A Survey Study on TPACK Framework for Normal Students of English Major in Ethnic Colleges and Universities:Empirical Analysis Based on Structural Equation Modeling

With the continuous advancement of education informatization,Technological Pedagogical Content Knowledge(TPACK),as a new theoretical framework,provides a novel method for measuring teachers’informatization teaching ability.This study takes normal students of English majors from three ethnic universities as the research object,collects relevant data through questionnaires,and uses structural equation modeling to conduct data analysis and empirical research to investigate the differences in the TPACK levels of these students at different grades and the structural relationships among the elements in the TPACK structure.The technological pedagogical knowledge element of the TPACK structure was not obtained by exploratory factors analysis but through path analysis and structural equation modeling,the results show that the one-dimensional core knowledge of technological knowledge(TK),content knowledge(CK),and pedagogical knowledge(PK)have a positive effect on the two-dimensional interaction knowledge of technological content knowledge(TCK)and pedagogical content knowledge(PCK);furthermore,TCK and PCK have a positive effect on TPACK;and TK,CK,and PK indirectly affect TPACK through TCK and PCK.On this basis,suggestions are provided to ethnic colleges and universities to develop the TPACK knowledge competence of normal students of English majors.

Mechanisms Influencing Learning Gains Under Information Security: Structural Equation Modeling with Mediating Effect

With the expanding enrollments in higher education,the quality of col-lege education and the learning gains of students have attracted much attention.It is important to study the influencing factors and mechanisms of individual stu-dents’acquisition of learning gains to improve the quality of talent cultivation in colleges.However,in the context of information security,the original data of learning situation surveys in various universities involve the security of educa-tional evaluation data and daily privacy of teachers and students.To protect the original data,data feature mining and correlation analyses were performed at the model level.This study selected 12,181 pieces of data from X University,which participated in the Chinese College Student Survey(CCSS)from 2018 to 2021.A confirmatory factor analysis was conducted and a structural equation modeling was conducted using AMOS 24.0.Through hypothesis testing,this study explored the mechanisms that influence learning gains from the per-spectives of student involvement,teacher involvement,and school support.The results indicated that the quality of student involvement has an important mediat-ing effect on learning gains and that a supportive campus environment has the greatest influence on learning gains.Establishing positive emotional communica-tions between teachers and students is a more direct and effective method than improving the teaching level to improve the quality of student involvement.This study discusses the implications of these results on the research and practice of connotative development in higher education.

Meta-analytic structural equation modeling:a primer

Meta-analytic structural equation modeling is a new research field which can help to explain the relationship between a group of variables in several studies by testing structural equation modeling.However,this methodology is still not very popular in many countries and researchers due to lack of promotion.This report aim s to giv e a primer on the principle of m eta-analytic structural equation modeling and provid e a reference for subsequent researchers to conduct m eta-analytic structural equation modeling analysis.

Investigation of the role of personal factors on work injury in underground mines using structural equation modeling

Work injuries in mines are complex and generally characterized by several factors starting from personal to technical and technical to social characteristics.In this paper,investigation was made through the application of structural equation modeling to study the nature of relationships between the influencing/associating personal factors and work injury and their sequential relationships leading towards work injury occurrences in underground coal mines.Six variables namely,rebelliousness,negative affectivity,job boredom,job dissatisfaction and work injury were considered in this study.Instruments were developed to quantify them through a questionnaire survey.Underground mine workers were randomly selected for the survey.Responses from 300 participants were used for the analysis.The structural model of LISREL was used to estimate the interrelationships amongst the variables.The case study results show that negative affectivity and job boredom induce more job dissatisfaction to the workers whereas risk taking attitude of the individual is positively influenced by job dissatisfaction as well as by rebelliousness characteristics of the individual.Finally,risk taking and job dissatisfaction are having positive significant direct relationship with work injury.The findings of this study clearly reveal that rebelliousness,negative affectivity and job boredom are the three key personal factors influencing work related injuries in mines that need to be addressed properly through effective safety programs.

