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Molecular & Cellular Biomechanics 2024, 21(3), 396.
https://doi.org/10.62617/mcb396
1
Article
The impact of ergonomics and biomechanics on optimizing learning
environments in higher education management
Kang Liu1,*, Yiwen Zhou2
1 Faculty of Education, Lomonosov Moscow State University, 119991 Moscow, Russia
2 Zhejiang Ocean University, Zhoushan 316000, China
* Corresponding author: Kang Liu, peacelucher1@outlook.com
Abstract: In higher education, the design of learning environments is serious in prompting
student well-being, engagement, and academic performance. Traditional classrooms often lack
ergonomic consideration, leading to discomfort, increased physical strain, and reduced
concentration. As education evolves, there is a growing need to apply ergonomic and
biomechanical principles to create spaces that accommodate students’ diverse physical and
cognitive needs. Despite the theoretical support for these interventions, there is limited
empirical evidence on their practical impact in educational settings. This study addresses this
gap by examining the effects of ergonomic and biomechanical adjustments on student
outcomes in higher education. Utilizing a mixed-methods approach, the research was
conducted across four universities with a diverse sample of 126 students. The interventions
included adjusting furniture, optimized spatial layouts, and environmental adjustments to
assess their influence on postural alignment, muscle activity, and engagement. Key findings
revealed significant improvements: postural alignment showed an increase in spinal angle from
118° to 133° and a reduction in neck angle from 37° to 29°. Muscle activity, particularly in the
neck and lower back, decreased by 40% and 44%, respectively. Additionally, self-reported
comfort improved from a mean of 2.8 to 4.3, while physical strain decreased from 3.7 to 2.2.
Engagement levels also improved, with scores rising from 3.1 to 4.5. These results underscore
the importance of ergonomic design in promoting student well-being and fostering a more
conducive learning environment, providing evidence-based recommendations for optimizing
learning spaces in higher education.
Keywords: biomechanical models; biomechanical principles; ergonomic design;
biomechanical interventions; physical strain; learning environment; postural alignment;
muscle activity
1. Introduction
The increasing complexity of Learning Environments (LE) in Higher Education
(HE) demands a comprehensive approach to enhance student well-being, engagement,
and academic performance [1,2]. As educational institutions continue to evolve, there
is a growing recognition of the need to design spaces that cater to students’ diverse
physical and cognitive needs [3]. Traditional classroom settings, frequently
categorized by static furniture, inadequate lighting, and limited consideration for
students’ physical postures, can inadvertently contribute to discomfort, reduced focus,
and even long-term musculoskeletal issues [4,5]. This has prompted an emphasis on
ergonomic and Biomechanical Principles (BP) in educational design, aiming to create
more inclusive and adaptive LE [6]. Ergonomics, optimizing LE for human use, is
critical in ensuring that learning spaces accommodate students’ varying body sizes,
CITATION
Liu K, Zhou Y. The impact of
ergonomics and biomechanics on
optimizing learning environments in
higher education management.
Molecular & Cellular Biomechanics.
2024; 21(3): 396.
https://doi.org/10.62617/mcb396
ARTICLE INFO
Received: 20 September 2024
Accepted: 8 October 2024
Available online: 14 November 2024
COPYRIGHT
Copyright © 2024 by author(s).
Molecular & Cellular Biomechanics
is published by Sin-Chn Scientific
Press Pte. Ltd. This work is licensed
under the Creative Commons
Attribution (CC BY) license.
https://creativecommons.org/licenses/
by/4.0/
Molecular & Cellular Biomechanics 2024, 21(3), 396.
2
abilities, and movement patterns [7]. Complementing this, biomechanics provides
insights into the physical mechanics of human movement, offering a detailed
understanding of how different spatial and furniture designs impact posture, muscle
activity, and overall physical strain [8].
The integration of ergonomic theories, such as Fitts’ Law [9], Person-
Environment Fit (P-E Fit) Theory [10], Cognitive Ergonomics [11], and
Anthropometric Theory [12], has been pivotal in the design of educational spaces that
enhance comfort and reduce physical strain. For example, Fitts’ Law [9] informs the
optimal placement of learning tools and furniture to minimize unnecessary movement,
while P-E Fit Theory [10] underscores the importance of aligning the physical
environment with individual student needs, including those with physical disabilities.
Cognitive Ergonomics [11] extends this by considering the mental processes involved
in learning, advocating for clear, organized layouts that minimize cognitive load and
support information retention. Anthropometric Theory [12] further contributes by
emphasizing the importance of designing furniture that accommodates the diverse
body dimensions of students, thereby promoting neutral postures and reducing the risk
of discomfort and fatigue. These ergonomic considerations, when effectively applied,
can foster an engaging and comfortable learning atmosphere that not only supports
students’ physical well-being but also enhances their academic performance [13].
Biomechanics complements ergonomic design by providing a scientific
understanding of the human body’s interaction with physical spaces [14].
Biomechanical models, such as the Kinetic Chain Model (KCM), Center of Gravity
and Balance Model (CGBM), and Biomechanical Load and Stress Model (BLSM),
highlight the importance of supporting natural body mechanics to prevent strain
and injury [15]. For instance, the KCM emphasizes the need for furniture that
supports natural alignment across various body segments, red ucing muscle and
joint stress [16]. The CGBM advocates for seating designs that promote a stable
and balanced posture, minimizing the likelihood of adopting poor postures like
slouching. Meanwhile, the BLSM focuses on distributing physical loads across the
body, ensuring that seating and desk designs minimize strain on critical areas like
the spine, neck, and lower back [17]. Applying these models in educational settings
can lead to the development of environments that support dynamic movement and
variability in posture, which are crucial for maintaining musculoskeletal health and
enhancing cognitive function [18].
