Investigating student engagement in blended learning settings using experience sampling and structural equation modeling

2017 ◽  
Vol 35 ◽  
pp. 21-33 ◽  
Author(s):  
Kristine C. Manwaring ◽  
Ross Larsen ◽  
Charles R. Graham ◽  
Curtis R. Henrie ◽  
Lisa R. Halverson
Keyword(s):  
Structural Equation Modeling ◽  
Student Engagement ◽  
Blended Learning ◽  
Structural Equation ◽  
Experience Sampling ◽  
Equation Modeling

scholarly journals Validating the University Student Engagement Model through Structural Equation Modeling

2018 ◽  
Vol 5 (4) ◽  
pp. 318 ◽  
Author(s):  
Hafsa Mzee Mwita
Keyword(s):  
Structural Equation Modeling ◽  
Student Engagement ◽  
Structural Equation ◽  
Factor Model ◽  
University Student ◽  
Equation Modeling ◽  
Psychological Constructs ◽  
Confirmatory Factor ◽  
The University ◽  
Behavior And Cognition

<p><em>The main purpose </em><em>of this study is to investigate whether emotional, cognitive and behavioral engagements, represents three conceptually and empirically distinct psychological constructs when studied within the same domain. This paper reports part of the findings from a major study entitled “Predictors of Self-Handicapping Behavior among Muslim Students”. Testing for factorial equivalence of scores from a measuring instrument was carried-out through structural equation modeling by using AMOS version 16.</em><em> </em><em>Results of Confirmatory Factor Analysis of responses from 790 undergraduates prove that the SEM three factor model of University Student Engagement (USE) is empirically fit and reliable, which also supports the argument that emotion, behavior and cognition are the student engagement manifestations of an interrelated constellation of academic student engagement. </em></p>

scholarly journals A STUDY ON PARTIAL LEAST SQUARES STRUCTURAL EQUATION MODELING (PLS-SEM) AS EMERGING TOOL IN ACTION RESEARCH

2021 ◽  
Author(s):  
Dalowar Hossan
Keyword(s):  
Structural Equation Modeling ◽  
Action Research ◽  
Student Engagement ◽  
Leadership Styles ◽  
Leadership Style ◽  
Structural Equation ◽  
Extrinsic Motivation ◽  
Motivational Factors ◽  
Equation Modeling ◽  
The Relationship

Structural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including educational management. Recent research advocates the use of partial least squares structural equation modeling (PLS-SEM) as an attractive tool in action research. The purpose of this paper is to systematically examine how PLS-SEM has been applied in action research with the aim of investigating the effect of teacher’s leadership styles (transformational and transaction) and student’s motivational factors (intrinsic and extrinsic) on student engagement for implementation of Communicative Language Teaching (CLT) in classrooms as well as explore the mediating role of motivational factors of student between the relationship of teacher’s leadership styles and student engagement. A cross-sectional survey design was used for the study featuring a self-administrated questionnaire among the students of some selected schools in Bangladesh. The transactional leadership style of teachers influences student engagement, intrinsic, and extrinsic motivation while the transformational leadership style of teachers influences the intrinsic and extrinsic motivation of the student. Both motivational factors mediated the relationship between leadership styles and student engagement. This study contributes to the literature by providing teachers with the updated guidelines for action research by using PLS-SEM. The study also suggests the way for increasing student engagement for CLT implementation in classrooms.

scholarly journals Path Analisis Technology Acceptance Model pada Penerapan Blended Learning

2020 ◽  
Vol 6 (2) ◽  
pp. 130-138
Author(s):  
Wawan Laksito Yuly Saptomo ◽  
Elistya Rimawati
Keyword(s):  
Structural Equation Modeling ◽  
Blended Learning ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
E Learning ◽  
Acceptance Model

Model pembelajaran Blended Learning  adalah sistem yang mengkolaborasikan pembelajaran tatap muka kelas dengan pembelajaran online memanfaatkan E-Learning. Penelitian ini bertujuan untuk mengukur tingkat penerimaan dan perilaku peserta didik terhadap teknologi  dari model pembelajaran Blended Learning. Variabel yang dikembangkan merujuk pada Technology Acceptance Model (TAM), yaitu  model penerimaan pengguna terhadap sistem informasi. Model TAM dikembangkan dari teori psikologis yang menjelaskan bahwa perilaku pengguna sistem berlandaskan pada kepercayaan, sikap, keinginan, dan hubungan perilaku pengguna. Data yang diperoleh dianalisis hubungan struktur variabel dengan Structural Equation Modeling (SEM) menggunakan metode Partial Least Square (PLS). Berdasarkan hasil Analisa PLS dan Boostraping diperoleh nilai Pengaruh Langsung, Pengaruh Tidak Langsung, dan Pengaruh tidak langsung sesuai jalur spesifikasi melalui variabel intervening (Spesific Indirect Efect).