Factors influencing the internet banking adoption decision in North Cyprus: an evidence from the partial least square approach of the structural equation modeling

Purpose:This paper aims to examine how the adoption decision of the internet banking in North Cyprus would be affected based on the following dimensions;the technology features,the personal characteristics,the social environment and the expected risk.Design/methodology/approach:A self-administered survey was conducted with 291 participants responded to it.The partial least square approach of the structural equation modeling(PLS-SEM)is employed to investigate the direct effects of the proposed factors on the adoption decision.Additionally,the mediation test is used to examine indirect effects.Findings:Results showed that even though the participants appreciated the benefits of the online banking as the perceived usefulness factor exerts the greatest direct effect,they would rather use clear and easy-to-use websites,adding to that their assessments of the usefulness of these services are significantly influenced by the surrounding people’s views and prior experience.This is demonstrated by the total effects of the perceived ease of use and the subjective norm factors,which are greater than the direct effect of the perceived usefulness factor since both of these factors have significant direct and indirect effects mediated by the perceived usefulness factor.The negative impact of the perceived risk factor is weak compared to the previous factors.While the personal innovativeness factor showed the weakest effect among the proposed factors.

Structural equation modeling analysis of factors influencing architects' trust in project design teams

This paper describes a structural equation modeling （SEM） analysis of factors influencing architects＇ trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural design institutes selected radomly from the altogether 59 ones in Shenzhen, P. R. China, and received 130 valid questionnaires. We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trus~ is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

Application of Structural Equation Modeling to Evaluate Service Quality of Sportswear Retailing

Structural Equation Modeling （SEM） used widely in sociology, economics and psychology is adopted. Based on data obtained from marketing research, and using statistical analysis software SPSSll. 0 and LISRELS. 7, Theory of Five Dimensions of service quality is proved to be suitable in sportswear retailing in China. It analyzes the relationship among five dimensions and puts them in order of importance as to service quality in sportswear retailing. Advices are given for sportswear retail companies to improve their .Service quality and enhance customer loyalty.

Linking Structural Equation Modeling with Bayesian Network and Its Application to Coastal Phytoplankton Dynamics in the Bohai Bay

Bayesian networks （BN） have many advantages over other methods in ecological modeling, and have become an increasingly popular modeling tool. However, BN are flawed in regard to building models based on inadequate existing knowledge. To overcome this limitation, we propose a new method that links BN with structural equation modeling （SEM）. In this method, SEM is used to improve the model structure for BN. This method was used to simulate coastal phytoplankton dynamics in the Bohai Bay. We demonstrate that this hybrid approach minimizes the need for expert elicitation, generates more reasonable structures for BN models, and increases the BN model＇s accuracy and reliability. These results suggest that the inclusion of SEM for testing and verifying the theoretical structure during the initial construction stage improves the effectiveness of BN models, especially for complex eco-environment systems. The results also demonstrate that in the Bohai Bay, while phytoplankton biomass has the greatest influence on phytoplankton dynamics, the impact of nutrients on phytoplankton dynamics is larger than the influence of the physical environment in summer. Furthermore, although the Redfield ratio indicates that phosphorus should be the primary nutrient limiting factor, our results show that silicate plays the most important role in regulating phytoplankton dynamics in the Bohai Bay.

Generalized structural equation modeling:Symptom heterogeneity in attention-deficit/hyperactivity disorder leading to poor treatment efficacy

