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.

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.

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.

Assessment of Relationship of Some Causal Factors Associated with Productivity of Longwall Mining Using Structured Equation Modeling

Enhancement of productivity optimization is steadily gaining the priority in mining companies especially in the underground coal mining industry which faces a daunting task to balance marginal profit generation with a comparatively high cost of production, volatile market price and rapid grade variation. This paper is aimed to analyze some of the causal factors both technical and site specific which are directly or indirectly impacting the productivity of the longwall coal mining system such as downtime of equipment system in longwall panel, overloading of conveyors and bin, preventive maintenance, gas management practices and injury severity rate. Structured Equation Modelling (SEM) was used to study the causal relationships between the above-mentioned factors and mine productivity. The equipment considered for analysis included shearer, armored face conveyor, crusher, bridge stage loader, chock supports, main gate drive, gate conveyor, hydraulic pumps and crusher. SEM was applied to relate the correlations existing among these causal variables in order to assess their direct or indirect impact on mining productivity. Based on the data extracted over a period of 10 months which included the extraction of 2 longwall panels, the study revealed a significant negative causal relationship between injury severity rate (p < 0.01) and equipment downtime (p = 0.001), with mine productivity. However, preventive maintenance delay time, gas management delay time and conveyor overloading delay time were found to have an insignificant direct influence on mine productivity but indirectly modify it through a significant mediator relationship with equipment downtime. This information would assist mine management to take proper preventive measures.

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.

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.

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.

Structured Equation Model of Tuberculosis Incidence Based on Its Social Determinants and Risk Factors in Bandar Lampung, Indonesia

World Health Organization through tuberculosis (TB) control averted up to six million deaths and cured thirty-six million people in 1995-2008, but had less success in reducing TB incidence, especially in thirteen high burden countries, including Indonesia. Therefore, TB control will need to have more emphasis on the issues of social determinants, as social determinants affect TB’s incidence directly and/-or through TB’s risk factors. This study aimed to identify a significant effect of social determinants and the risk factors of TB incidence. The research setting was at twenty-seven primary health centers and one hospital that have implemented the Directly Observed Treatment Short Course (DOTS) strategy in Bandar Lampung municipality, Indonesia. Respondents of this research were 238 smear-positive TB patients as case group and 238 patients without TB as control group. Research variables consisted of “social determinants”, “housing condition”, “household food security” and “health access” which were set as latent variables and measured through their indicators. Data had been collected by using questionnaire and then was analyzed with Structural Equation Modeling using SmartPLS 2.0 software. The result showed that “social determinants” through “housing condition” and “household food security” affected “TB incidence”. Moreover, “social determinants”, “housing condition” and “household food security” can be used to explain 34.1% variation of “TB incidence”. In conclusion, the knowledge can be used to support the TB control program, particularly to implement the DOTS strategy together with improving social determinants, housing condition and household food security.

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.

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.

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.

Validation of general linear modeling for identifying factors associated with Quality of Life: A comparison with structural equation modeling

Purpose: General linear modeling (GLM) is usually applied to investigate factors associated with the domains of Quality of Life (QOL). A summation score in a specific sub-domain is regressed by a statistical model including factors that are associated with the sub-domain. However, using the summation score ignores the influence of individual questions. Structural equation modeling (SEM) can account for the influence of each question’s score by compositing a latent variable from each question of a sub-domain. The objective of this study is to determine whether a conventional approach such as GLM, with its use of the summation score, is valid from the standpoint of the SEM approach. Method: We used the Japanese version of the Maugeri Foundation Respiratory Failure Questionnaire, a QOL measure, on 94 patients with heart failure. The daily activity sub-domain of the questionnaire was selected together with its four accompanying factors, namely, living together, occupation, gender, and the New York Heart Association’s cardiac function scale (NYHA). The association level between individual factors and the daily activity sub-domain was estimated using SEM?and GLM, respectively. The standard partial regression coefficients of GLM and standardized path coefficients of SEM were compared. If?these coefficients were similar (absolute value of the difference -0.06 and -0.07 for the GLM and SEM. Likewise, the estimates of occupation, gender, and NYHA were -0.18 and -0.20, -0.08 and -0.08, 0.51 and 0.54, respectively. The absolute values of the difference for each factor were 0.01, 0.02, 0.00, and 0.03, respectively. All differences were less than 0.05. This means that these two approaches lead to similar conclusions. Conclusion: GLM is a valid method for exploring association factors with a domain in QOL.

A Structural Equation Model (SEM) for Pharmacist Competencies in Improving Quality of Life of Cancer Patients: Effect of Missing Values on the SEM

Objective: With the goal of improving health-related quality of life (HRQOL) in cancer patients, we previously reported a structural equation model (SEM) of subjected QOL and qualifications of pharmacists, based on a series of questionnaires completed by patients and pharmacists. However, several patients and pharmacists were excluded from the previous study because it was not always possible to obtain all the data intended for collection. In order to reveal the effect of missing data on the SEM, we established SEMs of HRQOL and the competency of pharmacists, using correlation matrices derived by two different statistical methods for handling missing data. Method: Fifteen cancer patients hospitalized for cancer and were receiving opioid analgesics for pain control, and eight pharmacists were enrolled in this study. Each subject was asked four times weekly to answer questions presented in a questionnaire. SEMs were explored using two correlation matrices derived with pair-wise deletion (PD matrix) and list-wise deletion (LD matrix). The final models were statistically evaluated with certain goodness-of-fit criteria. Results: Data were intended to be collected four times weekly for each patient, but there were some missing values. The same SEMs for HRQOL were optimized using both the LD and PD matrices. Although the path diagrams of the SEMs were not identical in the “competency of pharmacists,” the two models suggested that a higher competency of a pharmacist lowered the “severity” of condition and increased the “comfort” of patients, resulting in an increase in the subjected QOL. Conclusion: In collecting data for clinical research, missing values are unavoidable. When the structure of the model was robust enough, the missing data had a minor effect on our SEM of QOL. In QOL research, the LD matrix as well as the PD matrix would be effective, provided the model is sufficiently robust.

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.

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.

Drivers of spatial structure in thinned forests

Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.

Enhancing disaster management effectiveness: An integrated analysis of keyfactors 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.