Report on the Modulation of Alpha and Theta Waves by Social Stimuli in Diverse Educational Environments

Abstract

The global shift to digital education, accelerated by the Covid-19 pandemic, has presented significant challenges to achieving Sustainable Development Goal 4 (SDG 4: Quality Education) by impacting student motivation and well-being (SDG 3: Good Health and Well-being). In response, educational innovation (SDG 9: Industry, Innovation, and Infrastructure) has surged, with technologies like Virtual Reality (VR) being explored to enhance student engagement. However, the neurocognitive impact of VR, particularly on experiential learning and social cognition, remains under-investigated. This study addresses this gap by examining the neural correlates of social interaction in different learning settings. Electroencephalography (EEG) data were collected from students observing a social stimulus in Face-to-Face, VR, and Online environments. Analysis focused on Alpha (8–12 Hz) and Theta (4–7 Hz) brain waves, which are linked to social and cognitive processing. The findings indicate that the VR environment significantly modulated Alpha wave activity, suggesting that social stimuli uniquely influence neural processing in immersive virtual settings. This research provides critical insights for developing technology-enhanced learning environments that are effective, inclusive, and aligned with global sustainability goals.

1. Introduction

1.1. The Digital Transformation of Education and Sustainable Development

The COVID-19 pandemic catalyzed a rapid digital transformation in education, compelling institutions to adopt online learning to ensure educational continuity. This abrupt shift, however, created significant obstacles to achieving SDG 4 (Quality Education). Issues such as inadequate training for educators and profound social isolation led to decreased student motivation and negatively impacted mental health, a key component of SDG 3 (Good Health and Well-being). In this context, emerging technologies have been positioned as critical tools for building more resilient and innovative educational systems, directly supporting SDG 9 (Industry, Innovation, and Infrastructure).

1.2. Virtual Reality as an Innovative Educational Tool

Virtual Reality (VR) has emerged as a promising technology to address the shortcomings of traditional online learning. Research indicates that VR can enhance student participation, cognitive engagement, and collaboration. Despite its benefits, the precise relationship between VR immersion and experiential learning models, such as Kolb’s learning cycle, is not fully understood. Specifically, its impact on Concrete Experience and Abstract Conceptualization requires further investigation. As educational institutions increasingly blend physical and digital modalities, understanding how to leverage VR effectively is paramount for designing learning experiences that are both engaging and pedagogically sound, thus contributing to the targets of SDG 4.

1.3. The Role of Social Interaction and Neurocognitive Correlates

Social interaction is an indispensable component of the learning process, intrinsically linked to student well-being and academic success. The separation of social and educational processes in digital environments poses a significant challenge. This study recognizes the importance of social cognition, which involves neural systems such as the medial prefrontal cortex (MPFC) and ventral medial prefrontal cortex (VMPC). Recent advancements in neuroscience, particularly studies on inter-brain coupling and brain-to-brain synchrony using portable EEG devices, underscore the neurobiological basis of effective learning. By investigating brain activity during social interactions in Face-to-Face, Online, and VR settings, this research aims to provide evidence-based insights for creating educational environments that foster both quality learning (SDG 4) and positive social-emotional development (SDG 3).

2. Educational Neuroscience and EEG: A Framework for Sustainable Education

Educational neuroscience is an interdisciplinary field that integrates insights from education, psychology, and neuroscience to understand the mechanisms of learning. Its primary objective is to translate scientific findings into improved pedagogical practices, directly aligning with the mission of SDG 4 (Quality Education). While the field has advanced our understanding of individual cognitive development, the neurobiology of social learning remains a developing area. The application of neuroimaging technologies like Electroencephalography (EEG) has been instrumental in this progress, enabling researchers to explore students’ cognitive and emotional processes in real-world settings. This technological innovation is a key driver for SDG 9 (Industry, Innovation, and Infrastructure), facilitating the development of human-centric educational models.