BACKGROUND Treatment efficacy for attention-deficit/hyperactivity disorder(ADHD)is reported to be poor,possibly due to heterogeneity of ADHD symptoms.Little is known about poor treatment efficacy owing to ADHD heterogeneity.AIM To use generalized structural equation modeling(GSEM)to show how the heterogeneous nature of hyperactivity/impulsivity(H/I)symptoms in ADHD,irritable oppositional defiant disorder(ODD),and the presentation of aggression in children interferes with treatment responses in ADHD.METHODS A total of 231 children and adolescents completed ADHD inattention and H/I tests.ODD scores from the Swanson,Nolan,and Pelham,version IV scale were obtained.The child behavior checklist(CBCL)and parent’s satisfaction questionnaire were completed.The relationships were analyzed by GSEM.RESULTS GSEM revealed that the chance of ADHD remission was lower in children with a combination of H/I symptoms of ADHD,ODD symptoms,and childhood aggressive behavior.ODD directly mediated ADHD symptom severity.The chance of reaching remission based on H/I symptoms of ADHD was reduced by 13.494%[=exp(2.602)]in children with comorbid ADHD and ODD[odds ratio(OR)=2.602,95%confidence interval(CI):1.832-3.373,P=0.000]after adjusting for the effects of other factors.Childhood aggression mediated ODD symptom severity.The chance of reaching remission based on ODD symptoms was lowered by 11.000%[=1-exp(-0.117)]in children with more severe baseline symptoms of aggression based on the CBCL score at study entry[OR=-0.117,95%CI:(-0.190)-(-0.044),P=0.002].CONCLUSION Mediation through ODD symptoms and aggression may influence treatment effects in ADHD after adjusting for the effects of baseline ADHD symptom severity.More attention could be directed to the early recognition of risks leading to ineffective ADHD treatment,e.g.,symptoms of ODD and the presentation of aggressive or delinquent behaviors and thought problems in children with ADHD.

Analysis of Satisfaction with Business Cost in Shanghai Using Structural Equation Modeling Approach

Tracing the origins of business cost, to define the satisfaction assessment factors on the business cost in Shanghai was investigated in this paper. Arguing that these effects: a single low cost is not only the criterion determining satisfaction. Other important factors, such as enterprise internal cognitive attitude,stability of the external environment,the quality of perceptions of government services can affect satisfaction. Within structural equation modeling( SEM) approach, six sets of hypotheses are drawn up and tested with a sample of 338 enterprises using questionnaires. Additionally,the analyses of findings introduce the crucial importance of these features in the assessment of satisfaction with business cost in Shanghai. Finally, the results show that internal cognitive has a positive impact on satisfaction. Stability of the external environment has a significant relationship with the effectiveness of government services. Stability of the external environmeat and the effectiveness of government servises have a positive effect on satisfaction.

Factors Affecting Quality of Equipment Maintenance Based on Structural Equation Modeling

Factors affecting equipment maintenance quality usually include personnel,equipment and facilities,raw materials and spare parts, craft, environment and quality management. These six factors affecting maintenance quality are not all the same degree. In order to find out which factor can influence equipment maintenance quality greatly and achieve sophisticated management,characteristic quantities of six factors are presented. A structural equation modeling( SEM) is designed using the six factors as latent variables and their characteristic quantities as the observed variable.According to the basic data obtained from the questionnaire survey,calculate the standardized regression weight by parameter estimation of the SEM. Then the key factors affecting the quality of the equipment maintenance are determined with the help of the standardized regression weight.

Enhancing disaster management effectiveness: An integrated analysis of key factors and practical strategies through Structural Equation Modeling (SEM)and scopus data text mining

In the 21st century, the surge in natural and human-induced disasters necessitates robust disaster managementframeworks. This research addresses a critical gap, exploring dynamics in the successful implementation andperformance monitoring of disaster management. Focusing on eleven key elements like Vulnerability and RiskAssessment, Training, Disaster Preparedness, Communication, and Community Resilience, the study utilizesScopus Database for secondary data, employing Text Mining and MS-Excel for analysis and data management.IBM SPSS (26) and IBM AMOS (20) facilitate Exploratory Factor Analysis (EFA) and Structural Equation Modeling(SEM) for model evaluation.The research raises questions about crafting a comprehensive, adaptable model, understanding the interplaybetween vulnerability assessment, training, and disaster preparedness, and integrating effective communicationand collaboration. Findings offer actionable insights for policy, practice, and community resilience against disasters. By scrutinizing each factor's role and interactions, the research lays the groundwork for a flexible model.Ultimately, the study aspires to cultivate more resilient communities amid the escalating threats of an unpredictable world, fostering effective navigation and thriving.

