The purpose of this study was to assess the measures of the Science Laboratory Environment Inventory (SLEI), an existing classroom environment measurement instrument, to provide up-to-date norms and validation evidence for a U.S. secondary school population. This instrument’s measures were established as a means of examining students’ perceptions of their learning environment in science classrooms, and subsequently providing indicators of performance. Pedagogical changes have taken place in the science classroom fostered by the National Science Standards. This study included an examination of the SLEI measures using Mesick’s validity framework including an in-depth analysis of the instrument’s content, substance, structure, generalizability and external validity. Rasch measurement theory was employed to investigate specific components of the instrument including item fit, rating scale function, dimensionality and individual performance information. Three hundred and fifty five high school science students completed the SLEI. Structural equation modeling was used to assess the dimensional structure of the measures of the instrument. Analyses revealed that a multi-dimensional model encompassing five distinct factors and excluding negatively worded items best characterized the SLEI measures. Multidimensional measures created by scaling the data to the Multidimensional Random Coefficients Multinomial Logit (Rasch) Model exhibited suitable rating scale structure, item quality, and reliability of separation. Analyses by academic grouping revealed that students in high achieving courses had a more favorable perception of all aspects of their learning environments when compared to students in the regular courses. In addition, student perceptions of the lab were influenced by the extent of students’ experience learning science. To determine whether differences observed by grade level could be attributable to biology learning experience versus experience in school, additional analyses were completed. The analysis revealed that differences in perception were consistent across academic achievement groups as well as experience level by first year and beyond (course level) rather than by grade level. This validation study has provided additional and up-to-date evidence concerning the validity of SLEI measures. Coupled with the existing research revealing positive correlations between student perceptions of their learning environments and their academic achievement, the outcomes reported here provide a foundation for future assessment of the relationship between classroom environment and student achievement. / Ph. D.

Yes / The study presents the Italian adaptation of the Personal and General Belief in a Just World (P-BJW and G-BJW) Scales. Dalbert and colleagues developed these scales to capture the belief in a just world for oneself and a just world in general. After the translation and back-translation, the P-BJW and G-BJW scales were administered first to a pilot sample of 213 university students and then to a national sample of 2683 Italian people. Results showed that it was necessary to make some revisions to the predicted two correlated factor structure. These changes entailed correlating the error terms for some manifest variables and removing the first item of the P-BJW factor. The final structure of the P-BJW and G-BJW scales presented satisfactory indexes of model fit as well as high reliability and moderate validity values. Additionally, this structure proved to fit the data better than an alternative one-factor or a bi-factor model with two orthogonal-specific factors. As predicted, well-being strongly predicted scores on the BJW, but age and gender did not. Multigroup comparisons among Northern, Central, and Southern Italy respondents indicated that Italian people interpret scale items equivalently, regardless of their geographical location. Introducing the P-BJW and G-BJW scales to the Italian justice scholarship is very useful to unpack the reasons why Italy reports lower levels of social justice than other European countries and also to investigate the link between justice, well-being, and other socio-psychological variables. / Open access funding provided by Università di Foggia within the CRUI-CARE Agreement.

Psychopathy is a personality disorder that has long been associated with significant behavioral, interpersonal, and affective problems. However, its core components and overall construct continue to be a point of heated debate amongst researchers, despite a robust pool of literature supporting its status as a distinct diagnosis from other personality pathologies. Recently, a subset of scholars have suggested that personality disorders are, in fact, extreme manifestations of normative personality traits and can be adequately identified and modeled utilizing extant measures of general personality. Using a large offender sample, the current study investigated the relationships between psychopathic traits and various domains and facets of general personality, as conceptualized by the Five Factor Model (FFM). The structures of the PCL-R and NEO-FFI-3 were analyzed by comparing a range of structural equation models. The correlations between these measures' domains and facets were also compared to those of extant findings. Furthermore, as previous research has suggested the existence of psychopathic subtypes within this construct, the current study also utilized a person-centered approach to investigate whether these subtypes could be identified within this study's sample and, if so, whether they displayed different profiles on the FFM domains and facets. Results supported arguments that these constructs are related but different from each other, challenging exertions that psychopathy and other personality pathologies can be successfully subsumed within the FFM structure.

This dissertation examined the differences in group mean scores of traditional and pilot groups on the students' motivational beliefs and their intention to pursue majors and careers in engineering. The difference between the two groups was in terms of instruction techniques used. The instructional techniques used for the traditional group was that of traditional engineering design (TED), while the technique used for the pilot group had more features of an active learning approach. Further, it tested the tenability of the domain identification model. The domain identification model was used to understand students' decision-making processes in committing to engineering majors and engineering careers. The data for this study was collected via online survey from first-year engineering students enrolled in an introductory engineering course at a research-intensive university located in southeastern US. The sample sizes of the traditional group and pilot group at the beginning of the semester were 875 and 188, respectively. The sample sizes of the traditional group and pilot group at the end of the semester were 812 and 242, respectively. The mean differences between the two groups were computed using t-tests via SPSS version 22.0. The causality hypothesized among variables in the domain identification model were tested using structural equation modeling (SEM) techniques. The measurement and structural models were estimated using LISREL version 9.1. This study followed the two-step SEM approach that Anderson and Gerbing (1988) suggested. A measurement model with an acceptable fit to the data was obtained followed by an estimation and evaluation of structural models. All the independent sample t-tests were not statistically significant indicating that the mean scores of students in the two groups did not differ significantly on any of the motivational and intention variables. The hypothesized measurement and structural models provided a good fit to the data. A few post-hoc revisions were made to the models. This study brought empirical evidence that the domain identification model can be used to understand students' major-and career-decision making processes. Engineering identification was a better predictor of major intention and career intention compared to engineering program utility, engineering program belonging, and engineering program expectancy. / Ph. D.

