Applying 4E Cognition to Acoustic Design: A Theoretical Framework for University Learning Environments

Abstract

The 4E Cognition paradigm offers a novel theoretical framework for understanding how acoustic environments influence cognitive processes in university learning spaces. This research integrates objective characterization of environmental parameters with comprehensive subjective evaluation of student experience to explore how aural conditions relate to cognitive processes and physiological stress responses in university learning environments. The study recruited 126 university students from the Engineering Faculty of “G. D’Annunzio” University, with final analysis including 66 valid responses from 28 participants in the acoustically treated classroom and 38 from the control condition. The results revealed modest associations between environmental conditions and cognitive performance measures, with small to moderate effect sizes (Cohen’s d ranging from 0.02 to 0.31). While acoustic treatment produced measurable improvements in speech intelligibility and acoustic quality ratings, differences in cognitive load and allostatic load indices were minimal between conditions. These findings provide preliminary empirical insights for applying the 4E Cognition framework to educational settings, suggesting that acoustic interventions may require extended exposure periods or more intensive treatments to produce substantial physiological and cognitive effects. This work contributes to the emerging field of cognitive architecture by introducing an innovative theoretical approach that reconceptualizes acoustic environments as potential cognitive extensions rather than mere background conditions. The findings offer initial evidence-based insights for integrating environmental considerations into educational facility design, while highlighting the need for longitudinal studies to fully understand how acoustic environments function as cognitive scaffolding in learning contexts.

1. Introduction

The relationship between environmental conditions and cognitive processes has been a central concern in philosophy of mind and cognitive sciences since the early 20th century. This awareness has evolved from simple observations of environmental influence to sophisticated theoretical frameworks that fundamentally challenge the traditional boundaries between mind, body, and environment. The recognition that thinking extends beyond the confines of the individual brain has profound implications for architectural design, particularly in educational settings where cognitive performance is paramount.

Recent architectural research has increasingly recognized the importance of environmental factors in supporting cognitive processes, with neuroarchitecture that demonstrates measurable impacts of built environments on human cognition and well-being [1,2]. The field of cognitive architecture has emerged to address how built environments can be designed to enhance human cognitive performance, moving beyond traditional aesthetic considerations to evidence-based design approaches that integrate psychological and neurological insights into architectural practice [3,4].

A pivotal moment in this theoretical evolution was the introduction of the Extended Mind Theory by Clark and Chalmers in 1997 [5]. This groundbreaking framework proposed that human cognitive processes are not confined within the limits of the brain but extend into the surrounding environment through tools, technologies, and environmental structures. This perspective opened pathways to an even broader approach that recognizes the direct and continuous interaction between mind, body, and environment.

The 4E Cognition paradigm has emerged as a comprehensive framework that encompasses four fundamental dimensions of cognitive processes: cognitive processes are intrinsically embodied in bodily experience embodied, situated in specific contexts embedded, emerging from interaction with the environment enactive, and distributed between neural systems and environmental structures extended [6]. This paradigm represents a radical departure from traditional computational models of cognition, positioning environmental design as an integral component of cognitive architecture.

In acoustic terms, this framework suggests that sound environments are not merely external stimuli to be processed, but become integral components of how we think, learn, and interact. The embodied dimension recognizes that acoustic experience involves our entire physical being, the embedded dimension acknowledges that the same cognitive task requires different strategies depending on the acoustic context, the enactive dimension emphasizes how we actively shape our acoustic environment through behavior, and the extended dimension proposes that well-designed acoustic spaces can function as cognitive tools that enhance our mental capabilities.

In academic contexts, this theoretical framework finds its ideal empirical testing ground. University classrooms, in particular, host activities that require sustained concentration, processing of complex information, and social interaction [7]. The cognitive demands of higher education make these environments particularly sensitive to environmental factors that can either support or hinder learning processes.

Among environmental parameters, acoustics plays a fundamental role in educational contexts [8,9]. Indoor Environmental Quality (IEQ), particularly acoustic quality, is a critical determinant of the holistic educational experience, significantly influencing the well-being, concentration, and performance of students [10,11]. The acoustic environment of classrooms can significantly influence attentional mechanisms, language comprehension, and working memory [12,13]. Background noise, excessive reverberation times, and poor speech intelligibility impose a greater mental effort on students [14], creating what cognitive load theory describes as an extraneous cognitive load that diverts mental resources from learning objectives.

Speech intelligibility has become a crucial factor in educational settings [15]. Students positioned in different locations within classrooms experience varying levels of auditory clarity, with those in rear sections of spacious classrooms often facing weakened vocal signals and excessive reverberation that challenge effective listening [16,17]. Since most learning activities involve oral communication, the intelligibility of spoken words—defined as the percentage of correctly understood speech items—is crucial for successful learning [18,19].