Measurement Research Based on Bayesian Structural Equation Cognitive Model

The Bayesian structural equation model integrates the principles of Bayesian statistics, providing a more flexible and comprehensive modeling framework. In exploring complex relationships between variables, handling uncertainty, and dealing with missing data, the Bayesian structural equation model demonstrates unique advantages. Therefore, Bayesian methods are used in this paper to establish a structural equation model of innovative talent cognition, with the measurement of college students’ cognition of innovative talent being studied. An in-depth analysis is conducted on the effects of innovative self-efficacy, social resources, innovative personality traits, and school education, aiming to explore the factors influencing college students’ innovative talent. The results indicate that innovative self-efficacy plays a key role in perception, social resources are significantly positively correlated with the perception of innovative talents, innovative personality tendencies and school education are positively correlated with the perception of innovative talents, but the impact is not significant.

A practical guideline for univariate meta-analytic structural equation modelling

Background:Meta-analysis is a quantitative approach that systematically integrates results from previous research to draw conclusions.Structural equation modelling is a statistical method that integrates factor analysis and path analysis.Meta-analytic structural equation modeling(MASEM)combines meta-analysis and structural equation modeling.It allows researchers to explain relationships among a group of variables across multiple studies.Methods:We used a simulated dataset to conduct a univariate MASEM analysis,using Comprehensive Meta Analysis 3.3,Analysis of Moment Structures 24.0 software.Results:Despite the lack of concise literature on the methodology,our study provided a practical step-by-step guide on univariate MASEM.Conclusion:Researchers can employ MASEM analysis in applicable fields based on the description,principles,and practices expressed in this study and our previous publications mentioned in this study.

Toward equation structural modeling:an integration of interpretive structural modeling and structural equation modeling

Interpretive structural modeling(ISM)is an interactive process in which a malformed(bad structured)problem is structured into a comprehensive systematic model.Yet,despite many advantages that ISM provides,this method has some shortcomings,the most important one of which is its reliance on participants’intuition and judgment.This problem undermines the validity of ISM.To solve this problem and further enhance the ISM method,the present study proposes a method called equation structural modeling(ESM),which draws on the capacities of structural equation modeling(SEM).As such,ESM provides a statistically verifiable framework and provides a graphical,hierarchical and intuitive model.

The integration model of objective and subjective data of residential indoor environment quality in Northeast China based on structural equation modeling

Currently the indoor environment quality is described or evaluated mainly by the subjective or objective data.However,research increasingly has demonstrated that objective and subjective data both had some weaknesses to characterize the indoor environment quality,and they can compensate for each other's relative weaknesses.Hence,this study aims to develop an integration model to allow indoor subjective and objective data to be combined based on the structural equation modeling approach,using the Northeast China residential indoor environmental survey data.The results indicated that the integration model had a good fit for the survey data,and the model validity was confirmed.Moreover,in contrast to the subjective data(R^(2)=0.363)and objective data(R^(2)=0.239),the integrated data(R^(2)=0.553)improved the explanatory power on the satisfaction with the overall indoor environment.Furthermore,this integration model demonstrated that indoor subjective data assigned more weights to the integrated data than the corresponding objective data.The association strength of thermal environment and indoor air quality(0.43 or 0.47)was the strongest among the interactions of thermal,air quality,acoustic,and lighting environments.Consequently,the main contribution of this paper was that it provided a comprehensive model to accomplish the integration of indoor environmental subjective and objective data,promoting the ability to describe and assess the indoor environment quality.

