Systematic review: inclusivity and sustainability in educational spaces through technology

Abstract

Introduction:

This systematic review investigates the role of technology in advancing inclusivity and sustainability in educational spaces.

Methods:

A structured methodology was applied to analyze 20 studies published between 2015 and 2025, sourced from IEEE Xplore, ACM Digital Library, and ScienceDirect.

Results:

The findings reveal that technologies such as artificial intelligence (AI), the Internet of Things (IoT), virtual and augmented reality (VR/AR), adaptive platforms, and the Edu-Metaverse enhance inclusion by personalizing learning, overcoming physical and cognitive barriers, and improving access for disadvantaged communities. Sustainability is supported through smart infrastructure, neuroarchitecture principles, and alignment with Sustainable Development Goals (SDGs) 4, 10, and 17. However, limited integration between neuroarchitecture, sustainability, and inclusion was identified, along with a lack of long-term impact assessment.

Discussion:

The results highlight the potential of technology to transform educational spaces into more inclusive and sustainable environments. Nevertheless, challenges related to scalability, equitable access, and interdisciplinary integration remain. Future research should focus on developing holistic frameworks and culturally adaptive solutions to bridge these gaps.

Systematic review registration:

https://osf.io/f5rxq

1 Introduction

Education today faces the challenge of adapting to an increasingly dynamic environment, where inclusion and sustainability converge as central pillars in the design of quality educational spaces. In this context, educational institutions have to consider not only their pedagogical practices but also their infrastructure to ensure accessible, equitable, environmentally responsible, and sustainable environments over time (Zhai et al., 2023; Hassan, 2023; Bressane et al., 2024; Al-Dmour, 2024). This is consistent with the purpose of developing students' potential and with the Sustainable Development Goals (SDGs), which seek quality, equitable, and inclusive education and learning opportunities for all (Alam et al., 2023; Muhammad and Li, 2024). However, approximately 16% of the world's population lives with disabilities, a figure that highlights the relevance of implementing educational practices that promote inclusion and accessibility (Balderas et al., 2024). Therefore, it is necessary to analyze: How can we improve the aforementioned aspects to achieve quality, accessible, and sustainable education through technology?

In this regard, the relationship between inclusion and sustainability must be explored from a new perspective, recognizing that both principles can and should coexist in spaces that promote quality learning (Hassan, 2023). Educational inclusion involves designing environments that are adapted to students' diverse cognitive, physical, and social needs. This requires not only pedagogical changes but also adjustments to infrastructure and learning resources so that all students, regardless of ability, can fully participate in the educational process (Al-Dmour, 2024). Sustainability in education refers to the implementation of practices and infrastructures that reduce environmental impact (Hassan, 2023; Al-Dmour, 2024). This includes efficient resource use, the construction of ecological spaces, and the promotion of an institutionally responsible environmental culture. In this context, technology facilitates access to quality education by overcoming geographic and physical barriers through intelligent, personalized resources (Hassan, 2023; Al-Dmour, 2024).

One emerging technology in this field is neuroarchitecture, which studies how the physical environment affects mental and emotional processes. This discipline suggests that elements such as light, acoustics, materials, and spatial distribution influence wellbeing and academic performance (Jung et al., 2025). Neuroarchitecture emerges from the intersection between neuroscience, environmental psychology, and architectural design. Specifically, its epistemological foundation lies in understanding how spatial configurations influence neural activity and human behavior. Building on this foundation, research in cognitive neuroscience suggests that environmental stimuli such as natural lighting, spatial geometry, acoustics, and material textures can modulate brain responses associated with attention, emotional regulation, and cognitive performance (Sternberg and Matthew, 2006; Coburn et al., 2017) In turn, within educational environments, and integrated with emerging technologies such as smart sensors, environmental control systems, and digital platforms, these principles provide a scientific basis for designing spaces that support learning, well-being, and inclusive participation (Jung et al., 2025; Alsafery et al., 2023).

Alongside the physical elements of the environment, digital technologies have also proven to be a driver of sustainable development. As Hariyani et al. (2025) points out, these tools offer innovative solutions in sectors such as education, health, the environment, and social equity. Technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), data analytics, and cloud computing are being used to optimize resource use, personalize learning, and manage educational infrastructures efficiently and responsibly (Hariyani et al., 2025; Bressane et al., 2024). Similarly, Ángeles Verdejo et al. (2022) proposes that Smart Labs can serve as experimental environments for evaluating sustainability through measurable indicators, combining adaptive design with user-centered technologies. Additionally, Zhai et al. (2023) highlights that immersive environments, such as Edu-Metaverse, have the potential to reduce urban learning gaps in emotional and cognitive domains, particularly in rural communities or areas with limited access. These platforms promote a participatory and distributed educational model, supported by decentralized technologies, intelligent avatars, and immersive experiences that strengthen educational equity. In this area, it is essential to analyze how technologies can be integrated coherently and effectively into the design, management, and transformation of educational spaces to enhance their inclusivity and sustainability (Hassan, 2023; Al-Dmour, 2024). This Systematic Literature Review (SLR) aims to synthesize existing knowledge on this convergence, identifying significant experiences, best practices, and research gaps. To achieve this, a structured review methodology was applied based on the Kitchenham and Charters (2007) approach, with extraction criteria that consider technological, social, and environmental dimensions relevant to the analysis.