Background noise presents a complex challenge in educational buildings. Ambient noise levels from external sources, student behavior, and internal service equipment significantly contribute to overall background noise, directly affecting speech intelligibility and cognitive performance [20,21]. Recent research emphasizes that good acoustic quality in classrooms is essential for creating optimal learning environments, with soundscape research in indoor environments gaining attention for its potential to contribute to healthier and more comfortable educational spaces [22].

The increase in cognitive load also carries a physiological cost that the human body pays in attempting to adapt to adverse environmental conditions. Prolonged exposure to acoustically inadequate environments can not only compromise information processing capabilities but can also activate physiological stress responses, including increased blood pressure, altered heart rate, and metabolic variations [23].

The cumulative physiological stress resulting from prolonged activation of responses to stressful situations, known as allostatic overload, can further compromise student well-being and performance. This concept, introduced by McEwen and Stellar [24], describes the wear and tear on the body that accumulates as an individual is exposed to repeated or chronic stress. In educational environments, this translates to a concerning cycle where poor acoustic conditions lead to increased cognitive effort, physiological stress, and ultimately reduced learning capacity [25].

Engineering classrooms present unique acoustic challenges due to their intensive cognitive demands and specific environmental characteristics. Students in engineering faculties are typically exposed to cognitive workloads that require high levels of concentration and precision. Additionally, these classrooms often feature noisy mechanical equipment, reflective surfaces, and complex geometries that can influence sound propagation, creating particularly challenging acoustic environments for sustained cognitive performance [26].

Contribution of This Work

This research applies the 4E Cognition paradigm to educational acoustic environments, combining established methodological approaches from architectural acoustics and environmental psychology in a novel application context. While individual components of our methodology draw from existing validated approaches, their integration for examining acoustic–cognitive relationships through the 4E framework in educational settings represents a new application of these established methods. The study explores how acoustic environments might function beyond simple background conditions by examining them through the lens of embodied, embedded, enactive, and extended cognition, offering a different theoretical perspective on environmental design considerations.

From a methodological standpoint, this work integrates three established assessment approaches: objective acoustic characterization following international standards, subjective acoustic perception evaluation using validated instruments, and subjective assessment of allostatic load through self-reported measures. While each method is well-established in its respective field, their combined application within the 4E Cognition framework for educational acoustic environments has not been systematically explored in previous literature. The study design comparing identical classrooms that differ only in acoustic treatment allows for controlled examination of these relationships, though we acknowledge the modest effect sizes observed suggest the complexity of these interactions may require different approaches or longer exposure periods to detect meaningful effects.

The practical contribution lies in providing initial empirical evidence for how established cognitive science frameworks might inform acoustic design decisions in educational settings. Rather than proposing revolutionary changes to current practice, this work offers a systematic approach to examining environmental factors through cognitive science principles, potentially informing evidence-based design decisions. The findings suggest that while acoustic improvements produced measurable changes in objective parameters and some subjective acoustic ratings, the relationship between environmental modifications and subjective cognitive–physiological responses may be more complex than initially hypothesized, highlighting areas for future investigation.

The ultimate objective is to contribute to understanding how established design approaches might be informed by cognitive science principles, providing a foundation for future research in this emerging interdisciplinary area.

This study addresses three primary research questions: (1) How do objective acoustic improvements in treated classrooms translate into subjective perceptual differences for students? (2) What is the relationship between acoustic environmental conditions and students’ cognitive load and allostatic load responses in university learning spaces? (3) Can the 4E Cognition framework provide a theoretical foundation for understanding acoustic environments as potential cognitive extensions in educational settings?

This paper is structured as follows. Section 2 presents the theoretical framework of 4E Cognition, exploring how the four dimensions—embodied, embedded, enactive, and extended cognition—inform our understanding of acoustic environments as cognitive extensions. Section 3 describes the materials and methods, including the acoustic characterization protocol and subjective assessment methodology applied to two twin university classrooms. Section 4 presents the results, beginning with objective acoustic measurements that establish the environmental context, followed by analysis of acoustic–cognitive performance relationships and comprehensive statistical analysis of the collected data. Finally, Section 5 discusses the implications of the findings for cognitive architecture theory and practical acoustic design, concluding with recommendations for future research directions in the emerging field of cognitively informed environmental design.