This dissertation illuminates patterns across disparate university data sets to identify the insights that may be gained through the analysis of large amounts of disconnected student data on first-year engineering (FYE) students and to understand how FYE instructors use data to inform their teaching practices. Grounded by the Academic Plan Model, which highlights student characteristics as an important consideration in curriculum development, the study brings together seemingly distinct pieces of information related to students' learning, engagement with class resources, and motivation so that faculty may better understand the characteristics and activities of students enrolled in their classes. In the dissertation's first manuscript, I analyzed learning management system (LMS) timestamp log-files from 876 students enrolled in the FYE course during Fall 2013. Following a series of quantitative analyses, I discovered that students who use the LMS more frequently are more likely to have higher grades within the course. This finding suggests that LMS usage might be a way to understand how students interact with course materials outside of traditional class time. Additionally, I found differential relationships between LMS usage and course performance across different instructors as well as a relationship between timing of LMS use and students' course performance. For the second manuscript, I connected three distinct data sets: FYE student's LMS data, student record data, and FYE program survey data that captured students' motivation and identity as engineers at two time points. Structural equation modeling results indicate that SAT Math was the largest predictor of success in the FYE course, and that students' beginning of semester engineering expectancy was the only significant survey construct to predict final course grade. Finally, for the third manuscript I conducted interviews with eight FYE instructors on how they use student data to inform their teaching practices. Ten themes emerged which describe the limited explicit use of formal data, but many instructors use data on an informal basis to understand their students. Findings also point to specific, existing data that the university already collects that could be provided to instructors on an aggregate, class-level basis to help them better understand their students. / Ph. D.

Approximately 63% of all incarcerated individuals in the U.S. identify as a parent (Glaze and Maruschak, 2010), with as many as 7% of children experiencing parental incarceration at some point in their lives (Murphey and Cooper, 2015). Historically, much of the parental incarceration literature has relied on between-groups comparison research, highlighting risks and determinants of pathology for youth with an incarcerated parent. However, significantly less research has attempted to understand resilience processes in the context of parental incarceration from a within-group resilience perspective. The overall goal of this dissertation research was to empirically test the theoretical Family Inequality Framework (Arditti, 2018) and better understand how family resilience processes influence the relationship between material hardship and child outcomes within the context of parental incarceration. Structural equation modeling was used to perform a mediational cross-sectional analysis. Results of these analyses suggest that parental mental health processes play an important role in mitigating adverse outcomes for families by mediating the effects of material hardship on youth academic adjustment in the context of parental incarceration. Theoretical, clinical, and policy implications, as well as future research directions are discussed. / Doctor of Philosophy / Approximately 63% of all incarcerated individuals in the U.S. identify as a parent (Glaze and Maruschak, 2010), with as many as 7% of children experiencing parental incarceration at some point in their lives (Murphey and Cooper, 2015). Historically, much of the existing research on parental incarceration is problem focused, painting these families in a negative light. In contrast, there is very little research highlighting the unique strengths and resiliences of families impacted by parental incarceration. The goal of this dissertation research was to better understand how family resilience processes, such as social support, parenting practices, and parental mental health, might reduce the negative impact of parental incarceration. Results suggest that parental mental health processes play an important role for overall family wellness during parental incarceration. In particular, the more a parent says they are doing well from a mental health perspective the better their kids appear to be doing in school. In this way, parental mental health wellness appears to provide a buffering effect against the common risks parental incarceration can introduce into a family. Theoretical, clinical, and policy implications, as well as future research directions are discussed.