Although no previous systematic reviews were identified that specifically address this intersection of inclusion and sustainability in educational spaces through technology, studies do partially examine key components. Wambua and Ondiek (2022) examines the impact of the IoT on the education of students with disabilities, highlighting benefits, challenges, and gaps, and emphasizing the need for inclusive and accessible policies. Complementarily, Msambwa et al. (2024) systematizes the integration of ICT in secondary education, highlighting the role of institutional actors, implementation barriers, and sustainable strategies that could be extrapolated to broader contexts. In the field of emerging technologies, the review by Salas et al. (2022) examines the use of AI and other innovative technologies in inclusive education for minority students, addressing both the benefits and the socio-cultural, pedagogical, and technological challenges. On the other hand, Fernndez et al. (2021) analyzes digital competence among higher education faculty, identifying low technological preparedness and the urgent need to train educators in both pedagogical and digital aspects. This review aims to synthesize fragmented knowledge, identify meaningful experiences, best practices, and research gaps, and generate a comprehensive vision to guide future policies and developments in the field. Therefore, the following research question is: How has technology contributed to the development of inclusive and sustainable educational spaces?

2 Methodology

This SLR was conducted following the methodological guidelines proposed by Kitchenham and Charters (2007). These guidelines are widely adopted in evidence-based research to ensure rigor, transparency, and reproducibility. The methodology is structured into three main stages: planning (Subsection 2.1), execution (Subsection 2.2), and reporting (Section 3). The transition from planning to execution involves moving from defining the scope, formulating research questions, and establishing the protocol to implementing a systematic search across selected digital libraries. In the execution stage, primary studies are screened and selected based on the defined criteria, their quality is assessed, and relevant data are extracted in a structured manner. The transition to the reporting stage marks a shift from data extraction to synthesizing and analyzing the collected data. In the reporting stage, the results of the review are presented through quantitative and qualitative analyses; the main findings are discussed; research trends and gaps are identified; and limitations and potential directions for future research are outlined. All materials related to the SLR, including search strategies, screening decisions, and data extraction tables, are publicly available on the Open Science Framework (OSF) repository.

Within this framework, the Kitchenham methodology integrates PRISMA through the SEGRESS guidelines, which are built directly upon the PRISMA 2020 standard (Kitchenham et al., 2022). This evolution is methodologically coherent, as Kitchenham's original protocols for software engineering were derived from the medical guidelines of the Cochrane Collaboration–the same origin from which PRISMA emerged (Kitchenham et al., 2022; Seplveda and Cravero, 2015). However, since PRISMA 2020 primarily focuses on quantitative health reviews, it previously presented adoption barriers for software researchers (Kitchenham et al., 2022). To overcome these, Kitchenham and colleagues adopted the structural rigor of PRISMA 2020 and extended its item definitions to suit empirical methods specific to technology, incorporating specialized guidelines for reporting mapping studies and qualitative reviews (Seplveda and Cravero, 2015). Consequently, this methodology inherits the robustness and transparency of PRISMA while adjusting its terminology and scope to the particular demands of technological development.

2.1 Planning the review

To establish a robust foundation for the review protocol, the PICOC framework (Population, Intervention, Comparison, Outcome, and Context) (Loveren and Aartman, 2007) was used to systematically and precisely structure the key elements of the research questions, ensuring clarity, focus, and alignment with the objectives of this systematic literature review. The resulting PICOC elements and their definitions are summarized in Table 1.

Based on the PICOC framework previously defined, the central Research Question (RQ) this review seeks to address is How has technology contributed to the development of inclusive and sustainable educational spaces?. In addition, three specific Sub-RQ (SRQ) were derived to guide the systematic extraction and analysis of information from each selected study: SRQ1: What current technologies are being used to enhance inclusion in educational spaces? SRQ2: How can the sustainable and inclusive impacts of a smart physical space be measured? and SRQ3: What examples exist of technology implementation for inclusive and sustainable educational spaces?

2.1.1 Search strategy

The PICOC was also used to define the search string for this SLR. Five key conceptual categories were identified: sustainability, inclusion, technology, educational spaces, and architecture. For each category, alternative terms, synonyms, and equivalent expressions were systematically selected to capture variations in terminology across the literature, as summarized in Table 2. These terms were combined using boolean operators (AND, OR) to ensure both breadth and relevance in the retrieval of studies. The final search string was constructed by integrating these categories as follows: (“EDUCATIONAL BUILDING” OR “EDUCATIONAL INFRASTRUCTURE” OR “EDUCATIONAL SPACE” OR “MULTISENSORY ENVIRONMENTS”) AND (“SUSTAINABLE”) AND (“INCLUSIVE” OR “ACCESSIBILITY”) AND (“TECHNOLOGY” OR “NEUROARCHITECTURE”). In addition, this search string was slightly adapted by appending the terms “systematic literature review” or “review” to identify relevant review studies, particularly those addressing the background and related work discussed in the introduction.