2. Theoretical Framework: 4E Cognition and Acoustic Design

The 4E cognition paradigm has completely changed how we understand the mind. Instead of seeing it as something that only happens in the brain, we now recognize it as something that involves our whole body, our environment, and our interactions with others [27]. This approach recognizes cognition as embodied, embedded, enactive, and extended, fundamentally reshaping how we think about the relationship between mind, body, and environment [6]. This framework emerged from converging insights in phenomenology, dynamic systems theory, and neuroscience, challenging computational models that locate cognition exclusively in neural processes. When it comes to acoustic experience, this theoretical approach reveals how sound environments are not just external stimuli to process but become integral parts of cognitive processes themselves. The acoustic environment continuously shapes our ability to pay attention, understand things, and interact socially, becoming a constitutive element of cognitive experience rather than mere sensory input.

2.1. Embodied Cognition

The concept of embodied cognition represents a fundamental shift in understanding cognitive processes, challenging the Cartesian tradition that separates mind and body. This theoretical perspective, developed through Maurice Merleau-Ponty’s contributions in phenomenology of perception and later formalized by researchers like Lakoff and Johnson [28] and Varela, Thompson, and Rosch [29], argues that cognitive processes are intrinsically rooted in bodily experience and sensorimotor interactions with the environment. Embodied cognition proposes that thinking, perception, and action are not separate processes but integrated aspects of a single dynamic body–mind–environment system. This approach emphasizes how bodily structures and sensorimotor capabilities directly shape cognitive processes and ways of understanding the world. In the acoustic domain, embodied cognition reveals particularly significant dimensions of sound experience. The human auditory system is not simply a passive receiver of sound waves, but an integrated system that involves the entire body in perceiving and processing sound. Sound vibrations are perceived not only through the traditional auditory apparatus, but also through bone conduction, bodily resonance, and tactile sensations, creating a multisensory experience that involves proprioception, balance, and spatial perception. Central to this understanding is the concept of body schema developed by Maurice Merleau-Ponty and later developed by Shaun Gallagher [30]: the implicit and proprioceptive sense of bodily configuration that enables fluid action in space. In the acoustic context, body schema extends to include perception of sound space, localization of acoustic sources, and understanding of spatial relationships through auditory information. Research on noise effects confirms this theoretical perspective, showing that exposure to inadequate acoustic environments activates physiological stress responses that involve the entire organism [31]. These effects represent direct manifestations of the embodied nature of acoustic experience, where environmental sound conditions translate into bodily responses that influence cognitive abilities and learning performance.

2.2. Embedded Cognition

The concept of embedded cognition argues that cognitive processes are intrinsically dependent on the environmental, social, and cultural context in which they manifest. This theoretical approach, developed through Lucy Suchman’s [32]. Contributions in studies on situated action and later elaborated by Andy Clark [5], proposes that the environment is not simply a source of input for the cognitive system, but constitutes an active and structuring part of cognitive processes themselves. Central to this understanding is the concept of affordances developed by James J. Gibson [33]: the environment provides opportunities and constraints for action that directly shape the ways we think, perceive, and act. In the acoustic domain, the situated nature of cognition manifests particularly clearly. The acoustics of learning environments provides a paradigmatic example of this embeddedness: the same cognitive task (for example, listening to a lecture) requires different cognitive strategies and resources depending on the specific acoustic context. In an acoustically optimized environment, students can engage in efficient listening, allowing cognitive resources to focus on content understanding and critical thinking. In acoustically challenging contexts, the same students must deploy additional cognitive resources for basic auditory processing, fundamentally altering the nature of the learning experience and the cognitive strategies employed. Cognitive load theory [34] provides a framework for understanding these situated processes. Background noise, excessive reverberation times, and poor speech intelligibility impose what the theory defines as extraneous cognitive load, which diverts mental resources from learning objectives. This extraneous load represents a direct manifestation of the embedded nature of cognition, where environmental conditions become integral parts of the cognitive process itself, determining not only performance but also the very ways through which the learning process is realized.

2.3. Enactive Cognition and Sound Interaction

The concept of enactive cognition represents perhaps the most radical element of the 4E paradigm, proposing that cognition is not a process of representing the external world, but emerges through dynamic interaction between organism and environment. This theoretical approach was developed mainly by Francisco Varela through the concept of autopoiesis and the idea of structural coupling, later elaborated by Evan Thompson [35] and Alva Noe [36] in studies on perception. According to the enactive perspective, perception is not passive reception of information but “enaction”—literally “putting into action”—through action and active exploration of the environment. As proposed by O’Regan and Noe [37], we perceive through action, developing sensorimotor skills that allow us to explore and interact with the surrounding world. In the acoustic domain, the enactive dimension reveals how sound experience is fundamentally interactive and co-constructed. Students do not passively receive acoustic information but actively engage with and shape their acoustic environment through adaptive behaviors: moving closer to sound sources, modifying their posture to optimize listening, using gestures to improve communication, or developing coping strategies for difficult acoustic conditions. The enactive perspective also highlights the importance of acoustic environments that support natural and bidirectional communicative behaviors. Optimal classroom acoustics should facilitate not only unidirectional teacher–student communication but also multidirectional student–student interaction, supporting collaborative learning processes central to contemporary educational approaches. In the phenomenological tradition, sound is not simply a perceptual object but a relational medium through which we come into contact with the world and with others. Maurice Merleau-Ponty [38] had already intuited how perception is always temporally extended and situationally structured—characteristics that apply paradigmatically to acoustic experience, since sound is intrinsically temporal and relational.