Despite the growing body of research supporting the integration of ergonomics
and biomechanics in educational design, there remains a gap in the practical
application of these principles within HE settings [19]. Many classrooms use static
furniture and layouts that do not fully accommodate students’ dynamic and diverse
needs [20]. This can result in increased physical strain, decreased comfort, and a
negative impact on engagement and learning outcomes. To address this gap, there is a
need for comprehensive studies that explore the effects of ergonomic and
Biomechanical Interventions (BI) on student well-being and academic performance.
Such research can provide valuable insights into how LE can be optimized to promote
physical health and cognitive engagement, ultimately fostering a more effective and
inclusive educational experience.
Molecular & Cellular Biomechanics 2024, 21(3), 396.
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The proposed work seeks to bridge the gap between theoretical ergonomics and
BP and their practical application in HE-LE. This study will be conducted across four
diverse universities, involving 126 participants from various academic disciplines, age
groups, and physical abilities. The research employs a mixed-methods approach,
integrating quantitative and qualitative data collection techniques to comprehensively
analyze how ergonomics and BI impact students’ physical well-being and engagement.
Quantitative assessments will include measurements of posture, muscle activity, and
movement patterns using tools like digital goniometers, electromyography (EMG)
sensors, and motion capture systems. Classroom furniture, such as desks and chairs,
will be modified to meet ergonomic standards, including adjustable heights, lumbar
support, and appropriate spatial layouts. Environmental factors like lighting and noise
levels will also be optimized to meet ergonomic guidelines. In addition to the objective
measurements, qualitative data will be collected through focus group discussions,
interviews, and classroom observations to capture students’ subjective experiences.
This aspect of the study aims to explore students’ perceptions of comfort, physical
strain, and concentration concerning the ergonomic and biomechanical conditions of
their LE.
The Objectives of the Work include:
(a) To assess the current ergonomic and biomechanical conditions in HE-LE by
measuring students’ posture, muscle activity, and movement patterns during
typical academic activities.
(b) To evaluate the impact of ergonomic interventions, such as adjustable furniture,
optimized lighting, and improved spatial layouts, on reducing physical strain and
enhancing postural alignment among students.
(c) To analyze the correlation between ergonomic adjustments and engagement
levels, focusing on how changes in the physical environment impact students’
comfort, concentration, and participation.
(d) To explore students’ subjective experiences regarding comfort and physical strain
concerning ergonomic conditions, qualitative methods like focus groups and
interviews are used to provide a holistic understanding of the learning experience.
The paper is organized as follows: Section 2 presents the theoretical framework,
Section 3 presents the methodology, Section 4 presents the analysis, and Section 5
concludes the work
2. Theoretical framework
2.1. Ergonomic theories
Ergonomic theories focus on designing LE tools and systems that optimize
human well-being and performance. In learning spaces, human-centered design is
crucial for creating environments that accommodate students’ diverse physical and
cognitive needs [21–25].
i) Fitts’ Law: Fitts’ Law is a foundational ergonomics theory that the time
required to move to a target area is influenced by the distance to and size of the target.
In the context of LE, this theory has implications for placing furniture, equipment, and
learning materials. By ensuring that essential items are within optimal reach and
arranged to minimize unnecessary movement, designers can reduce physical strain and
Molecular & Cellular Biomechanics 2024, 21(3), 396.
4
enhance the ease of access for students. For example, workstations, desks, and
educational tools should be positioned to allow natural movement paths, reducing the
time and effort needed to interact with them. This not only improves comfort but also
aids in maintaining a smooth workflow during learning activities, fostering a more
efficient and engaging educational experience.
ii) Person-Environment Fit (P-E Fit) Theory: The Person-Environment Fit (P-E
Fit) theory emphasizes the alignment between an individual’s features and their close
environment. In educational settings, this theory supports the idea that when students’
physical and cognitive needs are met through a well-designed environment, their
comfort and academic performance are enhanced. This includes providing adjustable
furniture, appropriate lighting, and acoustics designed to cater to diverse learning
needs, including those with physical disabilities or specific learning requirements. For
instance, height-adjustable desks and ergonomic chairs can accommodate various
body sizes and postures, reducing musculoskeletal strain and promoting a dynamic
and inclusive learning experience. When students can interact comfortably with their
LE, their engagement and overall well-being improve, leading to better academic
outcomes.
iii) Cognitive Ergonomics Theory: Cognitive Ergonomics theory extends
ergonomic considerations to the mental processes involved in learning, such as
perception, memory, and attention. According to this theory, learning spaces should
be designed to minimize cognitive load by providing a clear, organized layout that
facilitates ease of understanding and interaction. This involves reducing distractions,
ensuring adequate lighting, and arranging educational tools to support intuitive use.
For example, visual ergonomics play a crucial role in classroom design—adequate
contrast, appropriate font sizes on displays, and ensuring that teaching materials are
easily visible all contribute to enhanced information retention and focus. By reducing
unnecessary cognitive effort through effective design, LE can support students’ mental
processing, improving their ability to concentrate, comprehend, and retain information.
iv) Anthropometric Theory: Anthropometric Theory uses human body
measurements to design physical spaces, including furniture and spatial layouts. In LE,
this theory emphasizes creating seating, desks, and equipment that align with students’
diverse body sizes and shapes. Using anthropometric data, designers can ensure that
learning spaces support neutral postures, reducing the risk of physical strain and
discomfort. For instance, chairs should support the natural curve of the spine, and
desks should be at a height that allows students to sit with their feet flat on the floor
and elbows at a 90-degree angle when typing or writing. Properly designed
environments that accommodate these physical features can prevent discomfort and
fatigue, allowing students to maintain focus and participate more actively in learning
activities.