scholarly journals Adolescents’ Social Media Experiences and Their Self-Esteem: A Person-Specific Susceptibility Perspective

2021 ◽  
Author(s):  
Patti M. Valkenburg ◽  
J. Loes Pouwels ◽  
Ine Beyens ◽  
Irene Ingeborg van Driel ◽  
Loes Keijsers
Keyword(s):  
Social Media ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Experience Sampling ◽  
Self Esteem ◽  
Equation Modeling ◽  
Specific Effects ◽  
Peer Approval ◽  
Negative Effect ◽  
Specific Susceptibility

The aim of this preregistered study was to compare and explain the effects of (a) time spent on social media (SM), and (b) the valence (positivity or negativity) of SM experiences on adolescents’ self-esteem. We conducted a three-week experience sampling study among 300 adolescents (13-16 years; 126 assessments per adolescent; 21,970 assessments in total). Using an N=1 method of analysis (Dynamic Structural Equation Modeling), we found that the within-person effects of time spent with SM on self-esteem ranged from strongly negative ( = –.31) to moderately positive ( = +.27). Across all ESM observations of the valence of adolescents’ SM experiences, 55% of these experiences were positive, 18% negative, and 27% neutral. Finally, 78% of adolescents experienced a positive within-person effect of the valence of SM experiences on self-esteem ( ≥ +.05), 19% no to very small effects (–.05 &lt; &lt; +.05), and 3% a negative effect ( ≤ –.05). These sizeable differences in person-specific effects could be explained by adolescents’ trait self-esteem level, trait self-esteem instability, and their tendency to base their self-esteem on peer approval.

Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

2014 ◽  
Vol 35 (4) ◽  
pp. 201-211 ◽  
Author(s):  
André Beauducel ◽  
Anja Leue
Keyword(s):  
Structural Equation Modeling ◽  
Negative Correlation ◽  
Structural Equation ◽  
Error Score ◽  
Classical Test Theory ◽  
Test Theory ◽  
Equation Modeling ◽  
Eysenck Personality Questionnaire ◽  
Personality Questionnaire ◽  
True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

The Measurement Invariance of the Short Dark Triad

2020 ◽  
Vol 41 (4) ◽  
pp. 207-218
Author(s):  
Mihaela Grigoraș ◽  
Andreea Butucescu ◽  
Amalia Miulescu ◽  
Cristian Opariuc-Dan ◽  
Dragoș Iliescu
Keyword(s):  
Structural Equation Modeling ◽  
Item Response ◽  
Structural Equation ◽  
Dark Triad ◽  
Theory And Practice ◽  
Equation Modeling ◽  
Scale Level ◽  
High Stake ◽  
Differential Functioning ◽  
Item Functioning

Abstract. Given the fact that most of the dark personality measures are developed based on data collected in low-stake settings, the present study addresses the appropriateness of their use in high-stake contexts. Specifically, we examined item- and scale-level differential functioning of the Short Dark Triad (SD3; Paulhus & Jones, 2011 ) measure across testing contexts. The Short Dark Triad was administered to applicant ( N = 457) and non-applicant ( N = 592) samples. Item- and scale-level invariances were tested using an Item Response Theory (IRT)-based approach and a Structural Equation Modeling (SEM) approach, respectively. Results show that more than half of the SD3 items were flagged for Differential Item Functioning (DIF), and Exploratory Structural Equation Modeling (ESEM) results supported configural, but not metric invariance. Implications for theory and practice are discussed.

Childhood Intelligence Predicts Adult Trait Openness

2016 ◽  
Vol 37 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Adrian Furnham ◽  
Helen Cheng
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Social Background ◽  
Study Data ◽  
Equation Modeling ◽  
Direct Effects ◽  
Data Set ◽  
National Child Development Study ◽  
Nationally Representative ◽  
The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

Sign in / Sign up

Export Citation Format

Share Document