2.4. Extended Cognition

The extended dimension recognizes that cognitive processes can incorporate environmental structures as functional components of the cognitive system. In acoustic terms, this means that well-designed acoustic environments can function as cognitive extensions that enhance information processing capacity. The extended mind theory by Clark and Chalmers [39] proposes that human cognitive processes are not confined within the limits of the brain but extend into the surrounding environment through tools, technologies, and environmental structures. In the educational context, this extension includes not only technological tools but also the physical environment itself, including its acoustic properties. When applied to classroom acoustics, the extended mind perspective suggests that the acoustic environment becomes part of the cognitive system. A well-designed acoustic environment can function as a cognitive prosthesis, reducing the mental effort required for speech processing and allowing the allocation of cognitive resources to higher-order learning tasks. Conversely, poor acoustic conditions force the cognitive system to allocate substantial resources to basic auditory processing, creating what we might define as “cognitive friction” that impedes learning. For example, appropriate reverberation times can improve speech clarity and comprehension, effectively extending the cognitive system’s capacity for auditory processing. Conversely, excessive background noise or poor speech intelligibility forces the cognitive system to work with reduced capacity, highlighting the critical role of acoustic design in cognitive architecture.

3. Materials and Methods

The methodology adopted in this study follows a mixed-methods approach that integrates objective measurements and subjective evaluations. This multimethodological integration aligns with the theoretical framework of 4E Cognition, recognizing the embodied and situated nature of acoustic experience in learning environments and allowing for comprehensive understanding of the complex interactions between the built environment and students’ cognitive processes.

The bipartite approach comprises:

• Objective acoustic characterization: Measurements of relevant acoustic parameters including sound levels, reverberation times, and speech intelligibility indices.
• Subjective perceptual evaluation: Comprehensive questionnaires assessing perceived acoustic comfort, cognitive load, adaptation strategies, and allostatic load indicators.

This study focuses on two twin classrooms located at the Engineering Faculty of “G. D’Annunzio” University in Pescara, Italy. These classrooms, designated as Classroom A and Classroom B, presenting identical architectural and dimensional characteristics (both approximately 80 m² with a capacity of 60 students), are exposed to the same external environmental conditions, and are used for the same types of educational activities.

Classroom A (see Figure 1) has recently undergone comprehensive acoustic treatment, including installation of sound-absorbing panels on the ceiling, acoustic coverings on rear and side walls, and optimization of reflective surfaces in the frontal zone. The room has an area of 106.7 m², volume of 384 m³, and maximum occupancy of 61 students.

Classroom B (see Figure 2) has been maintained in its original conditions, characterized by reflective surfaces without any specific acoustic treatment. This classroom has an area of 92.5 m², volume of 333 m³, and maximum occupancy of 65 students. This experimental setting offers the unique opportunity to directly compare the impact of acoustic conditions on students in two otherwise identical environments, isolating the acoustic variable as a determining factor.

To provide comprehensive spatial documentation of the acoustic environments, cross-sectional views are presented in Figure 3 and Figure 4. These sections illustrate the vertical geometry of both classrooms, highlighting the 3.6 m ceiling height and the specific positioning of acoustic treatments in the treated classroom relative to typical student and instructor positions.

This experimental setting offers the unique opportunity to directly compare the impact of acoustic conditions on students in two otherwise identical environments, isolating acoustic variables as the sole architectural difference and enabling direct assessment of how specific built environment modifications influence cognitive processes.

3.1. Acoustic Characterization

The acoustic characterization of the two classrooms was meticulously conducted following established international standards. The measurement protocol adhered to UNI 11532-2 [40], which specifies measurement methods and evaluation techniques for acoustic characteristics in school environments, providing a comprehensive framework for assessing classroom acoustics to ensure optimal learning conditions.

All measurements were conducted under controlled environmental conditions (temperature: 20 ± 2 °C, relative humidity: 45–55%) with mechanical ventilation systems operating at normal settings. Measurements were performed in unoccupied rooms during periods of minimal external noise to establish baseline acoustic characteristics.

