scholarly journals Sociological Importance and Validation of a Questionnaire for the Sustainability of Personal Learning Environments (PLE) in 8th Grade Students of the Biobío Region in Chile

2019 ◽  
Vol 11 (5) ◽  
pp. 1301 ◽  
Author(s):  
José Luis Carrasco-Sáez ◽  
Marcelo Careaga Butter ◽  
María Graciela Badilla-Quintana ◽  
Laura Jiménez Pérez ◽  
Juan Molina Farfán
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Latent Variables ◽  
Human Interaction ◽  
Two Dimensional ◽  
Human Beings ◽  
Personal Learning ◽  
New Instrument ◽  
Confirmatory Factor ◽  
8Th Grade

Contemporary society is going through a cultural transition that leads to new conceptions about the ways in which human beings organize socially and communicate. This process of deep social and cultural transformations is characterized by a technological disruption, in which virtuality forms a new dimension that behaves as an extension of human intelligence. This new form of human interaction impacts on the social imagination, demanding one to rethink social and educational paradigms for the two-dimensional citizen. In this context, this research article describes the sociological importance and the process of social adaptation of users to a personal learning environment (PLE). It includes the validation process of an instrument for the study of the PLE of 8th grade students belonging to 15 schools in the Biobío Region of Chile. A PLE is a frame of reference that can help to understand how two-dimensional citizens socially adapt and influence the sustainability of local and global systems. The validation method for this instrument considered four stages: i) Expert judgment: considering the opinions of six educators and experts in information and communication technologies (ICT); ii) a pilot test: that included a non-probabilistic sample of 472 subjects; iii) a principal components analysis (PCA); and iv) a confirmatory factor analysis (CFA). The Questionnaire on Work Habits and Learning for Professional Futures and the Context Questionnaire SIMCE TIC were used as a reference. When performing a psychometric analysis, a Cronbach alpha coefficient of 0.89 was obtained. This confirms that the adaptation of the instrument is good. The results of the dimensional analysis help us define a structure for the new instrument considering three components that explain 55% of the total variance. The results of the confirmatory factor analysis showed adjustment indexes that support the theoretical model proposed for the PLE study. In conclusion, the instrument was composed of three latent variables: Open self-regulated learning (OSRL) with eight questions, information management (IM) with four questions, and creation and transfer of knowledge (CTK) with four questions.

scholarly journals Analysis of Psychometric Properties and Validation of the Personal Learning Environments Questionnaire (B-PLE) in Higher Education Students

2021 ◽  
Vol 13 (16) ◽  
pp. 8736
Author(s):  
José Luis Carrasco-Sáez ◽  
Marcelo Careaga Butter ◽  
María Graciela Badilla-Quintana ◽  
Juan Molina-Farfán
Keyword(s):  
Higher Education ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Learning Environments ◽  
Latent Variables ◽  
Cultural Transition ◽  
Personal Learning ◽  
New Instrument ◽  
Confirmatory Factor ◽  
Personal Learning Environments

We are living through a cultural transition, characterized by technological disruption and the erosion of the modern ideology, which are redefining the behavior of citizens in their physical and digital spaces. Virtuality emerges as a new human dimension, making it necessary to rethink social and educational paradigms for a new two-dimensional citizen. In this context, the psychometric features and validation procedure of an instrument (B-PLE) for analyzing Personal Learning Environments (PLE) in students of higher education institutions in the Biobío Region of Chile are described. There were four phases to the validation method: (i) content validity, as determined by six experts in education and ICT; (ii) pilot test, with a non-probabilistic sample of 327 subjects; (iii) principal components analysis (PCA); and (iv) confirmatory factor analysis (CFA). The results of the dimensional analysis made it possible to define the structure of the new instrument, explaining 72% of the total variance. The reliability analysis yielded an alpha coefficient of 0.92. The confirmatory factor analysis showed fit indexes that support the proposed theoretical model. In conclusion, the instrument was composed of three latent variables: Open learning (OL), with six questions, Information management (IM), with two questions, and Knowledge creation and transfer (KCT), with three questions.

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.

ASSESSING STATISTICS ANXIETY IN AN ONLINE OR HYBRID SETTING: THE ADAPTION AND DEVELOPMENT OF A NEW INSTRUMENT SASOH

2021 ◽  
Vol 20 (1) ◽  
pp. 2
Author(s):  
Lu Liu
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Mathematics Anxiety ◽  
Discriminant Validity ◽  
Item Analysis ◽  
Statistics Anxiety ◽  
Four Dimensions ◽  
New Instrument ◽  
Confirmatory Factor ◽  
Attitudes Toward Statistics

With the purpose of developing an instrument for measuring statistics anxiety in the online or hybrid setting, this study tested the newly developed instrument in two stages. Results on item selection and exploratory factor analysis based on pilot testing (n = 115) are presented. Results on classical item analysis, the confirmatory factor analysis, the measurement invariance test results, and the predictive and discriminant validity of the final model based on formal testing (n = 709) are presented. The resulting Statistics Anxiety Scale in the Online or Hybrid setting instrument (SASOH) has 27 items and four dimensions. The four dimensions are Class and Interpretation Anxiety (CI), Fear of Asking for Help Anxiety (FA), Online System Anxiety (OS), and Pre-Conception Anxiety (PC). The results of the confirmatory factor analysis revealed that the four-factor SASOH model represents an adequate description of statistics anxiety in an online or hybrid setting. Moreover, multiple-groups confirmatory factor analysis affirmed that the resulting model achieved at least partial measurement and structural invariance across gender and program. In addition, attitudes toward statistics significantly predicts the four factors of statistics anxiety, and the discriminant validity from mathematics anxiety was confirmed. Recommendations for future studies are also provided.

