scholarly journals Online vs. offline course evaluation revisited: testing the invariance of a course evaluation questionnaire using a multigroup confirmatory factor analysis framework

2020 ◽  
Author(s):  
Ellen Laupper ◽  
Lars Balzer ◽  
Jean-Louis Berger
Keyword(s):  
Higher Education ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Methodological Approach ◽  
Education Institution ◽  
Teaching Quality ◽  
Course Evaluation ◽  
Global Trends ◽  
Confirmatory Factor ◽  
Multigroup Confirmatory Factor Analysis

Abstract Survey-based formats of assessing teaching quality in higher education are widely used and will likely continue to be used by higher education institutions around the world as various global trends contributing to their widespread use further evolve. Although the use of mobile devices for course evaluation continues to grow, there remain some unresolved aspects of the classic paper and web-based modes of evaluation. In the current study, the multigroup confirmatory factor analysis approach (MGCFA), an accepted methodological approach in general mixed-method survey research, was chosen to address some of the methodological issues when comparing these two evaluation modes. By randomly assigning one of the two modes to 33 continuing training courses at a Swiss higher education institution, this study tested whether the two different modes of assessing teaching quality yield the same results. The practical implications for course evaluation practice in institutions of higher education as well as the implications and limitations of the chosen methodological approach are discussed.

scholarly journals Approbation of the Decision Making Tendency Inventory in the Russian Sample

2018 ◽  
Vol 26 (3) ◽  
pp. 146-163
Author(s):  
A.Yu. Razvaliaeva
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Education Institution ◽  
Scale Structure ◽  
Personal Factors ◽  
Higher Education Institution ◽  
Confirmatory Factor ◽  
Ambiguity Intolerance

We present the results of approbating the Decision Making Tendency Inventory (Misuraca et al., 2015) in the Russian sample (N=423, Mage= 25,01, SD = 9,63). The development of H. Simon’s satisficing theory in the current studies is considered. Confirmatory factor analysis confirmed the theoretical three-scale structure of the inventory. We describe the relations between maximizing, minimizing and satisficing scales and personal factors of decision-making, age, and education (its level and difficulty). The study demonstrates that maximizing and satisficing are close tendencies, implemented in case of making important effortful and resource-consuming (e.g., time-consuming) decisions, whereas minimizing is connected to withdrawal from effort and knowledge, avoidant strategies and ambiguity intolerance. The yielded results suggest that satisficing needs to be trained in conditions of high demands for the cognitive sphere such as studying in a higher education institution.

scholarly journals Student Burnout in Higher Education: A Demand-Resource Model Approach

2022 ◽  
Author(s):  
Balázs Jagodics ◽  
Éva Szabó
Keyword(s):  
Higher Education ◽  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Confirmatory Factor Analysis ◽  
Correlation Analysis ◽  
Structural Equation ◽  
Equation Modeling ◽  
Resource Model ◽  
Confirmatory Factor ◽  
Student Burnout

AbstractStudent burnout is a serious problem in higher education. It is associated with harmful consequences, such as decreased engagement, performance, and motivation, which can lead to dropout. The job demand-resource model of burnout is a comprehensive framework to grasp the factors related to the emergence of burnout. Although numerous studies claim its suitability in explaining burnout in work environments, its applicability in the educational context is less explored. The study aimed to analyze the structure and reliability of the newly developed University Demand-Resource Questionnaire (UDRQ) and to explore the links between its subscales and symptoms of student burnout. Using the online survey method, 743 Hungarian undergraduate students participated in the data collection. The student version of the Maslach Burnout Inventory was used in addition to the UDRQ. In the data analysis procedure, confirmatory factor analysis, correlation analysis, and structural equation modeling were utilized. The confirmatory factor analysis identified a five-factor structure related to both demands and resources. Correlation analysis revealed burnout to be associated positively to the subscales of demands and negatively to resources. Structural equation modeling analysis indicated that all five demands and two resources subscales can be used to build a model that predicts a significant proportion of the variance of student burnout scores. The findings suggest the demand-resource theory is an appropriate framework to predict burnout in higher education. The newly developed UDRQ has stable structure and good reliability and can be a useful tool in subsequent research related to student burnout.

scholarly journals Expected Learning Outcomes: A Confirmatory Factor Analysis of Higher Education in Interior Architecture and Interior Design for the Thailand Development

2019 ◽  
Vol 10 (4) ◽  
pp. 11-19
Author(s):  
Pornthep Jewpairojkit ◽  
Thanin Rattanolarn ◽  
Songwut Ekwuttiwongsa
Keyword(s):  
Higher Education ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Learning Outcomes ◽  
Interior Design ◽  
Professional Education ◽  
Interpersonal Relationship ◽  
Measurement Model ◽  
Interior Architecture ◽  
Confirmatory Factor

Abstract Nowadays, the standard of professional education, interior architecture and interior design at higher education in Thailand must meet the certification criteria from the Professional Council. However, the expected learning outcomes results in the past studies has not studied the components of expected learning outcomes that are explicit and consistent with the 20-Year National Strategy. The researchers therefore aim to study such components to lead to the development of a standard measurement model to further expected learning outcomes. The researchers synthesized the initial components through the document to create and develop a questionnaire to evaluate the level of performance by estimating 5 levels and collect data with the senior students in the curriculum that has been approved by the Professional Council. Divided into 362 samples in the analysis of survey elements and 364 samples in Confirmatory Factor Analysis by Cluster Random Sampling from state and private universities. The survey component analysis resulted in 6 components along with confirmatory factor analysis of empirical component. The results of the sequence analysis of weight components from descending order as follows: Cognitive for profession skill (CP)=.96 Interpersonal relationship and responsibility skill (IR)=.89 In numerical communication and information technology skill(NC)=.87 Profession future of Thailand skill (PF)=.85 Knowledge for Professional practice skill (KPP)=.73 Moral and ethical skill (ME) =.67.

Higher-Order Factors and Measurement Equivalence of the Spectrum of Teaching Styles’ Questionnaire Across Two Cultures

2020 ◽  
pp. 1-11
Author(s):  
Ioannis Syrmpas ◽  
Athanasios Papaioannou ◽  
Nikolaos Digelidis ◽  
Gokce Erturan ◽  
Mark Byra
Keyword(s):  
Preservice Teachers ◽  
Factor Analysis ◽  
Physical Education ◽  
Confirmatory Factor Analysis ◽  
Teaching Styles ◽  
Higher Order ◽  
Parameter Estimates ◽  
Minimum Requirement ◽  
Confirmatory Factor ◽  
Multigroup Confirmatory Factor Analysis

Purpose: This study aimed to test the invariance of perceptions of the Spectrum teaching styles across Turkish and Greek preservice physical education teachers and to examine whether the styles could be classified into two clusters through self-determination theory. Greek (n = 298) and Turkish (n = 300) preservice teachers participated. Method: Cothran, Kulinna, and Ward’s questionnaire based on teachers’ use of and beliefs about teaching styles was used to examine their perceptions of the styles. Results: Confirmatory factor analysis revealed 11 factor indices and parameter estimates, suggesting that the 11-factor model fit the data. Multigroup confirmatory factor analysis established metric measurement invariance across samples. Multigroup confirmatory factor analysis showed that, for all higher-order models, the minimum requirement for invariance factor loading was met. The model comparison revealed that the styles could be categorized into four clusters from less to more autonomy-oriented. Conclusion: These findings might be useful to practitioners who want to use teaching styles in the promotion of students’ motivation in physical education.

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