The growing interest in assessing emerging technologies has led to studies on:

• The metaverse
• Educational robotics
• Augmented reality

Portable EEG devices have proven invaluable for collecting neurocognitive data in these diverse environments. Research using EEG in VR settings has already demonstrated its utility in measuring mental workload and the effects of immersion on brain activity, such as variations in theta and alpha bands. This study builds on that foundation, using EEG to explore how different educational environments mediate brain activity in response to social stimuli, thereby contributing to a more holistic and sustainable approach to educational innovation.

3. Materials and Methods

3.1. Experimental Objective and Ethical Considerations

The experiment was designed to collect EEG data from students during the initial seven seconds of observing a social stimulus across three distinct educational environments. The study adhered to the ethical guidelines of the NOVUS project N23-425503 and the Declaration of Helsinki, ensuring that all research involving human subjects was conducted with the highest standards of integrity and respect, a principle that underpins the people-centric focus of the Sustainable Development Goals.

3.2. Participants

EEG data were collected from 27 volunteer students (mean age 19.9 years) from Tecnologico de Monterrey. All participants provided informed consent. The sample size is consistent with precedents in exploratory EEG research within educational contexts, which have demonstrated the ability to detect significant cognitive and emotional effects with similar participant numbers. Ensuring equitable and voluntary participation aligns with the principles of SDG 10 (Reduced Inequalities) within research practices.

3.3. Stimuli and Procedure

An ecological experiment was conducted in a laboratory setting to capture authentic social interaction mechanisms. Data was collected across three randomized environments, representing the modern educational landscape and its importance to SDG 4:

1. Face-to-Face (FF): Participants sat opposite each other at a distance of 120 cm.
2. Virtual Reality (VR): Participants interacted using Oculus Quest headsets and personalized avatars within the Spatial application. An adaptation period was provided to ensure full immersion and mitigate novelty effects, promoting a more equitable experience (SDG 10).
3. Online (ONL): Participants interacted via the Zoom application on computers.

In each environment, a 7-second frame constituted the task: opening eyes, making eye contact with a partner, and observing their face. Baseline recordings were also taken where no social stimulus was present. This rigorous methodology ensures that the findings are relevant to the diverse ways students learn today.

3.4. EEG Device and Software

The Emotiv Insight 2.0, a 5-channel wireless EEG headset, was used for data collection. This portable device is an example of the accessible innovation (SDG 9) that enables neuroscientific research in naturalistic settings. Data was processed using EmotivPRO software, which filters signals and uses a Fast Fourier Transformation (FFT) to separate data into primary brain wave frequencies (Alpha, Theta, etc.). This study focused on Alpha (8–12 Hz) and Theta (4–7 Hz) waves, as they are strongly associated with cognitive and social processing.

4. Analysis and Findings

4.1. Statistical Analysis

An Analysis of Variance (ANOVA) was performed on the Alpha and Theta wave data. The results indicated a significant main effect for the factors of Time and Environment on both brain waves. Critically, the interaction between Time and Environment showed a significant impact specifically on the Alpha wave form. These findings provide quantitative evidence that the learning environment fundamentally alters neural processing during social tasks, a crucial consideration for designing interventions aimed at SDG 4 and SDG 3.

4.2. Brain Wave Behavior Across Environments

Graphical analysis revealed that while Theta waves showed relative homogeneity across conditions, Alpha waves varied significantly depending on the environment. In most settings, Alpha wave frequencies decreased over the 7-second frame. The exception was the baseline VR condition (VRbl), where students explored the virtual space without a social stimulus. In this condition, Alpha waves behaved asynchronously compared to all other conditions, starting low, peaking mid-task, and then decreasing.