Measurement positions were strategically selected to provide comprehensive coverage of the classroom environment, with particular attention to typical student seating locations throughout the classroom (Figure 1 and Figure 2). Microphone positions were established at 1.2 m height, corresponding to seated student ear level, with six measurement points distributed throughout each classroom seating area. Sound source positions were placed at 1.5 m height, representing typical instructor locations.

Three main acoustic parameters were evaluated using different standardized methodologies:

Background noise assessment: The equivalent sound pressure level of technological systems was measured according to UNI EN ISO 16032 [41] under phase-stationary conditions, highlighting background noise levels when mechanical systems were operational.

Reverberation time (T30): Measurements followed ISO 3382-2 [42] requirements in strict accordance with specifications for ordinary rooms, employing at least two source positions and three microphone positions.

Speech transmission index (STI): STI values were derived using the indirect methodology specified in EN 60268-16 [43], based on impulse response and background noise measurements. Following UNI 11532 requirements, measurements employed at least one source position and four microphone positions.

All acoustic measurements were performed using professional-grade equipment calibrated according to manufacturer specifications:

• SAMURAI (VERSIONE 2.6.0 2009-1013 Versione driver SINUS 5.4.0334) Room Acoustic commercial software (licensed by SPECTRA S.p.A, Vimercate, Italy), configured for educational environment analysis;
• Larson Davis precision sound level meter (Class 1) with frequency analysis capabilities;
• Equipment calibrated before each measurement session using a Class 1 acoustic calibrator at 94 dB, 1 kHz reference signal;
• Dodecahedral omnidirectional sound source positioned at two locations per classroom, fed with exponential sweep signals covering the frequency range 125 Hz to 8 kHz;
• Directional sound source (NTi-Talkbox) consisting of a 100 mm diameter speaker powered by Maximum Length Sequence (MLS) signals.

Each measurement was repeated three times with 30-s intervals, following a 5-min equipment stabilization period. Reverberation time calculations employed the Schroeder backward integration method from impulse response measurements, with frequency analysis conducted in octave bands from 125 Hz to 4000 Hz, as specified by UNI 11532-2.

3.2. Subjective Assessment Protocol

The subjective investigation represents a fundamental element of the research protocol and has been structured according to validated psychometric principles, with particular attention to discrimination between immediate and cumulative acoustic effects. This approach allows for distinguishing between transient disturbances and long-term adaptive modifications in students’ attentional processes.

The study recruited 66 university students from the Faculty of “G. D’Annunzio” University, with participants distributed across the two experimental conditions: 28 students in the acoustically treated classroom and 38 in the control environment. Measurements were conducted during standard academic hours (9:00–17:00), with participants having varied exposure durations reflecting realistic usage patterns (0–10 min: 68.4%, 11–30 min: 23.7%, >30 min: 7.9%). The sample demographics are presented in

Table 1. Participant demographic characteristics by classroom condition. The exposure time refers to the time spent in classroom before survey completion. Distribution estimated based on typical classroom attendance patterns and survey administration timing.

Characteristic	Acoustically Treated (n = 28)	Control (n = 38)
Gender
Female, n (%)	25 (89.3)	25 (65.8)
Male, n (%)	2 (7.1)	13 (34.2)
Missing, n (%)	1 (3.6)	0 (0.0)
Age Group
21–26 years, n (%)	14 (50.0)	27 (71.1)
Other ages, n (%)	14 (50.0)	11 (28.9)
Academic Role
Students, n (%)	27 (96.4)	38 (100.0)
Other roles, n (%)	1 (3.6)	0 (0.0)
Exposure Duration
0–10 min, n (%)	18 (64.3)	26 (68.4)
11–30 min, n (%)	7 (25.0)	9 (23.7)
>30 min, n (%)	3 (10.7)	3 (7.9)

and a focus on the gender is presented in Figure 5.

Statistical analysis revealed a significant difference in gender distribution between the two classroom conditions (p = 0.009), with the acoustically treated classroom having a higher proportion of female participants (89.3% vs. 65.8%). Age distribution showed some variation between groups, with the control classroom having a higher proportion of participants in the 21–26 age range (71.1% vs. 50.0%). These demographic differences were considered as potential covariates in subsequent analyses to ensure the validity of acoustic environment comparisons.

Participants completed the assessment during regular classroom activities to ensure ecological validity of the acoustic experience. The survey was administered via digital platform to ensure standardized data collection and minimize potential experimenter bias. Prior to participation, all students provided informed consent, and the study protocol was approved by the institutional ethics committee.