2.2. Biomechanical models
Biomechanical models are crucial in understanding how human movement
interacts with the physical environment, particularly in educational settings [26–30].
These models focus on the mechanical principles governing human motion, including
Molecular & Cellular Biomechanics 2024, 21(3), 396.
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posture, muscle activity, and joint movement, to create environments that support
natural and efficient bodily functions [31–33].
i. KCM: The KCM views the human body as a series of interconnected segments
that work together to move. This model emphasizes the importance of supporting
the body’s natural movement patterns to prevent strain and injury in educational
settings. For instance, when students are seated for extended periods, the kinetic
chain suggests that the positioning of the feet, legs, hips, spine, and neck
contributes to overall posture and comfort. Educators can reduce muscle and joint
stress by designing chairs and desks that accommodate the natural alignment of
these body segments, such as providing adequate support for the lower back and
allowing for proper leg positioning. This improves comfort and reduces fatigue,
enabling students to focus more effectively during learning activities.
ii. CGMB: The CCBM examines how the body’s center of gravity and balance
influence stability and movement efficiency. This model informs furniture design
and spatial layouts in LE that promote a stable and balanced posture. For example,
seating that allows students to maintain their feet flat on the floor and their knees
at a right angle helps keep the center of gravity over the base of support, reducing
the likelihood of adopting poor postures like slouching. Desks at an appropriate
height enable students to balance their upper bodies without needing forward-
leaning or shoulder elevation. Learning spaces can enhance student comfort and
reduce the risk of musculoskeletal issues by ensuring that the body’s center of
gravity is aligned correctly.
iii. BLSM: The BLSM provides insight into how different physical environments
affect the load and stress placed on the body during activities. This model is
essential for understanding how seating, desk height, and spatial layout impact
students’ physical well-being in educational settings. For example, using a desk
that is too high can lead to elevated shoulders and increased muscle tension in the
neck and shoulders. Conversely, a desk that is too low can cause a forward-
hunched posture, placing excessive load on the spine. By applying this model to
educational furniture design, designers can ensure that physical loads are
distributed evenly across the body, reducing the risk of strain and enhancing
comfort during activities such as writing, typing, and reading.
iv. Ergonomic Posture and Movement Model (EPMM): The EPMM integrates
biomechanical principles to promote optimal posture and movement patterns in
LE. This model emphasizes the dynamic nature of posture, advocating for spaces
that allow and encourage movement rather than static positions. In classrooms,
this translates to providing adjustable furniture that supports a variation of
postures and movements, such as standing desks or chairs designed for natural
shifting and fidgeting. By incorporating movement into learning spaces, this
model recognizes the human body’s need for variability in posture to maintain
musculoskeletal health and prevent discomfort associated with prolonged static
postures. Furthermore, it aligns with research suggesting that periodic movement
can enhance cognitive function and concentration, improving the learning
experience.
Molecular & Cellular Biomechanics 2024, 21(3), 396.
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2.3. Interaction between ergonomics and biomechanics
Though distinct in focus, Ergonomics and biomechanics interact synergistically
to create physically supportive and cognitively stimulating LE. Ergonomics centers on
designing spaces that align with human capabilities and limitations, emphasizing
factors like comfort, usability, and safety. Biomechanics, on the other hand, delves
into the mechanics of human movement, focusing on how the body interacts with
physical forces. These fields offer a comprehensive approach to optimizing LE by
addressing human interaction’s static and dynamic aspects in educational spaces.
Integrating ergonomic principles with biomechanical models enables the creation
of spaces that support natural body mechanics while promoting cognitive and physical
well-being. For instance, ergonomic designs, informed by biomechanical insights, can
lead to the development of adjustable furniture that caters to various body sizes and
shapes. Chairs with proper lumbar support and desks at the right height can help
maintain neutral postures, reducing strain on the spine and minimizing the risk of
musculoskeletal disorders. Biomechanics further refines this approach by providing a
detailed analysis of the optimal angles and positions for joints during different
activities, ensuring that students can move fluidly and comfortably within their LE.
This interaction also extends to the dynamic aspects of learning, such as
movement and variability in posture. While ergonomics emphasizes the importance of
a well-designed, static workspace, biomechanics highlights the need for dynamic
movement to prevent the physical fatigue associated with prolonged sitting. Together,
they advocate for LE to encourage movement by using standing desks or flexible
seating arrangements that allow students to shift positions quickly. This promotes
physical health by preventing stiffness, enhancing circulation, and supporting
cognitive function. Research suggests that physical movement can stimulate brain
activity and improve concentration, enhancing learning outcomes.
Moreover, the combined application of ergonomics and biomechanics supports
inclusivity in educational settings. By considering both the ergonomic needs (such as
adjustability and comfort) and biomechanical requirements (such as range of motion
and joint alignment), learning spaces can be designed to accommodate a wide range
of students, including those with physical disabilities. For example, adjustable desks
and chairs can cater to students using wheelchairs or those requiring different seating
postures, ensuring that the learning environment is accessible and comfortable for
everyone. This holistic approach fosters an inclusive atmosphere where all students
can engage effectively in learning.