To identify primary studies, automated searches were conducted across the digital libraries IEEE Xplore, ACM Digital Library, and ScienceDirect, strategically complemented by manual searches in Google Scholar, specialized journals, and conference proceedings in Table 3, to expand coverage and mitigate publication bias. As evidenced in the identification phase of Figure 1, this initial process yielded a total of 1,401 records from indexed databases and manual search registers. To efficiently manage this volume of information, the Litmaps tool was employed to explore the state of the art and visualize citation networks. This technological screening phase facilitated the exclusion of 1,327 records through automated and manual exclusion criteria, ensuring that only works with the highest scientific relevance and thematic alignment advanced to the subsequent evaluation stage.

Figure 1

To ensure methodological transparency and align with interdisciplinary reporting standards, the entire study selection process conducted under the Kitchenham framework has been mapped to the PRISMA 2020 flow diagram in Figure 1. In the screening phase, the 74 records resulting from the initial yields were subjected to an exhaustive evaluation through title and abstract reading. This filter led to the exclusion of 54 articles that did not align with the specific objectives of the review, a process that is explicitly illustrated in the central block of Figure 1. Subsequently, retrieval was sought for the remaining 20 reports; in this stage, 100% successful access to the documents was achieved, ensuring that no potential sources were omitted due to technical or institutional access limitations.

In the final eligibility phase, the 20 recovered reports underwent a rigorous full-text examination where a predefined inclusion and exclusion criteria matrix was applied to validate their methodological quality and thematic pertinence. As observed in the lower section of Figure 1, no additional reasons for discarding studies were identified after this critical evaluation, confirming the precision of the filters applied in previous stages. As a final result, a total of 20 primary studies strictly met all quality and methodological rigor requirements, constituting the definitive evidence base for this systematic review and ensuring a robust and reliable synthesis of results.

Based on the identification of key milestones in the literature and global policy frameworks, a temporal boundary for this review was set to 2015. Sustainability in education has evolved from a purely environmental concern to a comprehensive approach encompassing social and economic dimensions. While its origins can be traced to seminal documents such as the 1972 Stockholm Declaration and the 1987 Our Common Future report of the World Commission on Environment and Development, the year 2015 marked a decisive milestone with the adoption of the United Nations SDGs (Msambwa et al., 2024; Salas et al., 2022). In particular, SDG 4 aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all,” explicitly linking sustainability with the transformation of education systems and learning environments (Salas et al., 2022). From this point onward, a consolidated global agenda emerged, focused not only on improving educational infrastructure from an environmentally responsible perspective but also on promoting accessible, safe, and sustainable educational spaces, especially in contexts of inequality. Consequently, academic literature since 2015 has shown a significant increase in interdisciplinary research addressing the sustainability of educational spaces, integrating sustainable architecture, technological innovation, and social inclusion as key pillars of more equitable and resilient human development (Fernndez et al., 2021; United Nations, 1972).

Finally, guided by the PICOC framework, a set of inclusion and exclusion criteria was defined to ensure the rigor, relevance, and consistency of the selected studies. These criteria, summarized in Table 4, were applied during the screening of titles, abstracts, and full-text articles, following the execution of both automated and complementary manual database searches. This systematic filtering process aimed to exclude studies that fell outside the scope of this review.

2.1.2 Extraction criteria

To answer the research questions, extraction criteria were established, as presented in Table 5. The importance of defining these criteria lies in avoiding researcher bias, ensuring that their expectations do not influence the analysis of the studies. The following paragraphs briefly describe these criteria and their relevance to the research and extraction of information for each article studied.

EC1, thematic focus of the study, identifies the conceptual lenses through which the selected studies examine the use of technology in educational spaces, explicitly focusing on sustainability, inclusivity, and neuroarchitecture. Sustainability refers to design and technological strategies intended to reduce environmental impact, optimizing resource use, and promoting long-term environmental equilibrium in learning environments (Salas et al., 2022; Uchima-Marin et al., 2024). Inclusivity encompasses approaches that aim to guarantee accessibility, equity, and meaningful participation for different users, including individuals with varying physical, sensory, or cognitive needs (Toto et al., 2024; Wulandari et al., 2024). Neuroarchitecture addresses the relationship between the built environment and human cognitive, emotional, and behavioral responses, emphasizing how spatial conditions, often supported or enhanced by technology, influence learning processes and wellbeing (Wang et al., 2022; Lee et al., 2022). In this review, neuroarchitecture means the set of design features in a space that affect how people think and feel in technology-based learning environments. From a Human-Computer Interaction (HCI) perspective, this means examining how factors such as lighting, room layout, sensory input, and comfort interact with digital tools to shape user experience, engagement, and learning outcomes.

EC2 captures the specific technological approach implemented in the studies to support inclusive educational spaces. It includes approaches based on AI, Augmented Reality (AR), Virtual Reality (VR), Multisensory Environments, IoT, and other emerging technologies. AI is considered in relation to data-driven adaptation, personalization, and decision support within learning environments (Garg, 2021). Augmented and VR are examined as tools designed for enhancing perception, engagement, and accessibility through immersive or layered experiences (Bodhwani and Sharma, 2023; Vats and Joshi, 2023). Multisensory environments refer to technologies that stimulate multiple sensory channels to support broad learning needs, while IoT-based solutions focus on interconnected devices that enable environmental monitoring, automation, and responsiveness (Allhoff and Henschke, 2018; Khanna and Kaur, 2020).