The assessment was designed to capture the multifactorial complexity of acoustic experience, analyzing four key dimensions that map the entire spectrum of interactions between environmental acoustics and cognitive-behavioral responses:

• Evaluate students’ perception regarding acoustic conditions in both classrooms;
• Identify correlations between acoustic characteristics and cognitive load;
• Quantify the impact of acoustic treatment on well-being and learning experience;
• Collect data on subjective allostatic load associated with prolonged exposure to current classroom acoustic conditions.

Table 2. Questionnaire structure: evaluation dimensions and scales used in the subjective assessment.

Section	Evaluation Type	Scale
Acoustic Environment Perception	General acoustic quality evaluation	Likert 1-7
	Teacher speech intelligibility perception	Likert 1-7
	Understanding of questions from classmates	Likert 1-7
	Echo and reverberation perception	Likert 1-7
	Identification of noise sources and disturbances	Binary/Open
	Spatial localization within classroom during lesson	Classroom map
Learning Process Impact	Concentration level maintained during lesson	Likert 1-7
	Frequency of distractions due to acoustic problems	Frequency scale
	Effort required to follow the lesson	Scaled effort
	Mental fatigue at lesson end	Likert 1-7
	Perception of information comprehension during lesson	% scale
	Specific difficulties encountered	Open questions
Allostatic Load Assessment	Perceived stress level during lesson	Likert 1-7
	Physical symptoms manifested	Tension scale
	Adaptation strategies adopted	Open questions
	Persistence of effects after lesson	Duration/Persistence

presents the questionnaire structure.

4. Results and Discussion

4.1. Acoustic Measurements

Acoustic characterization was conducted in accordance with the UNI 11532-2 standard for classroom acoustics. Measurements included:

• Reverberation time (T30) across octave bands;
• Background noise levels (LAeq);
• Speech Transmission Index (STI).

Table 3. Acoustic measurement results according to UNI 11532-2 standard (mean value from 125 Hz to 4000 Hz).

Parameter	Classroom A	Classroom B	Standard Requirement	Units
T30 (500–1000 Hz)	1.2	1.8	0.6–1.2	s
Background Noise	35	42	<35	dB(A)
STI	0.65	0.52	>0.60	-

shows the results of the objective acoustics characterization. Classroom A (treated) presents significantly better values, particularly for background noise levels (35 vs. 42 dB(A)). The Speech Transmission Index (STI) shows improvement in the treated classroom (0.65 vs. 0.52).

The acoustic analysis covered octave bands from 125 Hz to 4000 Hz, as specified by UNI 11532-2 for speech frequency assessment. Background noise measurements represent realistic operational conditions with both classrooms experiencing similar outdoor campus noise exposure through identical window configurations. It should be noted that this study examined natural architectural acoustic conditions without electroacoustic amplification systems, focusing on passive acoustic treatments rather than active sound reinforcement.

4.2. Acoustic–Cognitive Performance Relationships

The analysis of acoustic–cognitive relationships revealed modest associations between environmental acoustic conditions and cognitive performance measures, providing initial empirical insights for the 4E Cognition framework in educational settings. Figure 6 presents the comprehensive comparison of acoustic and cognitive parameters between the acoustically treated and control classrooms.

The acoustically treated classroom demonstrated measurable improvements in specific acoustic parameters. Acoustic quality ratings showed improvement in the treated classroom (M = 3.00, SD = 1.02) compared to the control condition (M = 2.82, SD = 1.01), representing a small effect size (Cohen’s d = 0.18). Speech intelligibility scores similarly favored the treated environment, with students reporting better comprehension (M = 4.96, SD = 1.00) versus control (M = 4.66, SD = 0.97), Cohen’s d = 0.31, indicating a small-to-moderate effect. However, these individual improvements did not translate into substantial differences in composite measures. The Acoustic Comfort Index showed comparable performance between conditions, with the treated classroom (M = 4.26, SD = 0.53) and control environment (M = 4.27, SD = 0.57) demonstrating minimal difference (Cohen’s d = −0.02). This suggests that while specific acoustic parameters improved with treatment, other factors may have influenced the overall perceived acoustic comfort. Cognitive performance measures revealed minimal differences between conditions. The Cognitive Load Index was nearly identical between the acoustically treated classroom (M = 4.18, SD = 0.95) and the control environment (M = 4.15, SD = 1.22), Cohen’s d = 0.03, indicating no meaningful difference in reported mental effort required for auditory processing tasks. The Allostatic Load Index demonstrated no meaningful differences between conditions, with students in the acoustically treated classroom (M = 2.83, SD = 0.61) and control group (M = 2.82, SD = 0.73) showing nearly identical cumulative physiological stress levels (Cohen’s d = 0.02). This finding indicates that the acoustic improvements achieved were insufficient to produce detectable changes in physiological stress responses within this cross-sectional study design. The results suggest that more intensive acoustic interventions or longer exposure periods may be necessary to observe meaningful effects on allostatic load, or that individual differences in acoustic sensitivity may require more nuanced analytical approaches.