Coupling Relationship Analysis on Households′ Production Behaviors and Their Influencing Factors in Nature Reserves:A Structural Equation Model

A households′production behavior directly influences the quality of the environment and determines the successful development of nature reserves.Meanwhile,the households′production behaviors are complicated by interrelated factors,such as protection attitudes,resource endowment,and family wealth.This research evaluated households near the Crested Ibis National Nature Reserve in Shaanxi Province,acquiring data from 436 households around Yang County and Ningshan County in the south slope of Qinling Mountains,China.Based on the collected data,we developed a structural equation model to evaluate the coupling relationships among households′ protection attitudes,production behaviors,resource endowment,and family wealth.The results showed that:1) households with great resource endowment had more negative attitudes,probably due to their greater protection costs;2) the households with higher education levels had worse protection attitudes;3) the households with more family wealth were likely to use fewer fertilizers,pesticides,and firewood;4) the households with more resource endowment showed less production and management behaviors;5) the enhancement of households' attitudes improved production behaviors to protection the environment,but the effects were not statistically significant.Our results provide a basis for the government's protection policy making,exploring the effective management measures that are beneficial for both nature reserve management and community development.

Quality Management Model for Phase I Clinical Drug Trials:A Structural Equation Model

This study aimed to construct a quality management model for phase I clinical drug trials.A cross-sectional survey was conducted and data were collected from 604 respondents at 69 institutions in China engaged in phase I clinical drug trials.Exploratory and confirmatory factor analyses were used to develop the survey tool.Structural equation modeling was used to construct a quality management model for phase I clinical drug trials.The results showed that the final survey tool had good reliability and validity(Cronbach’sα=0.938,root mean square error of approximation=0.074,comparative fit index=0.962,and Tucker—Lewis index=0.955).The model included five dimensions:government regulation,industry management,medical institution management,research team management,and contract research organization(CRO)management.In total,22 measurement items were obtained.The structural equation model indicated government regulation,industry management,medical institution management,and CRO management significantly affected the quality of phase I clinical drug trials(β=0.195,β=0.331,β=0.279,andβ=−0.267,respectively;P<0.05).Research team management had no effect on the quality of trials(β=0.041,P=0.610).In conclusion,the model is valuable for identifying factors influencing phase I clinical drug trials and guiding quality management practices.

A Structural Equation Model of Residents' Support for Mega Event

The aim of this article is to develop a structural equation model to assess key factors of residents' support for hosting mega event based on previous literature.The model consisted of five latent constructs and eight path hypotheses.A survey was conducted in Shanghai before 2010 World Expo.It was found that the support for mega events is affected directly and/or indirectly by four determinants factors:perceived benefits,perceived costs,personal benefits and community attachment,and support relies heavily on perceived benefits rather than costs.This study contributes to the existing body of knowledge in an attempt to understand local residents' support for a mega event in different economic and cultural settings.

A Re-Parametrization-Based Bayesian Differential Analysis Algorithm for Gene Regulatory Networks Modeled with Structural Equation Models

Under different conditions,gene regulatory networks(GRNs)of the same gene set could be similar but different.The differential analysis of GRNs under different conditions is important for understanding condition-specific gene regulatory relationships.In a naive approach,existing GRN inference algorithms can be used to separately estimate two GRNs under different conditions and identify the differences between them.However,in this way,the similarities between the pairwise GRNs are not taken into account.Several joint differential analysis algorithms have been proposed recently,which were proved to outperform the naive approach apparently.In this paper,we model the GRNs under different conditions with structural equation models(SEMs)to integrate gene expression data and genetic perturbations,and re-parameterize the pairwise SEMs to form an integrated model that incorporates the differential structure.Then,a Bayesian inference method is used to make joint differential analysis by solving the integrated model.We evaluated the performance of the proposed re-parametrization-based Bayesian differential analysis(ReBDA)algorithm by running simulations on synthetic data with different settings.The performance of the ReBDA algorithm was demonstrated better than another state-of-the-art joint differential analysis algorithm for SEMs ReDNet obviously.In the end,the ReBDA algorithm was applied to make differential analysis on a real human lung gene data set to illustrate its applicability and practicability.