The confirmatory factor analysis of teacher’s research motivation scale

2018 ◽  
Vol 8 (3) ◽  
pp. 101-106
Author(s):  
Ujsara Prasertsin
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Intrinsic Motivation ◽  
Latent Variables ◽  
Latent Variable ◽  
Extrinsic Motivation ◽  
Class Action ◽  
P Value ◽  
Confirmatory Factor ◽  
Motivation Scale

The purpose of the research is to develop the measurement of motivation scale of in class action research conducted by school teachers. The sampling is 403 teachers, subordinated to Office of The Basic Education Commission. Data collection was conducted through questionnaires of 20 questions. The questions were designed into 5 levels following to the motivation scale in research measurement of Deemer, Mahoney, & Ball (2010). This 20 questions questionnaire is consisting of 3 latent variables that are 9 questions of intrinsic motivation, 6 questions of failure avoidance and 5 questions extrinsic motivation. The purpose of confirmatory factor analysis (CFA) is to test the construct validity of research latent variables that found the harmony correlation of empirical data contained in this research model, the value of Chi-Square ( )=89.224 at the degree of freedom=71, P value=0.071, GFI=0.978, AGFI=0.936, RMSEA=0.062, RMR=0.018, Model AIC=367.224, Saturated AIC=420.000, Model CAIC= 1062.076, Saturated CAIC = 1469.777. The weight factors of latent variable are 0.692, -0.066 and 0.894 retrospectively. The value of reliability according to cronbach’s alpha coefficient of correlation is 0.479, 0.004 and 0.800 retrospectively. Moreover correlation matrix of 20 observed variables shows the correlation among latent variables of intrinsic motivation and extrinsic motivation with the significant level of statistic correlation at 0.05, the correlation value ranged between 0.196-0.604 and 0.196-0.696 retrospectively. The highest value of correlation scored 0.696 is founded in observed variables of intrinsic motivation latent variable. Keywords: Confirmatory, factor analysis, teacher, research motivation

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

scholarly journals Can Variances of Latent Variables be Scaled in Such a Way That They Correspond to Eigenvalues?

2017 ◽  
Vol 6 (6) ◽  
pp. 35 ◽  
Author(s):  
Karl Schweizer ◽  
Stefan Troche ◽  
Siegbert Reiß
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Simulation Study ◽  
Latent Variables ◽  
Latent Variable ◽  
Factor Model ◽  
Estimation Method ◽  
Factor Loadings ◽  
Confirmatory Factor ◽  
Theoretical Foundations

The paper reports an investigation of whether sums of squared factor loadings obtained in confirmatory factor analysis correspond to eigenvalues of exploratory factor analysis. The sum of squared factor loadings reflects the variance of the corresponding latent variable if the variance parameter of the confirmatory factor model is set equal to one. Hence, the computation of the sum implies a specific type of scaling of the variance. While the investigation of the theoretical foundations suggested the expected correspondence between sums of squared factor loadings and eigenvalues, the necessity of procedural specifications in the application, as for example the estimation method, revealed external influences on the outcome. A simulation study was conducted that demonstrated the possibility of exact correspondence if the same estimation method was applied. However, in the majority of realized specifications the estimates showed similar sizes but no correspondence. 

scholarly journals Uji Validitas Konstruk Pada Instrumen Motivasi Akademik Dengan Metode Confirmatory Factor Analysis (CFA)

2019 ◽  
Vol 7 (2) ◽  
pp. 78-85
Author(s):  
Milcham Chairun Syah
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Intrinsic Motivation ◽  
Extrinsic Motivation ◽  
Academic Motivation ◽  
Measurement Instrument ◽  
Three Dimensions ◽  
Academic Level ◽  
Confirmatory Factor ◽  
Academic Year

