Determinants of Zoom Fatigue among Graduate Students

1. Determinants of Zoom Fatigue
among Graduate Students of
Teacher Education Program
Ryan Michael F. Oducado, PhD1
Baby Rose G. Robles, PhD1, Daisy A. Rosano, PhD1, Rome B. Moralista, PhD2
1West Visayas State University, Philippines
2Guimaras State College, Philippines

2. INTRODUCTION
The rapid transition to online learning in all levels of
education including the graduate program during the
global coronavirus disease outbreak resulted in a
boom of videoconference applications use (Massner, 2021;
Wiederhold, 2020).
It has been observed that Zoom
meeting participants increased
by 2900 percent during the
COVID-19 outbreak (Iqbal, 2021).

3. A new phenomenon of feeling tired and exhausted
during virtual meetings or Zoom fatigue began to
emerge (Fauville et al., 2021).
Given that this new phenomenon appeared only
recently with the pandemic, there is still limited data
about Zoom fatigue especially in graduate education.
There is a need to explore Zoom fatigue in the
educational context particularly among graduate
students as online remote learning is likely to play a
substantial role in teaching and learning even beyond
the pandemic (de Oliveira Kubrusly Sobral et al., 2022; Massner, 2021)

4. • There are growing body of evidences on the likely
negative physical and psychological consequences
of Zoom meetings (Oducado et al., 2021; Poskakalova et al., 2021;
Salim et al., 2021; Usta Kara & Ersoy, 2022).
• Evidence also shows that students find it harder to
focus and are often less responsive during online
synchronous Zoom classes that undesirably affects
the nonverbal dynamics in online classes (Peper et al.,
2021).
• Identifying and addressing the factors that
contribute to videoconference exhaustion
experience of graduate students is necessary.

5. OBJECTIVES
This study determined the level of Zoom
fatigue among graduate students in the
Philippines.
This study also tried to examine if attitude
toward virtual meetings and non-verbal
factors are significantly associated with
Zoom fatigue in the context of graduate
teacher education.

6. METHODS
RESEARCH DESIGN
Descriptive-correlational
Cross-sectional
PARTICIPANTS
109
A-priori sample size calculator: 97
6 predictors
.05 desired probability level
.15 anticipated effect size
80% desired statistical power level
Average age: 29 years old
82.6% 17.4%
Master’s = 75.2%
Doctoral = 24.8%
Graduate students
Teacher Education

7. INTRUMENT &
DATA COLLECTION
Zoom Exhaustion & Fatigue scale
by Fauville et al. (2021)
Online survey (Google Forms)
March 2022
DATA ANALYSIS
SPSS v26
Mean, SD, f, %
Pearson’s r
Multiple linear regression analysis
Level of significance set at .05

8. RESULTS
Level of Zoom fatigue
Zoom fatigue Mean SD Description
General 3.80 .73 High
Visual 3.61 .96 Moderate
Motivational 3.51 .97 Moderate
Social 3.11 1.16 Moderate
Emotional 2.81 1.06 Moderate
ZEF score 3.37 .79 Moderate

9. • It was demonstrated in this research that graduate
students generally had moderate level of Zoom
fatigue.
• Virtual platform communication is said to be more
mentally exhausting than traditional face-to-face
communication (Tobing et al., 2022).
• About comparable levels of fatigue were noted from
the Standford study (Fauville et al., 2021), Indonesian
university students (Salim et al., 2021) and among Filipino
teachers (Oducado et al., 2022) and this study.

10. Correlational analysis
Variables Pearson’s r p-value
Attitude -.301 .001
Non-verbal mechanisms
Cognitive load in producing non-verbal cues .397 .000
Sense of being physically trapped .386 .000
Hyper gaze .320 .001
Mirror anxiety .240 .012
Cognitive load in interpreting non-verbal
cues
-.104 .284

11. Regression analysis
Variables B t p-value
(Constant) 2.107 2.702 .008
Sense of being physically trapped .379 3.478 .001
Cognitive load in producing non-verbal cues .156 2.044 .044
Attitude -.175 -1.514 .133
Mirror .082 .878 .382
Hyper gaze .065 .769 .444
Cognitive load in interpreting non-verbal cues -.129 -1.741 .085
R Square = .304, F = 7.419, p = .000

12. • The result replicates the findings of prior research
abroad (Fauville et al., 2021) and in the Philippines (Oducado
et al., 2021; Oducado et al., 2022) wherein sense of being
physically trapped was the strongest predictor of
Zoom fatigue.
• Being nonresponsive when attending synchronous
Zoom class can exacerbate Zoom fatigue symptoms
that may decrease learning capacity and attention
(Peper & Yang, 2021).

13. Zoom users need to
stay within the field
view of the camera
resulting to reduced
mobility when sitting
down and staring
straight ahead for
most of the time
during
videoconferencing
(Bailenson, 2021).

14. • Moreover, cognitive load in producing non-verbal
cues predicted higher levels of fatigue.
• This finding corroborates with that of the finding
from Standford (Fauville et al., 2021) and studies
conducted in the Philippines (Oducado et al., 2021; Oducado et
al., 2022).

15. Zoom users need to work
harder to send nonverbal
signals contributing to
higher levels of fatigue
(Bailenson, 2021).

16. • This research also demonstrated that while not
significant predictors, hyper gaze and mirror
anxiety were significantly correlated with Zoom
fatigue.

17. • Higher level of hyper haze was associated with
great levels of fatigue.
• In video conferencing platforms, people get the
front-on views of all other people for hours
consecutively and the amount close-up eye contact
can be intense (Bailenson, 2021).
Hyper gaze Zoom fatigue

18. • This study also found that higher levels of mirror
anxiety was linked to higher levels of fatigue.
• It has been explained that seeing a mirror image of
oneself for several hours in virtual meeting can
likely lead to negative self-focused attention
(Bailenson, 2021; Ratan et al., 2022).
Mirror anxiety Zoom fatigue

19. • This study also noted that more negative attitude towards
videoconferences was significantly correlated with higher
levels of Zoom fatigue.
• Similar findings were found in other studies conducted in
other countries (Fauville et al., 2021) and among
undergraduate students and teachers in the Philippines
(Oducado et al., 2021; Oducado et al., 2022).
• Understanding the role of attitudes is important because it
may likely influence strength of intention and acceptance or
use of videoconferencing platform in the future (Fishman et
al., 2021; Pedroso et al., 2021).
Attitude Zoom fatigue

20. CONCLUSION
• This study highlights that the present study generally
supports previous research on the association of
attitude toward videoconferences and the role of non-
verbal mechanisms specific to the use of virtual
conference on Zoom fatigue experience.
• While videoconferencing applications supported
educational activities during the global disease
outbreak, it is recommended to be mindful of the non-
verbal factors that contribute to Zoom fatigue and
know how to optimize current features on Zoom to help
minimize the exhaustion during virtual meetings.

21. • Despite the significant findings, this research has
limitations that could influence the generalizability and
reliability of our findings.
• This study only involves a sample of students in graduate
teacher education in one university in the Philippines,
used cross-sectional design that cannot establish causal
effect between variables, and employed questionnaires
that can lend itself to self-report bias.
• Despite these limitations, our research adds to the body
of knowledge on Zoom fatigue and can also be useful in
informing the design of effective strategies against the
unintended negative effects of videoconferencing tools.