Báo cáo nghiên cứu khoa học: Research on the effect of teacher burnout displays on student satisfaction in VNU-IS

Abstract This study explores the relationship between teacher-student interaction, teacher burnout, and student satisfaction in an offline educational setting.. Grounded in person-contex

VIETNAM NATIONAL UNIVERSITY, HA NOI

INTERNATIONAL SCHOOL

STUDENT RESEARCH REPORT RESEARCH ON THE EFFECT OF TEACHER BURNOUTDISPLAYS ON STUDENT SATISFACTION IN VNU-IS

KT.NC.SV.23_20

Team Leader: Pham Thi My Kim

ID: 20071050 Class: Dual-MNG2020A

Hanoi, Academic Year 2024-2025

TEAM LEADER INFORMATION

I Student profile

- Full name: Pham Thi My Kim

- Date of birth: 12/04/2002

- Place of birth: Bao Thang ,Lao Cai , Viet Nam

- Class: Dual-MNG2020A

- Program: Dual-Managerment

- Address: My Dinh PEARL 2 , Chau Van Liem , Nam Tu Liem , Ha Noi

- Phone no /Email: 0865204913./20071024@vnu.edu.vn

Advisor

(Sign and write fullname)

Hanoi, April 15th 2024

Team Leader

(Sign and write fullname)

Table of Contents

Abstract 4

1: Introduction 5

2: Literature review 5

3: Research model 6

4 Research methodology 7

4.1 Measurement development 7

Instrument 7

Participants 7

Data collection 8

5 Data analysis and findings 8

5.1 Assessment of the measurement model 8

5.2 Factor analysis 9

5.3 Internal consistency reliability 10

5.5 Discriminant validity 11

5.6 Assessment of the structural model 11

5.6.1 Collinearity issues 11

5.6.2 Explanatory power 13

5.6.3 Relevance of coefficients 13

5.6.4 Assess the significance of coefficients and hypotheses testing 14

6: Discussion and contribution 15

7: Conclusion 15

Abstract

This study explores the relationship between teacher-student interaction, teacher burnout, and student satisfaction in an offline educational setting Grounded in person-context interaction theory, the research model investigates how teacher burnout display influences student

satisfaction directly and indirectly through teacher interaction Data collected from 388

undergraduate students supports the positive association between teacher interaction and student satisfaction However, the hypothesized negative effect of teacher burnout display on student satisfaction was not directly significant An interesting finding is that teacher burnout display does have a negative influence on teacher interaction, suggesting a potential mediating effect These results highlight the importance of teacher-student interaction in fostering student

satisfaction and raise a critical question about the indirect influence of teacher burnout Further research is needed to explore how teacher burnout behaviors may impact student perceptions and satisfaction through the lens of teacher-student interaction This study contributes to the

understanding of factors influencing student satisfaction and provides valuable insights for promoting positive learning environments that prioritize both student well-being and teacher sustainability

1: Introduction

In educational settings, interactions between teachers and students are not only an

important part of the teaching process but also influence students' satisfaction levels and

indicators of their psychological health This interaction not only plays a role in imparting knowledge but also has an influence on student satisfaction and helps reduce the negative effects

of psychological problems they are facing In this context, teacher interactivity in the teaching process not only plays an important role in providing knowledge but can also positively

contribute to student satisfaction in the classroom

2: Literature review

In previous studies, the impact of teacher-student interactions on student satisfaction has received particular attention, especially in the context of online education These studies have shown a positive relationship between teacher-student interactions and student well-being in the classroom Factors such as richness of sound and pleasure from sound have been identified as important factors contributing to student satisfaction, with improvements in these areas leading

to improvements in student satisfaction significantly in classroom satisfaction Additionally, students' technical acceptance of the learning system, combined with its perceived ease and usefulness, has been shown to encourage greater satisfaction on the part of students However, it

is also important to realize that some factors such as audio richness and ease of use can reduce the positive impact of teacher-student interactions in the classroom

In addition, interactions between teachers and students in the face-to-face educational environment also play an important role in shaping student satisfaction In this study, we wanted

to explore the relationship between teacher interactions and the reduction of the effects of

negative psychological problems on students By analyzing teachers' support and presence in the classroom and the quality of their lessons, we highlight the necessity of this interaction in face-to-face education and its positive impact on student achievement student satisfaction