EC3 describes the type of improvements enabled by the technological solutions identified in the studies, focusing on how these technologies contribute to more inclusive educational spaces. Adaptive interfaces dynamically adjust content, interactions, or presentation based on user needs or preferences, while personalized learning experiences tailor educational interactions to individual learners (Zouhaier et al., 2023). Process automation uses technology to automatically manage or optimize environmental, administrative, or operational processes within educational spaces, thereby reducing barriers and cognitive or physical load for users (Suazo-Galdamés and Chaple-Gil, 2025). Inclusive ergonomics and furniture design address improvements in physical comfort, usability, and accessibility, often supported by technological sensing or adaptive mechanisms (Brisson, 2024).

EC4 addresses the design of the spatial experience as an evaluative dimension for assessing the sustainable and inclusive impacts of smart physical educational spaces. It focuses on biophilic design principles, commonly used to assess well-being, comfort, and a sense of connection to nature, all of which are strongly associated with sustainability outcomes (Barbiero et al., 2021). Spatial configuration and circulation flows are evaluated to determine accessibility, ease of movement, and adaptability for diverse users. Lighting conditions and material choices are assessed in terms of visual comfort, sensory perception, and environmental performance (Chen et al., 2018).

EC5 criterion distinguishes the inclusivity assessment approaches of the studies reviewed, specifically related to the robustness of the instruments used to assess inclusivity in smart physical educational spaces, rather than the research paradigm employed. Formal assessment refers to the use of evaluation instruments that are validated, standardized, or grounded in established empirical frameworks, such as recognized accessibility metrics, certified assessment tools, or instruments with documented reliability or methodological support. In contrast, informal assessment refers to ad hoc or context-specific evaluation practices, in which inclusivity is assessed through non-validated questionnaires, exploratory feedback mechanisms, or bespoke evaluation tools developed for a specific case without formal validation. In this way, the review identifies whether inclusive impacts are measured using methodologically robust, comparable instruments or through situational, exploratory approaches.

EC6 criterion captures whether the evaluated smart physical spaces display regulatory compliance with existing regulations, standards, or guidelines related to sustainability and equity. The binary classification (Yes/No) allows for a clear identification of whether studies explicitly reference compliance with building codes, accessibility standards, environmental certifications, or educational regulations. Regulatory compliance serves as an external and objective validation mechanism, complementing experiential and methodological assessments.

EC7 identifies the deployment environment where technology supports inclusive and sustainable education. It distinguishes smart physical environments, hybrid environments, and fully virtual environments. Smart physical environments are technology-enhanced spaces with digital systems in the infrastructure (e.g., smart classrooms or sensor-enabled campuses). Hybrid environments combine physical spaces with digital or virtual components, enabling blended interactions. Fully virtual environments are instructional settings where studying and interaction occur entirely in cyberspace.

EC8 identifies stakeholders involved in implementing technology for inclusive and sustainable educational spaces: universities, technology or construction companies, governments or public agencies, and NGOs or non-profits. Identifying stakeholders clarifies who drives, supports, and sustains efforts, and how responsibilities are distributed across academic, industrial, public, and civil sectors.

EC9 describes the collaboration model of how researchers and stakeholders work together to create and use technology in inclusive and sustainable educational spaces. It differentiates between cases in which stakeholders receive only the technology and cases in which they are actively involved by funding, supporting institutions, co-developing, or commercializing the solution during or after its creation. With this distinction, the review can determine whether new technologies arise solely from research or from joint efforts that also deliver economic value and ongoing investment, revealing different levels of involvement and long-term support.

EC10 distinguishes the research approach of technology implementation in inclusive and sustainable educational spaces. Empirical studies are works that report on implemented, tested, or evaluated technological interventions in real or simulated instructional settings, providing observed outcomes or measurable results. Conceptual proposals, in contrast, describe envisioned or designed technological solutions that are conceptually based but have not yet been empirically implemented or validated. This distinction enables the review to differentiate between documented implementations and proposed approaches, thereby allowing clearer interpretation of the maturity and usefulness of the reported examples.

2.2 Executing the review

The review was conducted in May 2025. After applying the inclusion/exclusion criteria to the studies obtained through the searches, the articles were selected, as shown in Figure 1. In addition, four additional articles, identified through manual searching, were considered. Then, a total of 20 studies were analyzed in depth considering quality and extraction criteria.

2.3 Study quality and validation procedures

This section describes the validation process carried out to ensure that the SLR on sustainability and inclusivity in educational spaces through technology was as objective and replicable as possible. For this purpose, we addressed the validation of four fundamental aspects: the review protocol, the selection of primary studies, the quality assessment of the studies, and the data extraction and classification criteria. Besides, to enhance transparency and reproducibility, the artifacts generated throughout the SLR process have been deposited in the Open Science Framework (OSF) repository, where they are openly available for consultation and replication purposes: https://osf.io/f5rxq.