3. Methodology
3.1. Population
The study’s population consisted of 126 students recruited from four higher
education institutions, carefully selected to represent a diverse cross-section of the
student body. This diversity was crucial for comprehensively analyzing how
ergonomics and biomechanics impact LE. The demographic composition included 78
Males and 48 Females, ranging in age from 18 to 30 years, capturing the typical range
of HE students, including Undergraduate (UG) and Postgraduate (PG) levels. Students
Molecular & Cellular Biomechanics 2024, 21(3), 396.
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came from various academic disciplines, such as science, humanities, engineering, and
the arts, ensuring that the study could assess ergonomic and biomechanical needs
across different learning activities and LE. Notably, the study also included students
with varying physical abilities, including those with physical disabilities, to provide a
more inclusive perspective on the ergonomic and biomechanical challenges faced
within educational settings.
The research was conducted across four universities, representing a mix of
traditional and modern LE, such as lecture halls, active learning classrooms, and
laboratories. Initial recruitment involved outreach to approximately 200 students
across HE institutions, with 150 students expressing initial willingness to participate.
This phase included a preliminary screening to identify individuals meeting the study’s
eligibility criteria, which required students to be enrolled in one of the participating
universities and actively engage in on-campus learning activities. Furthermore,
students with severe musculoskeletal or neurological conditions were excluded to
focus on typical ergonomic and biomechanical interactions in educational settings.
Of the 150 students who expressed interest, 140 met the eligibility criteria and
were shortlisted for the study. During the detailed briefing phase, 14 students withdrew
due to personal reasons or scheduling conflicts, resulting in a final count of 126
students. This final group was evenly distributed across the four universities, ensuring
a balanced representation of different LEs. Among them, 78 were males and 48 were
females, with the academic background further broken down into 32 students from
science, 28 from humanities, 40 from engineering, and 26 from the arts. The sample
also included 12 students with physical disabilities, such as mobility impairments,
providing valuable insights into these individuals’ ergonomic challenges and how
learning spaces can be optimized for inclusivity. Table 1 presents the characteristics
of the selected participants.
Table 1. Population characteristics for your study.
Characteristic
Details
Total Participants
126
Gender Males
78
Gender Females
48
Age Range
18–30 years
Academic Levels UG
92
Academic Levels PG
34
Academic Disciplines Science
32
Academic Disciplines Humanities
28
Academic Disciplines Engineering
40
Academic Disciplines Arts
26
Physical Abilities—Students with Physical Disabilities
12
Number of Universities
4
Initial Willingness
150
Shortlisted Participants
140
Withdrawals
14
Final Participants
126
Molecular & Cellular Biomechanics 2024, 21(3), 396.
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3.2. Research design
The study was conducted using a mixed-methods research design, integrating
qualitative and quantitative approaches to thoroughly analyze the impact of
ergonomics and biomechanics on LE through direct engagement with the participants.
For the quantitative component, students underwent a series of assessments involving
several ergonomic and biomechanical tools. These included evaluations of classroom
furniture, lighting, and spatial layout to measure how these factors influenced students’
posture, movement patterns, and physical strain during regular academic activities.
Measurements such as posture angles, reach distances, and muscle activity levels were
recorded using digital goniometers, EMG sensors, and motion capture systems.
Students also completed surveys and questionnaires to gauge their perceptions of
comfort, physical well-being, and engagement in their learning environments. This
data was then subjected to statistical analysis to identify patterns and correlations
between ergonomic and biomechanical factors and student outcomes.
In the qualitative component, a subgroup of participants was selected to share
their subjective experiences in more depth. Focus group discussions and in-depth
interviews were conducted to explore students’ insights into their LE. These
discussions delved into comfort, fatigue, concentration, and overall experience,
providing rich, descriptive data. Additionally, classroom observations were recorded,
allowing researchers to observe how students naturally interacted with LE, including
how they adapted their posture and utilized available furniture during learning
activities. This qualitative data offered valuable context to the quantitative findings,
helping to explain how ergonomic and biomechanical factors influenced students’
comfort and learning behaviors.
3.3. Apparatus
The apparatus used in this study included a range of ergonomic and
biomechanical assessment tools to measure and analyze the physical characteristics of
LE and their impact on students. For the ergonomic evaluation, instruments such as
digital goniometers and posture analysis software were utilized to assess students’
postural alignment and body angles during typical learning activities like sitting,
typing, and reading. Adjustable ergonomic chairs and desks were provided to measure
their impact on students’ posture and comfort, allowing for adjustments in seat height,
backrest angle, and desk height to suit individual students. Additionally, light and
decibel meters were employed to measure classroom lighting and noise levels,
ensuring these environmental factors met ergonomic standards for optimal learning
conditions.
For the biomechanical assessment, the study used EMG sensors to monitor
muscle activity and detect levels of physical strain experienced by students in different
postures. Classroom motion capture systems were set up to track students’ movements
and identify common patterns that may lead to discomfort or fatigue. This system
provided real-time data on joint angles, movement velocities, and body alignment,
offering a detailed analysis of students’ interactions with their environment. To further
understand the physical load experienced by students, force plates were utilized to
Molecular & Cellular Biomechanics 2024, 21(3), 396.
9
measure pressure distribution on seating surfaces, highlighting how different chair
designs influenced weight distribution and pressure points.
In addition to these primary tools, surveys and questionnaires were developed to
collect subjective data from participants regarding their comfort levels, perceived
physical strain, and overall satisfaction with the LE. This self-reported data was crucial
for correlating the objective measurements with students’ personal experiences.
Observation checklists were also used during classroom observations to systematically
record students’ behaviors, postural adjustments, and interactions with furniture and
equipment.