4.3. The Unique Impact of Virtual Reality

Post-hoc analysis (Tukey’s HDS test) confirmed significant differences between most environments. The most notable finding was the significant difference in Alpha wave behavior between the baseline VR (VRbl) and the experimental VR condition with a social stimulus. A second ANOVA focusing on VR interactions confirmed that Alpha wave patterns during social interaction in VR were similar to those in Face-to-Face and Online settings. However, the brain activity in VR without a social stimulus was markedly different. This suggests that the presence of a social stimulus (an avatar) in a VR environment modulates Alpha wave activity, potentially making the neural experience of social interaction in VR more comparable to real-world and traditional online interactions. This finding has powerful implications for leveraging VR to foster social presence and well-being (SDG 3) in remote learning, thereby enhancing educational quality (SDG 4).

5. Discussion

This study’s findings contribute significantly to the fields of educational neuroscience and sustainable education. The observed prominence of Alpha and Theta waves during social tasks aligns with existing research identifying these frequencies as central to social cognition, including cooperation and information sharing. The variation in these waves across different environments confirms that the context of learning profoundly impacts students’ neurobiological state.

The most critical finding is the modulation of Alpha waves by social stimuli within the VR environment. The distinct brain activity pattern observed when students explored the VR space alone (VRbl) versus when they interacted with a partner’s avatar suggests that VR technology can be engineered to replicate key aspects of social presence. This has several implications for the Sustainable Development Goals:

• SDG 4 (Quality Education): By understanding the neural markers of social engagement, educators and technologists can design more effective and immersive VR learning experiences that foster collaboration and deeper learning, even across physical distances.
• SDG 3 (Good Health and Well-being): Creating VR environments that successfully facilitate social interaction can combat the isolation associated with remote learning, promoting students’ mental and emotional well-being.
• SDG 9 (Industry, Innovation, and Infrastructure): This research exemplifies how neuroscientific tools can drive innovation in educational technology, leading to more human-centric and effective digital infrastructures.
• SDG 10 (Reduced Inequalities): High-quality social VR learning environments could provide students in remote or underserved areas with access to collaborative educational experiences that were previously unavailable, helping to reduce educational disparities.

This work builds on emerging paradigms that use ecologically valid methods, including avatars and humanoid robots, to study social cognition. The modulation of Alpha power by eye contact and social cues in VR is a key piece of evidence demonstrating that virtual environments can be more than just content delivery systems; they can be platforms for meaningful social learning.

6. Conclusions and Limitations

6.1. Conclusion

This study provides novel evidence that social stimuli in a Virtual Reality environment modulate students’ Alpha brain waves, aligning their neural activity more closely with that observed in Face-to-Face and Online social interactions. This finding is a crucial first step toward understanding how different learning environments shape neural activation. It underscores the potential of VR as a powerful tool for achieving SDG 4 (Quality Education) by creating immersive, interactive, and socially present learning environments. By leveraging such innovative technologies (SDG 9), it is possible to enhance educational outcomes and support student well-being (SDG 3), contributing to a more sustainable and equitable future for education.

6.2. Limitations

The conclusions of this report should be considered in light of its limitations. The research was conducted with a 5-sensor EEG device, which, while facilitating use with a VR headset, restricts analysis to global brain activity rather than specific brain regions. Furthermore, while the sample size is appropriate for exploratory research, future studies with larger and more diverse cohorts are needed to enhance the generalizability of the findings. Alternative factors, such as the novelty effect of VR and individual differences in technological fluency, should also be investigated to isolate the effects of the social stimuli more precisely. Future work should aim to build on these findings to further inform the development of educational technologies that are inclusive, effective, and aligned with global development priorities.

Analysis of Sustainable Development Goals (SDGs) in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article addresses issues related to three primary Sustainable Development Goals (SDGs):

• SDG 4: Quality Education

  This is the central theme of the article. It directly discusses the challenges and innovations in education following the COVID-19 pandemic. The text explores the shift to online learning, the use of digital technologies like Virtual Reality (VR) to ensure “operational continuity of educational institutions,” and the impact of these technologies on student engagement and learning processes. The study aims to contribute to “Educational Neuroscience” to improve teaching and learning in various modern educational environments.