2.3.1 Validation of the review protocol

To evaluate the SLR protocol, we relied on the PICOC and methodological guidelines for systematic reviews used in software engineering, which are extensible to other scientific areas. Before starting the validation process, the authors conducted an analysis of potential methodological weaknesses in the study. To reduce the risk of omission bias, a set of digital scientific databases relevant to the analysis of the review's topic was selected. These databases included Scopus, Google Scholar, SpringerLink, ScienceDirect, IEEE Xplore, and ACM Digital Library, covering education, sustainability, architecture, and technology. In addition, journals, conferences, and academic events related to technologies applied to learning and the design of universal spaces were reviewed.

The search string process was cyclical and divided into several phases. The goal was to create search chains that encompass the research questions and address both sustainability and educational inclusion through technology. To do this, synonyms and lexical variations of key terms such as “accessibility,” “educational spaces,” “inclusive education,” “sustainable design,” “educational technologies,” and “neuroarchitecture” were included. Boolean operators were applied based on each database's characteristics. Language filters were applied to include only studies published in English, ensuring that all reviewers could properly interpret and examine the selected papers.While English represents the predominant language in the consulted digital libraries, the authors acknowledge that this restriction may have led to the exclusion of relevant research published in other languages, particularly in regions where sustainability and inclusion are actively studied within different educational and cultural contexts. Therefore, future reviews could expand their scope to include multilingual searches to provide a broader, more geographically diverse perspective.

It is necessary to clarify a methodological aspect regarding the temporal framework. Although the initial search horizon was established in 2015 in order to capture the theoretical foundations of educational sustainability, after applying the inclusion, exclusion, and data extraction criteria, the final corpus of analyzed articles consisted of studies published from 2022 onwards. It was identified that the real convergence between neuroarchitecture, inclusive technologies, and sustainability reached its scientific maturity after the disruptive changes brought about by the pandemic.

2.3.2 Validation of study selection process

The main threats to validity at this point are usually related to ambiguous descriptions of the criteria, which can lead to incorrect interpretations and, consequently, inconsistent classification among reviewers. To avoid that and ensure the correct application of the inclusion and exclusion criteria defined for this SLR, and that the selected studies were consistent with the research questions, a formal validation process was conducted for the selection of primary studies. Three random scientific articles were selected on sustainability, inclusion, and educational technology. Three team members independently applied the previously defined inclusion and exclusion criteria. The results were analyzed using Fleiss' Kappa, a quantitative measure of agreement among multiple evaluators (Landis and Koch, 1977). This metric checks if agreement exceeds chance and assigns a value between 0 (no agreement) and 1 (perfect agreement). In this exercise, the Fleiss' Kappa value was 0.75, which, on the interpretation scale, indicates substantial agreement.

2.3.3 Quality assessment of primary studies

A quality assessment was applied to the selected primary studies using a normalized 0–1 scale to evaluate their methodological rigor, thematic relevance, and empirical contribution. First, a bibliometric weighting system was incorporated based on the number of citations and the year of publication, as presented in Table 6. The categories were classified as “Very High,” “High,” “Medium,” “Low,” and “Very Low.” To avoid penalizing recently published studies with naturally low citation counts, the scoring scheme assigns high scores to very recent publications to account for their limited time to accumulate citations. These scores were not used as exclusion criteria but rather to support the identification of the most robust and relevant studies during the qualitative synthesis phase. Overall, the analyzed corpus presented a high bibliometric profile, as shown in Table 7, with an average weighting score of 0.89 across the twenty reviewed studies, indicating that the selected papers are generally well cited in venues with recognized academic relevance.

Second, a set of subjective and objective evaluation questions was established. The subjective criteria examined whether: (i) the study addressed sustainability and inclusion inside educational spaces, and (ii) the study proposed technological solutions with functional applications for sustainable and inclusive learning environments. The objective criteria assessed whether: (i) the study was published in a relevant journal or conference within the domains of technology, education, sustainability, and inclusion, and (ii) the study reported empirical results, assessment criteria, or practical evidence supporting its proposals. Each question was scored numerically as presented in Table 7, and the aggregated results showed consistently high quality across the selected studies, with average scores surpassing 0.8 on all evaluation dimensions, signifying strong methodological soundness and relevance of the included‘literature.

3 Results

A multi-database search strategy was implemented across several scientific databases, yielding an initial set of studies for the review. After applying predefined inclusion and exclusion criteria, a final sample of 20 articles was selected for systematic analysis. A time-based analysis of publication years was conducted to examine the distribution of the selected studies over time. Figure 2 presents the number of articles published per year, showing that most of the selected studies were published between 2023 and 2025.

Figure 2

3.1 General description of the selected studies

The selected studies exhibit a heterogeneous distribution over the defined extraction criteria, reflecting varying levels of emphasis on inclusion, sustainability, and technological approaches in educational contexts. As shown in Table 8, general criteria, such as educational spaces and technology, were present in all analyzed studies (100%), indicating their central role in the reviewed literature. Criteria related to sustainability and inclusivity were addressed in 80% of the studies, showing a strong but not universal integration of these dimensions. In contrast, aspects such as biophilia (0%), spatial configuration and flows (35%), and natural and artificial lighting (20%) were less frequently examined, highlighting thematic areas that remain underrepresented and need further investigation. These disparities reveal an uneven research focus, with greater attention paid to digital and technological aspects than to the physical and neuroarchitectural dimensions of educational environments.