This dissertation examined the extent to which pre-high school students' motivation-related perceptions of their science class affected their science identification, which sequentially affected their future science-related career goals. The MUSIC® Model of Motivation (Jones, 2009, 2018) includes five components (i.e., eMpowerment, Usefulness, Success, Interest, and Caring) and is designed to help teachers design instruction to promote students' motivation. Domain identification (Osborne and Jones, 2011) is a concept closely related to students' motivation and academic outcomes. In this study, data was collected from 311 pre-high school students and Structural Equation Modeling (SEM) analysis was conducted to test the structure pattern among the MUSIC model components, science identification, and science-related career goals. Results indicate that with three of the MUSIC model components (i.e., usefulness, success, and interest) significantly related to students' science identification, students' science identification was highly correlated to their science career goals. Moreover, this study demonstrated the structure patterns among the MUSIC model components and science identification varied by gender by conducting multi-group SEM analyses for a separate female sample (N = 161) and male sample (N = 150). Consistently, students' science identification was a strong predictor of their science career goals in both female and male groups. These findings are important for STEM educators because they indicate that it may be possible for teachers to impact students' science identification and career goals by focusing on students' perceptions of the MUSIC model components in science class. Moreover, these results contribute to the study of the large gender gap in STEM careers. Teachers can focus on specific teaching strategies and help female students develop their science identification in ways that lead to their long-term science-related career goals. / Ph. D. / This dissertation examined the extent to which pre-high school students’ motivation-related perceptions of their science class affected their science identification, which sequentially affected their future science-related career goals. Science identification is a concept that describes the extent to which a student values science as an important part of his or her self (Osborne & Jones, 2011). One goal of this study examined how students’ perceptions of their science class affected students’ science identification. Specifically, this study focused on students’ perceptions of the five components of the MUSIC® Model of Motivation (Jones, 2009, 2018): eMpowerment, Usefulness, Success, Interest, and Caring. The MUSIC model was developed to help teachers design instruction to promote students’ motivation. In this study, results indicate that with three of the MUSIC model components (i.e., usefulness, success, and interest) significantly related to students’ science identification, students’ science identification was highly correlated to their science career goals. Moreover, this study reveals that the structure patterns among the MUSIC model components and science identification varied by gender. Consistently, students’ science identification was a strong predictor of their science career goals in both female and male groups. These findings are important for STEM educators because they indicate that it may be possible for teachers to impact students’ science identification and career goals by focusing on students’ perceptions of the MUSIC model components in science class. Moreover, these results contribute to the study of the large gender gap in STEM careers, in which females are underrepresented. Teachers can focus on specific teaching strategies and help female students develop their science identification in ways that lead to their long-term science-related career goals.

Yes / This research provides a comprehensive delineation of the process that leads to the formation of green behavior by including the role played by media and attitude towards environment-friendly packaging, along with ecological concern and perceived consumer effectiveness. The study offers a parsimonious framework that measures the major antecedents of environmental attitude divided into inward and outward orientation. Moreover, it also measures the effects of these environmental attitudes and attitude towards green packaging on green purchase intention. A total of 308 usable questionnaires were obtained from Indian consumers and data analysis was conducted using confirmatory factor analysis and structural equation modeling. The results show that inward environmental attitude and attitude towards green packaging play a pivotal role in shaping green purchase intention. Surprisingly, outward environmental attitude was found to be non-significant. Findings offer implications for marketing managers and public policy makers, as well as reveal fruitful avenues for further research.

Yes / Purpose – The main purpose of this study is to improve the understanding of how different aspects of the national institutional environment may influence the level of innovative entrepreneurial activity across countries. Several institutional and conductive factors affecting a country’s capacity to support innovative entrepreneurship is explored. Design/methodology/approach – Institutional theory is used to examine the national regulatory, normative, cognitive, and conducive aspects that measure a country's ability to support innovative entrepreneurship. A cross-national institutional profile is constructed to validate an entrepreneurial innovation model. The impact of country-level national institutions on innovative entrepreneurial activity as measured by Global Entrepreneurship Monitor (GEM) data is assessed through structural equation modeling (SEM). Findings – Knowledge about the influence of specific institutional aspects on innovative entrepreneurship, and hence of institutional structures within and across countries, is enhanced. For new innovative enterprises, conductive and regulatory aspects seem to matter most. All conductive factors have a significant and positive impact on entrepreneurial activity rates. Research limitations/implications – Results could support policy makers and practitioners in evaluating government policies’ effect on innovative entrepreneurship. Interventions should target both individual attributes and context. Future research could include longitudinal designs to measure the direction of causality. Practical implications – Aspects such as regulatory institutions, and conductive factors such as ICT use and technology adoption, are important for innovation entrepreneurship development. / The full text will be made available when the article is officially published.

Yes / Organizations adopt blockchain technologies to provide solutions that deliver transparency, traceability, trust, and security to their stakeholders. In a novel contribution to the literature, this study adopts the technology-organization-environment (TOE) framework to examine the technological, organizational, and environmental dimensions for adopting blockchain technology in supply chains. This represents a departure from prior studies which have adopted the technology acceptance model (TAM), technology readiness index (TRI), theory of planned behavior (TPB), united theory of acceptance and use of technology (UTAUT) models. Data was collected through a survey of 525 supply chain management professionals in India. The research model was tested using structural equation modeling. The results show that all the eleven TOE constructs, including relative advantage, trust, compatibility, security, firm’s IT resources, higher authority support, firm size, monetary resources, rivalry pressure, business partner pressure, and regulatory pressure, had a significant influence on the decision of blockchain technology adoption in Indian supply chains. The findings of this study reveal that the role of blockchain technology adoption in supply chains may significantly improve firm performance improving transparency, trust and security for stakeholders within the supply chain. Further, this research framework contributes to the theoretical advancement of the existing body of knowledge in blockchain technology adoption studies.