3.4. Measurements
The measurements in this study encompassed a change of ergonomic and
biomechanical parameters to assess the LE and its effects on students comprehensively.
For the ergonomic assessment, several key metrics were measured:
i. Postural Angles: Using digital goniometers and posture analysis software, the
angles of students’ joints, such as the spine, neck, shoulders, elbows, and knees,
were recorded during activities like sitting, reading, and typing. This data helped
identify deviations from neutral postures that could lead to discomfort or
musculoskeletal strain.
ii. Workspace Dimensions: Measurements included the height, depth, and width of
desks, chairs, and other classroom furniture. The objective was to evaluate
whether these dimensions adhered to ergonomic standards for students of
different body sizes and shapes.
iii. Environmental Factors: Light meters were used to measure the intensity of
classroom lighting (in lux), ensuring it met recommended levels for optimal
visual comfort. Decibel meters recorded noise levels within the learning spaces
to assess their potential impact on concentration and comfort.
In the biomechanical assessment, the focus was on quantifying the physical strain
and movement patterns of students:
i. Muscle Activity: EMG sensors were applied to measure muscle activity in areas
commonly affected by prolonged sitting, such as the neck, shoulders, and lower
back. EMG readings provided data on muscle engagement and fatigue, indicating
how different postures and furniture setups influenced physical strain.
ii. Movement Analysis: Motion capture systems tracked students’ movements to
measure joint angles, velocities, and body alignment during typical classroom
activities. This provided insights into movement patterns and postural changes,
identifying any biomechanical risk factors associated with the LE.
iii. Pressure Distribution: Force plates were used to measure pressure distribution on
seating surfaces. This helped assess how different chair designs affected weight
distribution and identified areas of high pressure that could lead to discomfort.
Additionally, subjective measurements were collected to complement the
objective data:
i. Self-Reported Comfort and Strain: Surveys and questionnaires were administered
to gather students’ subjective perceptions of comfort, physical strain, and
satisfaction with the LE. Students rated their comfort levels and reported any
Molecular & Cellular Biomechanics 2024, 21(3), 396.
10
physical discomfort they experienced during classes, which was then correlated
with the objective measurements.
ii. Behavioral Observations: Systematic observations were conducted using
checklists to record students’ postural adjustments, movement frequency, and
interaction with classroom furniture. This qualitative data provided context to the
quantitative measurements, highlighting how students adapted to LE over time.
Table 2 presents the apparatus and the measurements used in this study.
Table 2. Apparatus and measurement.
Apparatus
Measurements
Units
Digital Goniometers
Postural Angles (spine, neck, shoulders,
elbows, knees)
Degrees (°)
Posture Analysis Software
Joint Angles during activities like sitting
and typing
Degrees (°)
Adjustable Ergonomic Chairs and
Desks
Workspace Dimensions (height, depth,
width)
Centimeters (cm)
Light Meters
Classroom Lighting Intensity
Lux
Decibel Meters
Classroom Noise Levels
Decibels (dB)
EMG Sensors
Muscle Activity (neck, shoulders, lower
back)
Microvolts (µV)
Motion Capture Systems
Movement Patterns (joint angles,
velocities, alignment)
Degrees (°), m/s
Force Plates
Pressure Distribution on Seating
Surfaces
Newtons (N)
Surveys and Questionnaires
Self-Reported Comfort and Physical
Strain
Likert Scale (1–5)
Observation Checklists
Behavioral Observations (postural
adjustments, movement)
Descriptive Data
3.5. Data collection and analysis
Data Collection for this study involved a systematic approach, utilizing
quantitative and qualitative methods to gather comprehensive insights into the impact
of ergonomics and biomechanics on LE. The quantitative data were collected through
a series of structured assessments conducted in the classroom with 126 participants.
Using ergonomic tools like digital goniometers, posture analysis software, and EMG
sensors, researchers measured students’ posture angles, muscle activity, and
movement patterns during typical learning activities such as sitting, typing, and
reading. Workspace dimensions, including desk and chair heights, were recorded
alongside environmental factors like lighting intensity and noise levels using light and
decibel meters. Surveys and questionnaires were distributed to all participants to
capture their self-reported perceptions of comfort, physical strain, and engagement in
the LE. This data provided a numerical basis for analyzing classroom ergonomic and
biomechanical conditions.
For the qualitative data, a subset of participants was selected for focus group
discussions and in-depth interviews to explore their subjective experiences in the LE.
These sessions were designed to delve into students’ insights into comfort, fatigue,
and concentration, offering a nuanced understanding of how ergonomic and
Molecular & Cellular Biomechanics 2024, 21(3), 396.
11
biomechanical factors affected their learning experiences. Classroom observations
were also conducted, wherein researchers systematically noted students’ behaviors,
postural adjustments, and interactions with furniture and equipment. These
observations provided context to the quantitative measurements, illustrating how
students naturally adapted to their environment. Data Analysis involved both statistical
and thematic methods. Quantitative data were analyzed using statistical software to
identify patterns, correlations, and potential causal relationships between ergonomic
factors (like desk height or lighting) and biomechanical outcomes (such as posture or
muscle strain). Descriptive statistics summarized the key features of the data, while
inferential statistics, such as correlation analysis, were used to explore relationships
between variables, such as the impact of ergonomic adjustments on comfort and
engagement levels. For the qualitative data, thematic analysis was employed.
Transcripts from focus group discussions and interviews were coded to identify
recurring themes related to student’s experiences and perceptions of their LE. This
analysis helped uncover more profound insights into how students felt about their
classrooms’ ergonomic and biomechanical aspects. Observational data were also
reviewed to identify student interaction patterns with the LE, such as standard postural
adjustments or adaptive behaviors.