As part of the analysis, cross-tabulations were conducted according to the previously defined criteria. To present results, bubble charts were used to illustrate the simultaneous overlap of two dimensions across the reviewed studies. Each bubble represents the number of articles that address both criteria jointly, facilitating the identification of recurring research patterns, gaps, or contrasts within the field. In the figures below, the axes correspond to the analyzed criteria.

The three most relevant cross-references selected for this section are presented below. In each chart, the bubble size and the number indicate how many articles address both criteria simultaneously.

Cross-referencing facilitates the identification of relevant patterns within the analyzed studies. As illustrated in Figure 3, sustainability and inclusivity represent the largest number of technological applications in the reviewed literature. The highest frequencies occur in the “Other” category, with 12 studies addressing sustainability and 15 addressing inclusivity. Substantial contributions are also evident in Artificial Intelligence (11 and 12 studies, respectively) and Augmented/Virtual Reality. In contrast, associations with Neuro-Architecture are minimal across all technological approaches, with only one study in Artificial Intelligence and one in the 'Other' category, and are absent in all other areas. This indicates a distinct research gap that remains largely unexplored.

Figure 3

Figure 4 illustrates the relationships between technological approaches and spatial experience design criteria in the analyzed studies. The results show that the Spatial Configuration and Flows dimension accounts for the highest number of matches across different technologies, particularly within the Internet of Things (5 studies), followed by the 'Other' category (4 studies). Similarly, Natural and Artificial Lighting presents notable associations, especially with the Internet of Things (3 studies) and Artificial Intelligence (2 studies). In contrast, Biophilia shows no associations across all technological approaches, with zero occurrences recorded. These patterns suggest that current research tends to prioritize spatial configuration and environmental lighting aspects when integrating technology into spatial experience design, while biophilic considerations remain entirely underexplored in the reviewed literature.

Figure 4

Figure 5 illustrates the distribution of stakeholders involved in the development and implementation of technological approaches. The results show that Universities represent the most prominent actors, particularly in studies categorized under “Other” technologies (15), followed by Artificial Intelligence (14) and Augmented/Virtual Reality (12). Governments or public agencies also demonstrate a notable level of participation, especially in the “Other” category (13) and in Artificial Intelligence (11). In contrast, Technology or construction companies and NGOs or non-profit organizations appear less frequently across the analyzed studies, with the latter showing the lowest engagement levels (ranging from 3 to 6 studies). These patterns highlight the central role of academic institutions in driving research and experimentation with emerging technologies, while also suggesting opportunities for broader collaboration with governmental, industrial, and non-profit stakeholders.

Figure 5

3.2 Current technologies for inclusion in educational spaces

Digital technologies are transforming the concept of inclusion in educational spaces, expanding access and adapting environments to students' cognitive, physical, and social needs. The combined analysis shows that technologies such as AI, the IoT, VR, AR, and adaptive platforms are key to this transformation. For instance, Smart Labs integrates environmental sensors and virtual assistants to dynamically adjust variables such as lighting and temperature, creating responsive and accessible learning environments (Hariyani et al., 2025). Similarly, systems based on biosensors and machine learning algorithms have been used to adapt lighting conditions according to students' cognitive load, linking environmental comfort with learning-related outcomes (Jung et al., 2025).

From a virtual perspective, the Edu-Metaverse is described as a three-dimensional ecosystem enabling active participation through intelligent avatars, supporting students in rural contexts or those facing social integration challenges (Zhai et al., 2023; Bobko et al., 2024). These environments present immersive experiences, personalized tutoring, and collaborative learning, reducing anxiety while promoting affective inclusion. Complementarily, VR has been applied to represent complex processes that cannot be physically reproduced (Jarrin et al., 2024). The convergence of XR, AR, and VR technologies has also been linked to improvements in comprehension, retention, and academic performance (Sikand and Rattan, 2024; Ader et al., 2023).

Regarding cognitive inclusion, AI-based recommendation systems adapt pedagogical strategies for students with cognitive or sensory disabilities (Bressane et al., 2024), while intelligent classroom management systems reorganize educational spaces according to occupancy dynamics, integrating sustainability and inclusion principles (Ye et al., 2025). Similarly, adaptive platforms such as OpenEDR4C provide multimodal content tailored to diverse learning styles (Alvarez-Icaza et al., 2024; Deng et al., 2023). In contexts affected by the digital divide, access to digital infrastructure strongly influences students' perceptions and use of technology (Alam et al., 2023; Hariyani et al., 2025). Disconnected and low-cost educational technologies have shown strong potential to reduce inequality while adhering to the principle of “leaving no one behind” (Portela et al., 2024), aligned with Universal Design for Learning principles, which promotes multiple pathways for access, participation, and expression(Ader et al., 2023). Finally, specialized technologies such as LECTPAT (Balderas et al., 2024), a multimodal platform based on pictograms for students with cognitive disabilities, along with multisensory aids such as subtitles, haptic feedback, or smart glasses, reinforce the idea of education centered on diversity and individualized responses to student needs.