Student satisfaction

In the educational context, student satisfaction plays an important role in assessing the quality of educational services This is especially true in face-to-face educational settings, where the relationship between teacher and student can influence the student's learning experience To better understand student satisfaction, we will refer to this concept, describing the factors that influence student satisfaction in the face-to-face educational environment, including interactions between teacher and student Finally, we will propose methods to improve the quality of

educational services based on insights from our research

Introduces person-context interaction theory and how it applies to psychological and educational research Person-context interaction theory emphasizes the important role of the social environment in shaping human behavior and mood According to this theory, person and contextual influences both contribute to understanding social interactions and individual

cognition The social environment can include cultural, economic, and educational system

factors Presents previous research that uses this theory to understand the relationships between people and their social environment

In psychological and educational research, person-context interaction theory has been widely applied to understand the complex relationships between students and learning

environments Lau and Nie (2008) pointed out that contextual situation can affect students' performance and psychology Sieber and colleagues (2020) studied online educational

environments and emphasized the importance of teacher-student interaction Dalirnaghadeh and Yilmazer's (2022) study focused on the acoustic environment and its influence on students Additionally, Alsharida and colleagues (2021) investigated students' technical acceptance of online education systems

Propose to use this theory to analyze the impact of teacher-student interaction on student satisfaction in offline education With a solid theoretical basis and previous research, we can use person-context interaction theory to analyze the impact of teacher-student interaction in offline educational environments In this way, we can better understand how contextual factors such as traditional learning environments, classroom noise, and student technology acceptance can influence student satisfaction them in the learning process This can help us develop effective educational strategies and improve the learning experience for students in offline education environments Moreover, we want to find out the relationship between the Teacher interaction and effect of it in the process of lower the impact of burnout display on the student satisfaction

3: Research model

Figure 1: Research model

H1 Burnout Teacher Display positively affects on Teacher interaction

H2 Teacher interaction positively affects student satisfaction

H3 Burnout Teacher display positively affects Student satisfaction

4 Research methodology

4.1 Measurement development

Instrument

The items questionnaire was created based on the Teacher-Student Interaction Scale according to

Xu (2016) measured the level of student-teacher interaction using a 5-point scale evaluated from

1 (extremely dissatisfied) to 5 (extremely satisfied) The items used to measure the interaction and support density on and out of class with item such as “Do you feel the good quality

information of lecture which prepared by the teacher.”

This instrument provides a framework for measuring student perceptions of teacher interaction

It can be used in educational research to assess the effectiveness of teaching methods and

classroom environments

Table 0: Measurement sources

Maslach C,

Jackson SE 1984 Emotional display It refer to the emotional display from teacher E 3 James Myron

Henderer 1967 Interpersonal Describe as the relationship of teacher with others RE 1

Xu (2016) Teacher

presence The appear of the teacher on the class P 3

Xu (2016) Information

quality

Measurement the quality of information which is provided

for students

Aldridge, S., &

Rowley, J

(1998)

Student satisfaction

Measure the satisfaction of the students with education service

provided

Participants

Participants were 388 undergraduate students from 3 different universities and different majors in

Ha Noi Participants included 308 females, 78 males, and 2 different The majority of students are known as Sophomore (36,08%), the most of the remaining students are Freshman (26.80%) together with Junior (23.20%) and Senior (13.92%) The students received and voluntarily

completed the questionnaire online, the specific data is shown in Table 1

Data collection

The survey consisted of 4 personal information questions and 11 questions with a 5-point scale response with the preparation in Vietnamese The aim was to survey 200 responses from

undergraduate students from 3 Universities in Ha Noi Participants are the people who are

studying in various majors and received the questionnaire online The survey was conducted in

10 days from 18th March to 28th March and received a total of 388 responses included in the analysis