4. Results
Table 3. Descriptive statistics.
Measurement
Baseline Mean
Baseline SD
Post-Intervention Mean
Post-Intervention SD
Units
Postural Angles (Spine)
118
9
133
7
Degrees (°)
Postural Angles (Neck)
37
7
29
4
Degrees (°)
Postural Angles (Shoulders)
14
4
11
3
Degrees (°)
Workspace Dimensions (Desk Height)
72
4
76
2
Centimeters (cm)
Workspace Dimensions (Chair Height)
44
3
47
3
Centimeters (cm)
Lighting Intensity
320
45
480
40
Lux
Noise Levels
62
6
48
5
Decibels (dB)
Muscle Activity (Neck)
18
5
11
3
Microvolts (µV)
Muscle Activity (Lower Back)
23
6
15
4
Microvolts (µV)
Self-Reported Comfort
2.9
1.2
4.2
0.9
Likert Scale (1–5)
Self-Reported Physical Strain
3.6
1.0
2.1
0.7
Likert Scale (1–5)
Engagement Levels
3.1
1.1
4.5
0.8
Likert Scale (1–5)
The descriptive statistics, as shown in Table 3, indicate significant improvements
in postural alignment, ergonomic conditions, and student well-being after the
interventions. Postural Angles for the spine improved, with the mean increasing from
118° (SD = 9) to 133° (SD = 7), indicating a more upright posture. Neck angles showed
a decrease in mean from 37° (SD = 7) to 29° (SD = 4), reflecting reduced forward head
posture. Shoulder angles also improved, with a reduction in mean from 14° (SD = 4)
to 11° (SD = 3). Workspace dimensions saw adjustments, with desk height increasing
from a mean of 72 cm (SD = 4) to 76 cm (SD = 2) and chair height from 44 cm (SD =
3) to 47 cm (SD = 3), aligning better with ergonomic standards. Lighting intensity
Molecular & Cellular Biomechanics 2024, 21(3), 396.
12
increased from 320 lux (SD = 45) to 480 lux (SD = 40), while noise levels decreased
from 62 dB (SD = 6) to 48 dB (SD = 5), contributing to a more conducive LE. Muscle
activity readings showed a reduction, with neck muscle activity decreasing from 18
µV (SD = 5) to 11 µV (SD = 3) and lower back muscle activity from 23 µV (SD = 6)
to 15 µV (SD = 4), indicating less physical strain. Self-reported comfort improved
significantly, with the mean increasing from 2.9 (SD = 1.2) to 4.2 (SD = 0.9) on the
Likert scale. Conversely, physical strain decreased from a mean of 3.6 (SD = 1.0) to
2.1 (SD = 0.7). Engagement levels also rose from a mean of 3.1 (SD = 1.1) to 4.5 (SD
= 0.8), suggesting enhanced student participation and focus.
Table 4 and Figure 1 show the analysis of postural alignment differences,
revealing significant improvements with ergonomic adjustments. Postural angles
(spine) showed a higher mean of 132° for adjustable desks than 118° for standard
desks, with a t-value of 4.56 and a p-value of 0.001, indicating a statistically significant
difference. Neck angles were lower in adjustable desks, with a mean of 28° versus 36°
for standard desks (t-value = 3.92, p-value = 0.002), suggesting reduced forward head
posture. Shoulder angles also improved, with a mean of 10° for adjustable desks
compared to 15° for standard desks (t-value = 2.87, p-value = 0.005). Regarding
standard postural deviations, forward head posture frequency was notably higher with
standard desks at 22%, compared to 9% with adjustable desks. Rounded shoulders
were observed in 18% of students using standard desks versus 11% with adjustable
desks. Slouched sitting was more prevalent in standard desk users at 19%, as opposed
to 7% for those using adjustable desks. These results highlight the effectiveness of
ergonomic adjustments in promoting better posture and reducing the occurrence of
postural deviations.
Table 4. Differences in postural alignment based on ergonomic adjustments and standard postural deviations.
Comparison
Mean (Adjustable
Desk)
Mean (Standard Desk)
t-value
p-value
Significance
Postural Deviation
Frequency (%)
Postural Angles
(Spine)
132°
118°
4.56
0.001
Significant
15% (Standard Desk)
Postural Angles
(Neck)
28°
36°
3.92
0.002
Significant
25% (Standard Desk)
Postural Angles
(Shoulders)
10°
15°
2.87
0.005
Significant
20% (Standard Desk)
Postural Deviation
(Forward Head
Posture)
9%
22%
-
-
-
22% (Standard Desk)
Postural Deviation
(Rounded Shoulders)
11%
18%
-
-
-
18% (Standard Desk)
Postural Deviation
(Slouched Sitting)
7%
19%
-
-
-
19% (Standard Desk)
Molecular & Cellular Biomechanics 2024, 21(3), 396.
13
Figure 1. postural alignment analysis.
The correlation analysis shown in Table 5 and Figure 2 indicates significant
negative relationships between ergonomic factors and physical strain. Desk height
showed a strong negative correlation with neck muscle activity (r = −0.62, p = 0.001)
and lower back muscle activity (r = −0.55, p = 0.002). This suggests optimal desk
height is associated with reduced neck and lower back muscle strain. Chair design
factors also demonstrated significant correlations. Lumbar support had the highest
negative correlation with lower back muscle activity (r = −0.68, p = 0.001), indicating
that chairs with proper lumbar support substantially reduce lower back strain. Seat
height was negatively correlated with thigh muscle activity (r = −0.47, p = 0.004),
implying that correct seat height can alleviate strain on the thighs. Seat depth
negatively correlated with knee muscle activity (r = −0.39, p = 0.011), suggesting that
adequate seat depth helps reduce knee strain. Lastly, backrest angle was negatively
correlated with neck muscle activity (r = −0.58, p = 0.002), indicating that an
appropriate backrest angle can significantly reduce neck strain.