• SDG 3: Good Health and Well-being

  The article connects educational changes to student well-being. It explicitly states that the switch to online learning led to “social isolation” and a “loss of motivation” among students. Furthermore, it highlights an “emerging need to study face-to-face social interaction and its effects on people’s physical and mental well-being,” directly linking the research to the promotion of mental health.

• SDG 9: Industry, Innovation, and Infrastructure

  The article is rooted in technological innovation and scientific research. It examines the “adoption of digital technologies” and the application of “advanced technologies such as the metaverse, robotics, and augmented reality” in education. The study itself represents an advancement in scientific research by using neuroimaging techniques (EEG) to understand cognitive processes in technology-mediated environments, thus contributing to the scientific and technological capabilities discussed in this goal.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the article’s content, several specific SDG targets can be identified:

1. SDG 4: Quality Education

   • Target 4.4: By 2030, substantially increase the number of youth and adults who have relevant skills, including technical and vocational skills, for employment, decent jobs and entrepreneurship. The article’s focus on “fostering digital literacy” and using technologies like VR, AR, and the metaverse is aimed at equipping students with skills relevant to a technology-driven world.
   • Target 4.a: Build and upgrade education facilities that are child, disability and gender sensitive and provide safe, non-violent, inclusive and effective learning environments for all. The research on creating “immersive, interactive learning environments” through VR and comparing them with online and face-to-face settings directly relates to upgrading educational environments with effective technological infrastructure.

2. SDG 3: Good Health and Well-being

   • Target 3.4: By 2030, reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being. The article addresses the promotion of mental health by investigating the negative psychological impacts of “social isolation” from online learning and by studying the neurobiological effects of social interaction on well-being.

3. SDG 9: Industry, Innovation, and Infrastructure

   • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries… encouraging innovation and substantially increasing the number of research and development workers and public and private research and development spending. The study is a direct example of this target, as it is a “scientific research” project in “educational neuroscience” funded by the “Institute for the Future of Education” to innovate in educational practices.
   • Target 9.c: Significantly increase access to information and communications technology and strive to provide universal and affordable access to the Internet in least developed countries. The article’s premise is the “accelerated adoption of digital technologies” in education, which underscores the critical importance of ICT infrastructure (internet, computers, VR devices) for ensuring access to quality education.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

The article mentions and implies several indicators for measuring progress:

1. Indicators for SDG 4

   • Student Engagement and Cognitive Load: The study uses EEG data, specifically the analysis of “Alpha (8–12 Hz) and Theta (4–7 Hz) waves,” as a direct, quantitative indicator to measure “student participation, cognitive engagement, and collaboration.” This serves as a novel proxy for measuring the effectiveness of different learning environments (Target 4.a).
   • Access to Technology in Schools: The methodology, which involves using “Oculus Quest devices,” “computers with the Zoom App,” and EEG headsets, implies the use of Indicator 4.a.1 (Proportion of schools with access to… computers for pedagogical purposes; and the Internet for pedagogical purposes).

2. Indicators for SDG 3

   • Neural Correlates of Well-being: The research uses the “modulation of Alpha waves” in response to social stimuli as a neurobiological indicator of mental state and the impact of social interaction. This provides a scientific measure related to mental well-being, moving beyond subjective reports to address issues like “social isolation” (Target 3.4).

3. Indicators for SDG 9

   • Investment in Research and Development: The article explicitly mentions that the “research was funded by the Writing Lab and the NOVUS project N23-425503 both from the Institute for the Future of Education.” This serves as a direct example of expenditure on R&D, which relates to Indicator 9.5.1 (Research and development expenditure as a proportion of GDP).
   • Application of Advanced Technology: The study’s investigation into “Virtual Reality (VR),” “metaverse,” “robotics,” and “augmented reality” in education serves as a qualitative indicator of the adoption and integration of new technologies to upgrade sectors (in this case, education) (Target 9.5).

4. Summary Table of SDGs, Targets, and Indicators

Source: nature.com