Motivasi akademik merupakan suatu hasrat atau dorongan seseorang dalam memperoleh sesutua yang ingin diraih untuk tercapainya suatu tujuan tertentu pada bidang akademiknya, yang diukur dengan menggunakan Academic Motivation Scales (AMS), berdasarkan tiga dimensi motivasi akademik, yaitu extrinsic motivation, intrinsic motivation dan amotivation (Deci & Ryan dalam Ayub, 2010). Academic Motivation Scales (AMS) merupakan instrumen pengukuran baku yang dikembangkan oleh Vallerand (dalam Areepattamannil, 2011) untuk mengukur tiga dimensi motivasi akademik yang berjumlah 28 item. Penelitian ini bertujuan untuk menguji validitas konstruk instrumen tersebut. Data dalam penelitian ini diperoleh dari seluruh mahasiswa semester 2 Fakultas Psikologi UIN Jakarta tahun akademik 2013/2014 yang berjumlah 149 orang. Metode yang digunakan dalam pengujiannya yaitu confirmatory factor analysis (CFA) dengan menggunakan software LISREL 8.70. Hasil dari penelitian ini menunjukkan bahwa 23 item bersifat unidimensional, artinya item-item tersebut hanya mengukur satu faktor saja sehingga model satu faktor dapat diterima.Academic motivation is a desire or encouragement of someone to get something they want to achieve a certain goal in their academic level, which is measured by using Academic Motivation Scales (AMS) based on three dimensions of academic motivation, namely extrinsic motivation, intrinsic motivation and motivation (Deci & Ryan in Ayub, 2010). Academic Motivation Scales (AMS) is a standard measurement instrument developed by Vallerand (in Areepattamannil, 2011) to measure three dimensions of academic motivation totaling 28 items. This study aims to examine the construct validity of the instrument. The data in this study were obtained from all 2nd semester students of the Faculty of Psychology, UIN Jakarta, 2013/2014 academic year, from 149 people. The method used in the test was confirmatory factor analysis (CFA) usenig the LISREL 8.70 software. The results of this study indicate that 23 items are unidimensional, means they only measure one factor, so that a model of one factor is acceptable.

scholarly journals Genomic Bayesian confirmatory factor analysis and Bayesian network to characterize a wide spectrum of rice phenotypes

2018 ◽  
Author(s):  
Haipeng Yu ◽  
Malachy T. Campbell ◽  
Qi Zhang ◽  
Harkamal Walia ◽  
Gota Morota
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Bayesian Network ◽  
Flowering Time ◽  
Latent Variables ◽  
Complex Traits ◽  
Latent Variable ◽  
Grain Morphology ◽  
Hill Climbing ◽  
Confirmatory Factor

AbstractWith the advent of high-throughput phenotyping platforms, plant breeders have a means to assess many traits for large breeding populations. However, understanding the genetic interdependencies among high-dimensional traits in a statistically robust manner remains a major challenge. Since multiple phenotypes likely share mutual relationships, elucidating the interdependencies among economically important traits can better inform breeding decisions and accelerate the genetic improvement of plants. The objective of this study was to leverage confirmatory factor analysis and graphical modeling to elucidate the genetic interdependencies among a diverse agronomic traits in rice. We used a Bayesian network to depict conditional dependencies among phenotypes, which can not be obtained by standard multitrait analysis. We utilized Bayesian confirmatory factor analysis which hypothesized that 48 observed phenotypes resulted from six latent variables including grain morphology, morphology, flowering time, physiology, yield, and morphological salt response. This was followed by studying the genetics of each latent variable, which is also known as factor, using single nucleotide polymorphisms. Bayesian network structures involving the genomic component of six latent variables were established by fitting four algorithms (i.e., Hill Climbing, Tabu, Max-Min Hill Climbing, and General 2-Phase Restricted Maximization algorithms). Physiological components influenced the flowering time and grain morphology, and morphology and grain morphology influenced yield. In summary, we show the Bayesian network coupled with factor analysis can provide an effective approach to understand the interdependence patterns among phenotypes and to predict the potential influence of external interventions or selection related to target traits in the interrelated complex traits systems.

scholarly journals Formation of Social Capital for Community College Students: A Second-Order Confirmatory Factor Analysis

2018 ◽  
Vol 47 (1) ◽  
pp. 3-30 ◽  
Author(s):  
Yu (April) Chen ◽  
Soko S. Starobin
Keyword(s):  
College Students ◽  
Community College ◽  
Social Capital ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Community College Students ◽  
Latent Variables ◽  
Institutional Agents ◽  
Family Social Capital ◽  
Confirmatory Factor