Table 5. Correlation between ergonomic factors and physical strain.
Ergonomic Factor
Physical Strain (EMG Data)
Correlation Coefficient (r)
p-value
Significance
Desk Height
Neck Muscle Activity (µV)
−0.62
0.001
Significant
Desk Height
Lower Back Muscle Activity (µV)
−0.55
0.002
Significant
Chair Design (Lumbar Support)
Lower Back Muscle Activity (µV)
−0.68
0.001
Significant
Chair Design (Seat Height)
Thigh Muscle Activity (µV)
−0.47
0.004
Significant
Chair Design (Seat Depth)
Knee Muscle Activity (µV)
−0.39
0.011
Significant
Chair Design (Backrest Angle)
Neck Muscle Activity (µV)
−0.58
0.002
Significant
Molecular & Cellular Biomechanics 2024, 21(3), 396.
14
Figure 2. Correlation between ergonomic factors and physical strain.
The analysis of the correlation between workspace dimensions and muscle
activity levels is shown in Table 6 and Figure 3, and it shows significant reductions
in muscle strain when using optimal ergonomic setups. For desk height, the mean
muscle activity in the neck muscles decreased from 20 µV in suboptimal setups to 12
µV in optimal setups, resulting in a 40% reduction in strain (p = 0.001). Similarly,
lower back muscle activity reduced from 18 µV to 10 µV, a 44% decrease (p = 0.002),
indicating the positive impact of an optimal desk height. Chair height adjustments led
to a notable reduction in thigh muscle activity, decreasing from a mean of 16 µV in
suboptimal conditions to 9 µV in optimal setups, a 43.75% reduction (p = 0.003). Chair
seat depth also significantly affected knee muscle activity, reducing from 14 µV to 8
µV, equating to a 42.86% decrease (p = 0.004). Chair backrest angle had a similar
impact, reducing neck muscle activity by 42.11% (from 19 µV to 11 µV, p = 0.001).
Footrest availability contributed to a 41.18% reduction in lower leg muscle activity,
decreasing from 17 µV in suboptimal setups to 10 µV in optimal setups (p = 0.002).
These results underscore the importance of optimizing workspace dimensions such as
desk height, chair height, seat depth, backrest angle, and footrest availability to
minimize muscle strain and improve physical comfort.
Table 6. Correlation between workspace dimensions and muscle activity levels.
Workspace
Dimension
Muscle Group
Mean Muscle Activity
(Suboptimal Setup, µV)
Mean Muscle Activity
(Optimal Setup, µV)
% Reduction in
Muscle Activity
Significance (p-
value)
Desk Height
Neck Muscles
20
12
40%
0.001
Desk Height
Lower Back Muscles
18
10
44%
0.002
Chair Height
Thigh Muscles
16
9
43.75%
0.003
Chair Seat Depth
Knee Muscles
14
8
42.86%
0.004
Chair Backrest
Angle
Neck Muscles
19
11
42.11%
0.001
Footrest
Availability
Lower Leg Muscles
17
10
41.18%
0.002
Molecular & Cellular Biomechanics 2024, 21(3), 396.
15
Figure 3. Correlation between workspace dimensions and muscle activity levels.
Table 7 and Figure 4 show that the survey and questionnaire analysis
significantly improved after ergonomic interventions. Self-reported comfort increased
notably, with the pre-intervention mean of 2.8 (SD = 1.1) rising to a post-intervention
mean of 4.3 (SD = 0.9). The median also improved from 3 to 4, indicating a shift
toward higher comfort levels. The t-value of 6.75 and a p-value of 0.001 indicate that
this change is statistically significant. Self-reported physical strain significantly
decreased, with the mean reducing from 3.7 (SD = 1.0) to 2.2 (SD = 0.8). The median
dropped from 4 to 2, showing a considerable reduction in perceived strain. The t-value
of −5.89 and a p-value of 0.002 confirm the significance of this reduction. Engagement
levels also improved, with the pre-intervention mean of 3.2 (SD = 1.0) increasing to
4.4 (SD = 0.7) post-intervention. The median moved from 3 to 4, suggesting enhanced
student engagement. This change was statistically significant, as indicated by a t-value
of 5.32 and a p-value of 0.001.
Table 7. Analysis of survey and questionnaire responses.
Measureme
nt
Pre-
Interventi
on Mean
Pre-
Interventio
n Median
Pre-
Intervention
SD
Post-
Intervent
ion Mean
Post-
Intervention
Median
Post-
Interventio
n SD
t-value
p-value
Significanc
e
Self-
Reported
Comfort (1–
5 Scale)
2.8
3
1.1
4.3
4
0.9
6.75
0.001
Significant
Self-
Reported
Physical
Strain (1–5
Scale)
3.7
4
1.0
2.2
2
0.8
−5.89
0.002
Significant
Engagement
Level
(Overall)
(1–5 Scale)
3.2
3
1.0
4.4
4
0.7
5.32
0.001
Significant
Molecular & Cellular Biomechanics 2024, 21(3), 396.
16
Figure 4. Analysis of survey and questionnaire responses.