These findings must be interpreted within the specific context of modern university engineering classrooms (106.7 m² and 92.5 m², 3.6 m ceiling height) during standard academic hours with normal HVAC operation. The modest effect sizes observed may reflect the complexity of acoustic–cognitive interactions in realistic educational environments, where multiple environmental factors interact simultaneously.

4.3. Statistical Analysis

Statistical analyses were conducted using R software (version 4.3.0) with appropriate parametric and non-parametric tests selected based on data distribution characteristics. Normality was assessed using Shapiro–Wilk tests, and homogeneity of variance was evaluated using Levene’s test. For normally distributed data with equal variances, independent samples t-tests were employed; otherwise, Welch’s t-test or Mann–Whitney U tests were utilized as appropriate.

Effect sizes were calculated using Cohen’s d for independent samples, computed as:

$$d={\displaystyle \frac{M_1-M_2}{S{D}_{pooled}}}$$

(1)

where $S{D}_{pooled}=\sqrt{{\displaystyle \frac{(n_1-1)S{D}_1^2+(n_2-1)S{D}_2^2}{n_1+n_2-2}}}$ represents the pooled standard deviation [44]. Effect size interpretations followed Cohen’s conventional criteria: small effect (d = 0.2), medium effect (d = 0.5), and large effect (d = 0.8) [44]. Additional guidance for effect size interpretation was drawn from contemporary methodological literature [45].

The final analysis included 66 valid responses, with 28 participants from the acoustically treated classroom and 38 from the control condition. Missing data analysis revealed no systematic patterns of missingness, and cases with excessive missing values in key variables were excluded from composite index calculations.

Physiological stress manifestations revealed an unexpected finding: 100% of participants in both conditions reported some form of physical symptoms during or after classroom exposure. This universal symptom prevalence indicates that both acoustic environments impose measurable physiological demands, despite the acoustic treatment implemented in one classroom. The similarity in symptom prevalence suggests that the current level of acoustic intervention may be insufficient to eliminate stress responses, or that other environmental factors beyond acoustics contribute to physiological strain in both settings.

The distribution of allostatic load scores across conditions is presented in Figure 7, revealing nearly identical patterns of cumulative stress response between the acoustically treated and control environments (M = 2.83 vs. 2.82, Cohen’s d = 0.02). This finding suggests that both classroom conditions operate within an equivalent range of physiological demand, with the acoustic treatment producing no detectable reduction in cumulative stress levels.

The modest effect sizes observed in this study (ranging from d = 0.02 to d = 0.31) reflect both the complex nature of acoustic–cognitive interactions in real educational environments and the challenges of detecting acoustic intervention effects in naturalistic settings. While the acoustic treatment produced measurable improvements in specific parameters (speech intelligibility, acoustic quality ratings), these changes did not translate into substantial differences in cognitive load or physiological stress measures. This pattern suggests that either more intensive acoustic interventions or different measurement approaches may be necessary to demonstrate the cognitive–architectural principles proposed by the 4E framework, or that the theoretical relationships may be more context-dependent than initially hypothesized.

The significant demographic differences between groups represent important confounding variables that may have influenced results. The gender distribution difference (89.3% female in treated vs. 65.8% in control classroom, p = 0.009) is particularly notable, as research indicates gender differences in acoustic sensitivity and stress responses. Age distribution variations (50.0% vs. 71.1% in 21–26 age range) may also affect acoustic perception and cognitive responses. Additionally, unmeasured environmental variables such as lighting conditions, air quality, classroom usage patterns, and time-of-day variations could have influenced results. These factors may have been as influential as the acoustic interventions themselves, highlighting the need for more rigorous experimental control in future studies.

4.4. Interpretation of Findings

The findings of this study require interpretation within the broader context of classroom acoustics research and cognitive–environmental interactions.

Speech intelligibility and cognitive load relationships: Our STI improvement from 0.52 to 0.65 aligns with established research by Bradley and Sato [46], who reported similar ranges in educational environments. However, while our treated classroom approaches the recommended threshold of >0.60 for good intelligibility, the minimal differences in cognitive load measures contrast with previous studies that found stronger correlations between acoustic improvements and cognitive outcomes. This discrepancy may reflect differences between university and elementary school populations, as most previous research has focused on younger students who may be more sensitive to acoustic disruptions.

