scholarly journals University Student Engagement Scale: Development and Validation in Indian Context

2021 ◽  
pp. 223-235
Author(s):  
Savita Gupta ◽  
Renu Nagpal
Keyword(s):  
Student Engagement ◽  
Prime Factor ◽  
Three Dimensional ◽  
Sampling Technique ◽  
University Student ◽  
Emotional Engagement ◽  
Internal Reliability ◽  
Scale Development And Validation ◽  
Indian Context ◽  
Development And Validation

In academic achievement, student engagement is considered a prime factor to enhance motivation among students. Student engagement is a constructive approach that refers to the level of concentration, inquisitiveness, and enthusiasm that students demonstrate when they learn. The study aims to elucidate the development of a three-dimensional construct of student engagement based on psycho-education oriented measures such as behavioural, cognitive and emotional engagement. Data from 470 students studying in science, humanities, and engineering streams from different universities of Punjab, was collected via random sampling technique. The factor analysis of the scale reveals that 31 items had three factors, behavioural, cognitive, and affective engagement. Good internal reliability (????=0.889) and adequate convergent and discriminant validities are reported, which establishes good psychometric properties of the scale.

scholarly journals The Influence of Student Engagement Towards Learning Achievement of School of Communication and Business Telkom University

2020 ◽  
Vol 3 (1) ◽  
pp. 13-21
Author(s):  
Intan Tamara Febrinzky
Keyword(s):  
Regression Analysis ◽  
Student Engagement ◽  
Descriptive Analysis ◽  
Linear Regression Analysis ◽  
Cognitive Engagement ◽  
Sampling Technique ◽  
Emotional Engagement ◽  
Simple Linear Regression ◽  
Learning Achievement ◽  
Analysis Techniques

This study aims to determine the effect of student engagement on student achievement in the Faculty of Communication and Business, Telkom University. The aspects studied were cognitive engagement, emotional engagement and behavioral engagement in terms of student engagement. And the value of GPA for learning achievement. The method in this study uses descriptive analysis techniques with simple linear regression analysis. To collect the sample using incidental sampling technique through a questionnaire. This questionnaire was distributed to 361 students of the Faculty of Communication and Business Telkom University. From the results of tests conducted, it is found that there is a relationship between student engagement on learning achievement. Where this relationship is perfectly positive correlation. And there is no significant effect between student engagement on learning achievement.

scholarly journals Validitas dan Reliabilitas Skala Student Engagement

2020 ◽  
Vol 11 (2) ◽  
pp. 139
Author(s):  
Mahmud Junianto ◽  
Khoiruddin Bashori ◽  
Nurul Hidayah
Keyword(s):  
High School Students ◽  
Student Engagement ◽  
Discriminant Validity ◽  
Sampling Technique ◽  
Emotional Engagement ◽  
Measurement Tool ◽  
Measuring Instruments ◽  
Measuring Instrument ◽  
Validity And Reliability ◽  
School Students

Research on student engagement has been incrase in recent years. Therefore, to determine the high or low level of student engagement, a valid and reliable measuring instrument is required. This means that the measuring instrument of student engagement must measure only the construct of student engagement reliably and consistently in measurement. The purpose of this research was to test the validity and reliability of the student engagement construct based on Fredrick et al theory. The components of student engagement that are used as a reference for making measuring instruments consist of behavioral engagement, emotional engagement, and cognitive behavior. The study was conducted on 100 high school students using a proportional sampling technique. The measuring instrument is constructed using a semantic differential scaling model. The validity and reliability test used the confirmatory factor analysis (CFA) approach with the help of PLS 3.2.9 software. The results showed that the student attachment measurement tool was declared valid and reliable to be used as a measuring tool. The convergent and discriminant validity tests have met the standards, with loading factor score value of P> 0.5, while the Cronbach alpha reliability score is 0.753 and the composite reliability is 0.835. This measuring instrument is also declared fit with an RSMR value of 0.033. 7 items dropped out of the 18 items tested. Keywords :Student Engagement, Validity,Reliability, Measurement

scholarly journals e-Learning quality: Scale development and validation in Indian context

2012 ◽  
pp. 500-517
Keyword(s):  
Factor Analysis ◽  
Scale Development ◽  
Point Of View ◽  
Covariance Model ◽  
Measurement Scales ◽  
Scale Development And Validation ◽  
Indian Context ◽  
Quality Scale ◽  
E Learning ◽  
Development And Validation

The aim of this paper is to develop a reliable and valid e-learning quality measurement scales from the learner as well as faculty perspectives in Indian context. Exploratory factor analysis followed by confirmatory factor analysis was done which is presented in two forms; covariance model and the structural model. The covariance model shows that the factors namely collaboration, industry acceptance and value addition are important from the learner’s point of view whereas the factors namely transparency in assessment, technical know-how and engagement (from students) are important from faculty point of view. Factors namely course content and design structures (technology/website design) are found equally important for learner’s as well as faculty’s perspective. The structural models validate the previously extracted factors along with their indicators. The findings of this study validate the long held belief that e-learning quality is a multidimensional construct and serves as a critical success factor. The proposed scale will help in identifying issues that contribute towards e-learning quality in Indian context and thereby formulating strategies accordingly, resulting in efficient (in terms of cost) and effective (outcomes) e-learning practices, which is the necessity of the hour for the economic development of the country. A fair amount of literature on e-learning dealt with identifying factors explaining the constructs of quality, perceived value and satisfaction. But there is paucity of research pertaining to e-learning quality scale development and validation from the learner as well as faculty perspective. This study is an attempt to bridge this gap in the existing literature.

Measuring Parents’ Perceptions of Programming Education in P-12 Schools: Scale Development and Validation

2018 ◽  
Vol 57 (5) ◽  
pp. 1260-1280 ◽  
Author(s):  
Siu-Cheung Kong ◽  
Robert Kwok-Yiu Li ◽  
Ron Chi-Wai Kwok
Keyword(s):  
Factor Analysis ◽  
Three Dimensional ◽  
Educational Innovation ◽  
Programming Education ◽  
Scale Development And Validation ◽  
Effective Implementation ◽  
Confirmatory Factor ◽  
Key Factor ◽  
Instrument Measuring ◽  
Development And Validation

Schools around the globe increasingly realized the importance of technology and its application in the education system. To guarantee a successful educational innovation, schools seek out different parties for valuable opinions. Among them, parents are the important feedback providers, because their attitudes are influential on children’s academic performance. Moreover, their involvement and support are considered the key factor that facilitates an effective implementation of programming education at schools. This study aimed at developing and validating an instrument measuring parents’ perceptions of programming education among P-12 schools in Hong Kong. We propose that parents’ perceptions of programming education is a multidimensional construct which constitutes (a) understanding, (b) support, and (c) expectation. In total, 524 questionnaires were collected from the parents who attended programming workshops and seminars. Exploratory factor analysis shows evidence for the three-dimensional construct. Confirmatory factor analysis reconfirms the measurement structure. Implications of the study are discussed.

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