Table 8 and Figure 5 shows the analysis of engagement levels by demographics
and ergonomic conditions, which shows notable improvements across all groups after
ergonomic interventions. Male students experienced increased engagement, with the
mean rising from 3.1 to 4.2, showing a difference of +1.1. Female students had a
slightly higher improvement, with their engagement mean increasing from 3.3 to 4.5,
a difference of +1.2. Students with physical disabilities demonstrated the most
significant change, with their engagement mean increasing from 2.9 to 4.4, marking a
difference of +1.5. This indicates a substantial positive impact of ergonomic
adjustments on this group. Regarding ergonomic conditions, those in the optimal
ergonomic setup group saw an increase in engagement from a mean of 3.4 to 4.6, a
difference of +1.2. Meanwhile, the suboptimal ergonomic setup group also showed
improvement, with engagement levels rising from 3.0 to 4.0, reflecting a +1.0
difference.
Table 8. Engagement levels by demographics and ergonomic conditions.
Demographic/Condition
Pre-Intervention Engagement Mean
Post-Intervention Engagement Mean
Difference
Male Students
3.1
4.2
+1.1
Female Students
3.3
4.5
+1.2
Students with Physical Disabilities
2.9
4.4
+1.5
Optimal Ergonomic Setup
3.4
4.6
+1.2
Suboptimal Ergonomic Setup
3.0
4.0
+1.0
Figure 5. Demographics and ergonomic conditions analysis for engagement.
Molecular & Cellular Biomechanics 2024, 21(3), 396.
17
The pattern recognition analysis in movement data, as shown in Table 9 and
Figure 6, reveals a significant decrease in behaviors associated with discomfort
following ergonomic interventions. Frequent postural shifts reduced from a pre-
intervention frequency of 63% to 33%, showing a 47.6% decrease, primarily related
to poorly designed chairs and desks. This reduction indicates decreased physical strain
post-intervention. Forward leaning dropped from 38% to 17%, a 55.3% decrease
associated with the lack of backrest support and low desk height, reducing neck and
shoulder strain. Slouching or slumped posture decreased from 52% to 19%, a 63.5%
reduction, highlighting the impact of non-adjustable seating on lower back discomfort.
Crossed leg sitting declined by 58.6%, from 29% to 12%, due to insufficient seat depth,
which improved hip and knee alignment. Standing or fidgeting reduced from 21% to
11%, a 47.6% decrease, reflecting relief from prolonged sitting discomfort through
adjustable furniture. Stretching and adjustments dropped from 33% to 14%, a 57.6%
decrease, often linked to poor ergonomic setups. The reduction in these behaviors
post-intervention indicates increased static postures and suggests enhanced comfort
and stability.
Table 9. Pattern recognition in movement data.
Movement Pattern
Pre-Intervention
Frequency
Post-Intervention
Frequency
Change (%)
Associated Ergonomic
Condition
Impact on Physical Strain
Frequent Postural
Shifts
63%
33%
−47.6%
Poorly designed chairs and
desks
Decreased physical strain
post-intervention.
Forward Leaning
38%
17%
−55.3%
Lack of backrest support,
low desk height
Reduced neck and shoulder
strain.
Slouching or
Slumped Posture
52%
19%
−63.5%
Non-adjustable seating
Reduced lower back
discomfort.
Crossed Leg Sitting
29%
12%
−58.6%
Insufficient seat depth
Improved hip and knee
alignment.
Standing or Fidgeting
21%
11%
−47.6%
Prolonged sitting
discomfort
Enhanced comfort with
adjustable furniture.
Stretching and
Adjustments
33%
14%
−57.6%
Poor ergonomic setup
Increased static postures
post-intervention.
Figure 6. Pattern recognition in movement data.
Molecular & Cellular Biomechanics 2024, 21(3), 396.
18
5. Conclusion and future work
This study demonstrates the significant impact of ergonomics and BI on
enhancing LE in HE. By integrating principles such as Fitts’ Law, Person-
Environment Fit Theory, and various biomechanical models, the research successfully
highlights the importance of creating adaptable and inclusive educational spaces that
cater to students’ diverse physical and cognitive needs. The interventions, including
using adjustable furniture, optimized spatial layouts, and attention to environmental
factors like lighting and noise, resulted in marked improvements in postural alignment,
reductions in muscle strain, and enhanced engagement levels. Key findings, such as
the increase in spinal angle from 118° to 133° and the decrease in neck muscle activity
by 40%, provide concrete evidence of the positive effects of ergonomic adjustments
on student well-being. Moreover, the study reveals that ergonomic interventions can
significantly improve self-reported comfort and reduce physical strain, with comfort
levels rising from a mean of 2.8 to 4.3 and strain decreasing from 3.7 to 2.2. Enhanced
engagement levels, with scores increasing from 3.1 to 4.5, further indicate that a well-
designed LE supports physical health and fosters cognitive engagement and academic
performance. These findings underscore the crucial role of ergonomics and
biomechanics in educational design, advocating for adopting adaptive LE that
accommodates a range of student requirements, including those with physical
disabilities.
Author contributions: Conceptualization, KL and YZ; methodology, KL and YZ;
software, KL and YZ; validation, KL and YZ; formal analysis, KL and YZ;
investigation, KL and YZ; resources, KL and YZ; data curation, KL and YZ; writing—
original draft preparation, KL and YZ; writing—review and editing, KL and YZ;
visualization, KL and YZ; supervision, KL and YZ; project administration, KL and
YZ; funding acquisition, KL and YZ. All authors have read and agreed to the published
version of the manuscript.
Ethical approval: Not applicable.
Conflict of interest: The authors declare no conflict of interest.
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