subgroup of 20% - 25% of children in a low-income sample may suf...

This study examines the relationships between student engagement in the first year of college and three desirable outcomes of undergraduate education. Student engagement is a domain of constructs that measures both the time and energy students devote to educationally purposeful activities and how students perceive different facets of the institutional environment that facilitate and support their learning. The three outcomes represent a portion of what is meant by success in the first year experience, namely obtaining good grades, acquiring intellectual skills that are important for future academic achievement and success in the professional world, and gaining knowledge of a general nature in step with the commonly embraced liberal arts mission of the general curriculum. The study is a secondary analysis of existing data utilizing two primary data sources: student responses to the fourth edition of the College Student Experiences Questionnaire and student records maintained by Indiana University Bloomington. Structural equation modeling (SEM) was employed to model the complex relationships between the students ’ precollege characteristics, engagement behaviors and perceptions, and the outcome variables. The findings point to four conclusions: (a) different forms of engagement are precursors to different outcomes, (b) different forms of engagement interact to contribute to desired outcomes, (c) high expectations coupled with adequate support are requisite conditions for learning and development in the first college year, and (d) grades do not necessarily represent how much students believe they have learned. Implications for research, policy and practice are also offered. 2 The Relationship between Student Engagement and Selected Desirable Outcomes

The Dissertation Committee for Zeynep Cemalcilar certifies that this is the approved version of the following dissertation:

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An earlier version of this work was presented in a symposium conducted at the 2005 annual meeting of the American Education Research Association. Funding for the early phases of this work was provided through grants to the third author from the Society for the Study of School Psychology and the University at Albany. The authors acknowledge Bill Disch for his support with statistical analysis. Address correspondence to: John Hitchcock, Caliber, an ICF International Company,