3.3 Indicators and methods for measuring inclusion and sustainability

The reviewed studies reveal diverse methodologies for assessing inclusion in educational spaces, encompassing cognitive, digital, social, and perceptual dimensions. An innovative approach is proposed based on AI (Bressane et al., 2024), where multilayer neural networks and fuzzy logic allow for the evaluation of the level of “learning limitation” and “potential for improvement” of students with disabilities. This system generates real-time, adapted pedagogical recommendations, promoting effective personalization of teaching. From a technical standpoint, space utilization is modeled with deep learning algorithms based on occupancy, energy consumption, and usage patterns, with direct implications for equity in resource allocation and educational planning (Ye et al., 2025). In contrast, a perceptual approach merging surveys with physical measurements (temperature, lighting, and ventilation) is adopted to examine how environmental quality affects student satisfaction and well-being, key components of sensory and emotional inclusion (Al-Dmour, 2024). Focusing on digital inclusion, a qualitative method based on attitude models and thematic analysis using NVivo is employed, highlighting social-cultural factors that shape perceptions of technological accessibility in contexts with limited infrastructure (Alam et al., 2023). This perspective is reinforced by studies reporting no significant differences in skill development between rural and urban students when using disconnected educational technologies, underscoring their potential to reduce the digital divide (Portela et al., 2024). Regarding accessibility indicators, technical criteria such as color contrast, semantic structure, keyboard navigation, and compatibility with assistive technologies (ARIA) are systematized to ensure inclusive digital environments (Balderas et al., 2024). Within this context, SDG 4 (inclusive and quality education) and SDG 10 (reduced inequalities) emerge as central frameworks directing evaluative practices. Teacher training, critical thinking, and self-efficacy are emphasized as core competencies that should be systematically assessed (Ciolacu et al., 2023). Consequently, inclusion indicators are evolving from basic access metrics toward multidimensional systems that integrate perception, adaptability, and equity.

Approaches to educational sustainability are similarly diverse but tend to align with regulatory frameworks and technological solutions. A comprehensive model based on 232 official indicators from UNDP, SDG Compass, and IRIS+ enables the evaluation of energy efficiency, physical accessibility, resource consumption, and user well-being inside the SDG framework (Ángeles Verdejo et al., 2022). Global models such as the Digital Sustainability Index (DSI), the Digital Transformation Framework (DTF), and the Impact Pathways Framework (IPF) complement this vision, quantifying the social, economic, and environmental impacts of digital technologies (Hariyani et al., 2025). Multi-objective optimization models in VR-simulated environments support sustainability-related decision-making in construction, demonstrating the value of simulation during design phases (Jarrin et al., 2024). Other studies integrate ambient intelligence techniques. Biosignal-based systems combine indicators such as visual fatigue and cognitive performance with energy simulations to dynamically adjust lighting in learning spaces (Jung et al., 2025), while occupancy sensors record and analyze behavior patterns in educational environments, improving space efficiency, adjusting environmental conditions, and lowering energy consumption based on users' real behavior (Alsafery et al., 2023). Beyond SDG 4 and SDG 10, SDG 3 (good health and well-being) and SDG 17 (partnerships for the goals) are incorporated into initiatives intended to develop cross-cutting sustainability competencies, assessing not only the ecological performance of educational spaces as well as their capacity to encourage environmental awareness and collective responsibility among future professionals (Ciolacu et al., 2023).

3.4 Examples and notable implementation cases

The reviewed studies provide diverse examples of how digital technologies are applied to promote inclusion and sustainability in educational environments, spanning physical spaces, virtual simulations, and large-scale deployments, all supported by empirical evidence. One of the most comprehensive cases is the UJAmI Smart Lab at the University of Jaén (Ángeles Verdejo et al., 2022). Equipped with over 130 devices, including environmental sensors and virtual assistants, this intelligent environment enables the simultaneous assessment of accessibility, energy efficiency, and user well-being. Its design regards it as a living laboratory for validating SDG indicators, with strong potential for replication in educational contexts.

Several studies further demonstrate the impact of improving environmental conditions on student experience. Campus-based studies show that enhancing variables such as ventilation and lighting significantly increases student satisfaction (Al-Dmour, 2024), while adaptive lighting systems improve concentration and reduce visual fatigue (Jung et al., 2025). Energy optimization and more accurate occupancy management are also reported through intelligent space monitoring (Ye et al., 2025), and occupancy and environmental sensors, such as those used in the SpaceSense project in the United Kingdom, support evidence-based decisions on space usage, confirming the operational value of educational sensorization (Alsafery et al., 2023). Beyond physical spaces, virtual and immersive environments also play a relevant role. The educational potential of the Metaverse has been analyzed as a framework for fostering equity through virtual teaching communities and immersive interaction, underscoring collaboration and inclusive knowledge creation (Zhai et al., 2023). In real-world contexts, VR-based simulations show improvements of 48.3% in decision-making accuracy in construction planning related to sustainability (Jarrin et al., 2024).