4.2 Analytical method

This research focus on Partial Least Squares Structural Equation Modeling (PLS-SEM) for data analysis due to its strengths in both prediction orientation and handling complex models with smaller sample sizes (Chin, 1998) This aligns perfectly with our goal of understanding how various factors influence student-teacher interaction Additionally, PLS-SEM aligns with established practices in social science research (Henseler et al., 2016) However, before delving into the core research questions, the analysis prioritizes ensuring reliable data SmartPLS software (version 4.0.9.5) facilitates a two-step process First, the measurement model undergoes assessment to confirm the questionnaire accurately captures the intended constructs (Anderson & Gerbing, 1988) This vital step establishes reliability Then, the analysis proceeds to the structural model, where the hypothesized relationships are examined to determine their significance and illuminate how these factors influence student-teacher interaction

5 Data analysis and findings

5.1 Assessment of the measurement model

The study adopted a well-structured measurement model by utilizing instruments adapted from validated sources This strengthens content validity, suggesting the measures capture the intended constructs Additionally, the use of multi-item scales for most constructs enhances convergent validity, meaning the indicators likely measure the underlying and using the scale from 1 to 5 represent from completely unsatisfied to completely satisfied However, a more comprehensive assessment would benefit from additional information Examining factor loadings would clarify the strength of each indicator's relationship with its construct Reporting reliability estimates like Cronbach's Alpha would assess internal consistency Finally, techniques like Average Variance Extracted (AVE) could be used to ensure the measures for different constructs are distinct

(discriminant validity) One minor point to consider is the use of a confidence scale for online student self-efficacy, which deviates from the standard Likert scale used elsewhere in the study While it might capture the essence of the construct, justification for this difference would be valuable

5.2 Factor analysis

Figure 1: Outer loadings and R 2 of PLS algorithm

Table 2: Outer loadings

Information quality Interpersional

Student satisfaction

Teacher presence

E1 -0.371

E2 0.847

E3 0.876

IN1 0.902

IN2 0.901

P1 0.848

RE 1

S2 -0.438

S3 -0.576

S1 0.89

Indicators with very low loading (below 0.40) belonging to the first-order construct below always be eliminated from the measurement model (Hair, Hult, Ringle & Sarstedt, 2022) and the model was run again Table 3: Adjusted outer loadings Emotional Information quality Interpersonal Student satisfaction Teacher presence P2 0.893 P1 0.864 E2 0.886

E3 0.884

IN1 0.901

IN2 0.902

RE 1

S1 1

All indicator loading after eliminate very low loading indicators (below 4.0) are all above the threshold value of 0.708 (Hair, Risher, Sarstedt, Ringle, 2019) which suggest sufficient level of indicator reliability which are cater for the next assessment of measurement model

5.3 Internal consistency reliability

Table 4:

First-order

construct

Second-order construct

Emotional

0.724 0.879 0.783

Teacher burnout display 0.847 0.907 0.766 Information

quality 0.769 0.897 0.812

Teacher

presence 0.705 0.871 0.772 interaction Teacher 0.853 0.901 0.694

The internal consistency values are displayed in matrix format The results for Cronbach’s alpha and composite are above 0.70 threshold (Hair el at ,.2019), indicating that all construct

measurement are reliable The minimum acceptable AVE is 0.50 or higher indicates the construct explains 50 percent or more of indicator’s variance that make up the construct (Hair et al.,2022), the AVE show of in table … is ranging from 0.69 to 0.8 in scale All these values surpass 0.5 (Chin, 1998), indicating the presence of convergent validity

5.5 Discriminant validity

Table 5:

Emotional

Information quality Interpersonal

Student satisfaction Information quality 0.154

Teacher burnout

Table 5 presents the output from HTMT analysis The HTMT ratios range from 0.126 to 01.24, all below the threshold of 0.85 (Kline, 2015) expecpt Teacher burnout display This suggests there are issues with overlapping with one items across the constructs Given the sensitivity and specificity of the HTMT criterion in identifying discriminant validity problems This supports that there is lack of discriminant validity

5.6 Assessment of the structural model

5.6.1 Collinearity issues

Table 6: VIF

Information quality Interpersional

Student satisfaction

Teacher burnout display

Teacher interaction

Teacher presence

Teacher

burnout

Teacher

Hair et al (2016) emphasized the importance of checking the structural model for collinearity issues This is done by analyzing the variance inflation factor (VIF), which evaluates the

relationship between endogenous constructs and their corresponding exogenous constructs The