Background noise and physiological responses: The 7 dB reduction in background noise (42 to 35 dB(A)) represents a meaningful improvement according to classroom acoustic standards. However, the universal prevalence of physical symptoms (100% in both conditions) suggests that acoustic improvements alone may be insufficient to eliminate environmental stress responses. This finding contrasts with studies by Klatte et al. [47], who observed clear physiological benefits from noise reduction, indicating that multiple environmental factors may contribute to stress in university settings.

Effect size interpretation: Our modest effect sizes (Cohen’s d = 0.02–0.31) are smaller than those typically reported in elementary school acoustic intervention studies. This may reflect the complexity of cognitive–acoustic interactions in higher education environments, where students have developed greater adaptation strategies, or the limitations of cross-sectional measurement approaches in detecting cumulative effects that require extended exposure periods.

Theoretical framework implications: The 4E Cognition paradigm represents a novel approach to understanding acoustic–cognitive relationships, moving beyond simple cause-and-effect models. While our empirical findings show limited support for dramatic cognitive extensions through acoustic design, the theoretical framework provides a foundation for future research that may require different methodological approaches or more intensive interventions to observe meaningful effects.

5. Conclusions

This study represents an initial step toward understanding the complex relationships between acoustic environment and cognitive processes in educational settings. By grounding the research in the 4E Cognition paradigm, we move beyond simple cause-and-effect relationships to explore the theoretical framework for dynamic interactions between environment and cognition.

The integration of objective acoustic measurements with subjective assessments and physiological monitoring provides a comprehensive methodological approach for investigating how acoustic design may impact student well-being and learning capacity. This multidimensional approach aligns with the holistic perspective of 4E Cognition, recognizing that optimal learning environments should theoretically support the embodied, embedded, enactive, and extended dimensions of cognitive processes.

The theoretical analysis of these four dimensions offers a systemic framework for understanding acoustic experience as a potentially distributed cognitive phenomenon. The embodied dimension highlights how sound experience involves the entire organism, not just the auditory apparatus, with our findings confirming that acoustic conditions in both treated and control environments produced universal physiological responses. The embedded dimension demonstrates how cognitive processes may require different strategies and resources depending on the acoustic context, though our results showed limited empirical evidence for this situated nature of cognition. The enactive perspective reveals the theoretical importance of interactive sound experience, where students and environment could co-constitute each other through adaptive behaviors and communicative strategies. The extended dimension proposes the acoustic environment as a possible functional extension of the cognitive system, though our data provided minimal support for this relationship in the current study context.

While our empirical findings showed modest effect sizes (d = 0.02 to 0.31) and limited differences between acoustic conditions, the theoretical synthesis suggests potential for a paradigmatic shift in acoustic design. Rather than optimizing isolated physical parameters, future research could explore the concept of “acoustic cognitive prostheses”—environments that might systematically amplify natural cognitive abilities under different conditions or with more intensive interventions.

The concept of creating acoustic ecosystems that function as cognitive scaffolding remains a promising theoretical direction, representing environmental structures that could support and amplify cognitive processes rather than simply hosting them. This integrated approach offers an innovative conceptual framework for designing educational environments, where acoustics could potentially become an active tool for cognitive enhancement rather than mere background conditions.

The limited translation of acoustic improvements into cognitive and physiological differences reflects several important considerations. First, while the acoustic treatment produced measurable improvements in STI (0.65 vs. 0.52) and background noise levels (35 vs. 42 dB(A)), the intervention intensity may have been insufficient to cross perceptual thresholds necessary for detectable cognitive impact. Second, the cross-sectional study design may not capture adaptation effects that require extended exposure periods to manifest. Third, the complexity of cognitive load and stress responses involves numerous environmental and personal factors beyond acoustics alone, as evidenced by the universal reporting of physical symptoms (100% in both conditions), suggesting both environments imposed physiological demands that acoustic improvements alone could not eliminate.

Future research should examine longitudinal adaptation to acoustic environments with extended exposure periods, investigate individual differences in acoustic sensitivity and stress response, develop more sensitive measurement approaches for detecting cognitive–acoustic interactions, explore more intensive acoustic interventions, and expand this theoretical framework to other types of learning environments with controlled experimental conditions.

The ultimate goal remains to establish whether acoustic design can function as a fundamental component of cognitive architecture, creating learning environments that actively support human cognitive potential. However, achieving this goal may require more substantial environmental modifications, longer exposure periods, or different populations than those examined in the present study. This research contributes primarily to the theoretical development of cognitive architecture approaches to environmental design, providing a foundation for future empirical investigations of the 4E Cognition framework in educational settings.