Objective: This quantitative study constructed a statistical model to measure family social capital and college social capital among community college students. The authors also examined influences of these two types of social capital constructs on degree aspiration. Method: This study utilized the STEM (Science, Technology, Engineering and Mathematics) Student Success Literacy Survey (SSSL) to collect data in all 15 community college districts in Iowa. With more than 5,000 responses, the authors conducted descriptive analysis, exploratory and confirmatory factor analysis, and structural equation modeling (SEM) analysis. Results: College social capital was measured by three latent variables such as interaction with advisors, interaction with faculty members, and transfer capital. The three latent variables were further measured by 14 survey items. Family social capital was measured by six survey items that described parent–child interaction in high school. The SEM results indicated that college social capital had stronger direct influences on degree aspiration compared with family social capital. The impact of family social capital was delivered through the mediation of college social capital. Contributions: Findings contributed to the literature by emphasizing the important role of institutional agents in promoting degree aspiration. Intervention programs should be implemented to encourage interactions between institutional agents and underrepresented and disadvantaged students.

Development of a Greek Version of the Sport Motivation Scale

2000 ◽  
Vol 90 (2) ◽  
pp. 505-512 ◽  
Author(s):  
George Doganis
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Internal Consistency ◽  
Factor Models ◽  
Greek Version ◽  
Sport Motivation ◽  
Confirmatory Factor ◽  
Good Internal Consistency ◽  
Motivation Scale ◽  
Sport Motivation Scale

The aim of the present study was to examine preliminarily the validity of a Greek version of the 1995 Sport Motivation Scale of Pelletier, Fortier, Vallerand, Tuson, Briere, and Blais. For 134 athletes the seven subscales had moderate to good internal consistency (Cronbach coefficients α from .64 to .78). Confirmatory factor analysis with nested factor models supported the structural validity of the inventory. Moreover, correlations of scores on the subscales with a measure of task and ego orientation as well as with athletes' self-reported effort in training were in the expected direction.

scholarly journals DETERMINANTS OF ACADEMIC RESEARCH COMMERCIALIZATION IN IRAN GAS INDUSTRY

2013 ◽  
Vol 11 (1) ◽  
pp. 34-49
Author(s):  
Yaghoub Zahedi Anbardan
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Research Methodology ◽  
Latent Variables ◽  
Qualitative Data ◽  
Academic Research ◽  
Gas Industry ◽  
Research Commercialization ◽  
Confirmatory Factor ◽  
Quantitative Results

The aim of this research is to identify determinants of academic research commercialization in the Iranian gas industry. For this purpose, we have applied a mixed research methodology. After reviewing the literature we conducted interviews with academics that have experience in the gas industry commercialization in order to develop the research questionnaire. Qualitative data were analyzed by codifying the interviews. To analyze the quantitative results we applied the exploratory and confirmatory factor analysis (EFA, CFA). The results show that there are 6 latent variables and 28 observed variables including the gas industry academic research commercialization requirements and prerequisites in Iran.

scholarly journals Construction and Validation of Emotional Agility Measurement Tools : Measuring One'S Emotional Agility

2021 ◽  
Vol 10 (1) ◽  
pp. 65-72
Author(s):  
Hana Kamilah ◽  
Hanifah
Keyword(s):  
Mental Health ◽  
Factor Analysis ◽  
Young Adult ◽  
Confirmatory Factor Analysis ◽  
Construct Validity ◽  
P Value ◽  
Reliability Test ◽  
Confirmatory Factor ◽  
Measurement Tools ◽  
Emotional Condition

Mental health includes one’s ability to adjust themselves with the daily stres they experience. On stresful event, there’s always highly emotional condition attached, therefore the ability to regulate emotions becomes vital. Emotional Agility is one’s ability to face emotions, thoughts loosely and move past them to help change or retain behaviors in line with goal and values . In Indonesia, research regarding Emotional Agility and it’s measurement hasn’t been explored much. The instrument are designed based on Emotional Agility theory–Susan David and being tried out to 112 respondents (young adult individuals). The validity test being used pertains to Construct Validity, using model testing Confirmatory Factor Analysis. Reliability test are done using Alpha Cronbach technique. Based on the try out, an instrument of Emotional Agility in Indonesian Version is produced consisting 49 items (p-value=1.00, RMSEA=0.00, CFI=0.97, NFI=0.97, IFI=0.97 and reliability coefficient of 0.860).

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