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.

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 Measurement Invariance pada Indonesian Tawadhu Scale (ITS)

2020 ◽  
Vol 3 (2) ◽  
pp. 71-86
Author(s):  
Yonathan Natanael ◽  
Mirna Devi ◽  
Yasril Ananta Burhanudin ◽  
Jamiludin Nur
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Research Method ◽  
Measuring Instrument ◽  
Multidimensional Model ◽  
New Instrument ◽  
Confirmatory Factor ◽  
Instrument Testing ◽  
Multiple Groups ◽  
Interpersonal Dimension

The purpose of this study to develop a new instrument of tawadhu that valid, unbiased, and can be used in Indonesia. The research method uses combination similarization in Islamic Psychological studies and psychological construction scale. The number of participants in this research is 613 Muslims with range 16 to 45 years old. Instrument consists of 7 items measuring intrapersonal dimension and 13 items measuring interpersonal dimension. Methods that used measuring instrument testing are Aiken validity and Multiple Groups Confirmatory Factor Analysis (MGCFA) with a multidimensional model. The results of Aiken analysis show that all items are valid measuring tawadhu. Also, MGCFA shows that Indonesian Tawadhu Scale is an unbias scale. This instrument can be used by Muslims in Indonesia as it integrates the concept of Psychology and Islam.

scholarly journals A SCALE DEVELOPMENT STUDY FOR IDENTIFYING THE LEVELS OF KNOWLEDGE, PERCEPTION AND AWARENESS OF CHEMICAL HAZARD SYMBOLS

2014 ◽  
Vol 13 (2) ◽  
pp. 165-181
Author(s):  
Cemal Tosun
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Age Groups ◽  
Two Dimensional ◽  
Validity And Reliability ◽  
Multiple Choice Questions ◽  
One Dimensional ◽  
The Third ◽  
Chemical Hazard ◽  
Confirmatory Factor

The purpose of this study was to develop a scale to identify the levels of knowledge, perception and awareness of chemical hazard symbols of participants from a variety of backgrounds and ranging in age from 12 years to 40 and over. Experts were consulted for the contextual and the language validity of each item on the scale. In line with the opinions of the experts, the scale, consisting of a total of 25 items distributed under four sections, was applied to 462 participants of all age groups, so as to calculate the discrimination and difficulty indexes. In order to decide whether the third section of the scale is one-dimensional or two-dimensional, data obtained from the 13 multiple-choice questions constituting this section were examined using confirmatory factor analysis. Afterwards the items constituting the second and the third sections of the scale were tested in terms of their reliability. Finally, a useful scale of 24 items in four sections was prepared with tested validity and reliability. Key words: awareness, confirmatory factor analysis, hazard symbols, perception, reliability, validity.

scholarly journals Evaluation of the Social Benefits of Financial Innovation Towns Based on SEM Model——Taking Yuhuang Shannan Fund Town as an Example

2021 ◽  
Vol 251 ◽  
pp. 01075
Author(s):  
Guimei Wu ◽  
Yuting Ye ◽  
Ting Li ◽  
Xueqin Chen ◽  
Shasha Zhu
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Latent Variables ◽  
Evaluation System ◽  
Structural Equation ◽  
Financial Innovation ◽  
Social Benefits ◽  
The Social ◽  
Confirmatory Factor ◽  
The Impact

Taking Yuhuang Shannan Fund Town as a typical example, this paper established a financial innovation characteristic town social benefit evaluation system through on-site investigation and quantitative analysis. It can be summarized into five major aspects: social and livelihood development, socioeconomic development, ecological environment, infrastructure construction and related system construction. Then we constructed a structural equation model (SEM) for the evaluation of social benefits of towns, and made the assumption that the impact of the five latent variables on the total variable of social benefits is positive. Through the first-order confirmatory factor analysis and the second-order confirmatory factor analysis of the structural equation, it is concluded that the five latent variables have a positively significant impact on the social benefits and have strong internal consistency. According to the degree of influence, effective suggestions are given from private equity and industrial foundation, which provide reference and practical guidance of the construction of financial innovative towns in the future.

Testing Factorial Invariance across Groups: A Reconceptualization and Proposed New Method

1999 ◽  
Vol 25 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Gordon W. Cheung ◽  
Roger B. Rensvold
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Latent Variables ◽  
Cross Cultural ◽  
Factorial Invariance ◽  
Published Data ◽  
Data Set ◽  
Test Items ◽  
Confirmatory Factor ◽  
Different Cultures

Many cross-cultural researchers are concerned with factorial invariance; that is, with whether or not members of different cultures associate survey items, or similar measures, with similar constructs. Researchers usually test items for factorial invariance using confirmatory factor analysis (CFA). CFA, however, poses certain problems that must be dealt with. Primary among them is standardization, the process that assigns units of measurement to the constructs (latent variables). Two standardization procedures and several minor variants have been reported in the literature, but using these procedures when testing for factorial invariance can lead to inaccurate results. In this paper we review basic theory, and propose an extension of Byrne, Shavelson, and Muthgn’s (1989) procedure for identifying non-invariant items. The extended procedure solves the standardization problem by performing a systematic comparison of all pairs of factor loadings across groups. A numerical example based upon a large published data set is presented to illustrate the utility of the new procedure, particularly with regard to partial factorial invariance.

Sign in / Sign up

Export Citation Format

Share Document