From a pedagogical perspective focused on cognitive and digital inclusion, educational recommendation systems based on neural networks and fuzzy logic have been deployed with over 800 university students, enabling differentiated interventions tailored to disability types, including multisensory resources and collaborative platforms (Bressane et al., 2024). Multiple use cases involving AI, the IoT, and blockchain further support adaptive learning, intelligent classroom monitoring, and secure educational certification, illustrating the strategic value of integrated technological ecosystems (Hariyani et al., 2025). Large-scale implementations additionally reinforce the equity dimension, as digitalization positively impacts student attitudes while unequal access to technology perpetuates academic lag (Alam et al., 2023). Programs such as AIED Unplugged in Brazil benefited more than 164,000 students across 8,238 schools by giving personalized feedback to improve writing skills, with no notable performance differences between rural and urban students, confirming the potential of disconnected technologies to reduce educational inequality (Portela et al., 2024).

Finally, institutional initiatives illustrate the integration of inclusion, sustainability, and future-oriented competencies. Programs such as Digital Learning Media Pro, focused on teacher training in digital media, and the Education 4.0 Challenge seminar, which applies design thinking to strengthen transversal skills, are documented at the University of Passau (Ciolacu et al., 2023). In parallel, the VictoryXR Metaversity program connects more than 15 universities through a digital twin campus, expanding access to inclusive and personalized learning in virtual environments (Sikand and Rattan, 2024).

4 Discussion

This section analyzes the relevance and contributions of the findings obtained in this SLR, highlighting the strengths and weaknesses of the collected evidence. Likewise, the limitations of this review, their possible solutions, and the validation of the protocol applied in the Protocol Design section are discussed. These findings demonstrate that implementing technological solutions that meet sustainability and educational inclusion criteria presents a complex challenge and requires detailed analysis.

4.1 Strengths of the research

A strength of the reviewed studies is the diversity of methodological methods employed, ranging from advanced computational models to qualitative methods. Bressane et al. (2024) demonstrate “an original approach based on AI, where multilayer neural networks and fuzzy logic allow the evaluation of the degree of learning limitation and possibility of improvement,” while (Alam et al., 2023) employ “a qualitative approach based on attitude models and thematic analysis with NVivo, revealing socio-cultural factors that influence the perception of technological accessibility.” These methodological examples enrich understanding of the studied phenomenon from various approaches and help identify not one but several possible solutions to the issue at hand.

Several documented cases provide robust evidence of the effectiveness of technological applications in inclusive education. The AIED Unplugged program in Brazil by Portela et al. (2024), for instance, benefited more than 164,000 students across 8,238 schools by giving personalized feedback. Similarly, the Smart Lab UJAmI by Ángeles Verdejo et al. (2022) is equipped with over 130 devices, including environmental sensors and virtual assistants, enabling the deployment of advanced educational technologies. In addition, a study by Jarrin et al. (2024) reports quantitative outcomes, including a 48.3% improvement in the accuracy of constructive decision-making when VR is applied to construction planning.

The findings of this SLR reveal that the analyzed technological applications have considerable potential to promote inclusivity and sustainability in education, demonstrating that technology can help create more equitable and environmentally responsible educational environments. The emerging adaptive systems exemplified suggest a promising integration toward educational ecosystems that not only respond to learner-specific learning needs but also optimize resource use and minimize environmental impact.

4.2 Weaknesses and limitations of the research

A significant limitation of this review lies in the scarcity of studies that directly address the convergence of concepts such as inclusivity, neuroarchitecture, and educational sustainability, which constitute the fundamental pillars of our analysis. The objective was not to examine these topics in isolation, but rather to identify the nexus where all these criteria converge in order to better understand the challenges of modern educational spaces. Under this premise, the fact that only 20 articles were identified is itself a finding. Among the 20 articles that form the documentary basis of this study, at least one investigation was found that articulates inclusivity, neuroarchitecture, and educational sustainability jointly as a line of analysis. This limitation highlights the need to develop research approaches that integrate sustainability, inclusion, and neuroarchitectural principles as complementary elements of educational design. Part of this limitation may be explained by the current state of development of neuroarchitecture within the educational technology literature. Although neuroarchitecture is frequently referenced as a conceptual framework, its effective integration into empirical studies remains limited. This may be attributed to the relative novelty of neuroarchitecture as an interdisciplinary field, as well as to the persistent fragmentation among architecture, neuroscience, and research on technology-mediated learning environments. Consequently, the literature tends to present neuroarchitecture more as a conceptual promise than as a fully operationalized research domain.

On the other hand, the reviewed studies focus primarily on short-term evaluations or technical validations. Although immediate improvements are documented, such as the one reported by Jung et al. (2025), who found that their “bio-signaled adaptive lighting system improves concentration and reduces visual fatigue,” there is little evidence of the sustained impact of these technologies on long-term learning outcomes. A continuing tension persists between technological sophistication and actual accessibility. While some studies propose highly technological solutions, others recognize that “the conditions of access to digital infrastructure significantly influence students' perception of technology and its use” by Hariyani et al. (2025); Alam et al. (2023). This paradox is evident in the contrast between highly equipped Smart Labs and the AIED Unplugged approach by Portela et al. (2024), which “proposes intelligent educational solutions compatible with low-cost devices and offline functions”. In this context, advancing the evidence-based integration of neuroarchitecture into educational technology research requires the development of robust neurocognitive indicators that objectively capture the effects of spatial design on learning experiences. Relevant indicators may include sustained attention, cognitive load, stress reduction, emotional well-being, and working memory performance. These variables can be assessed through different methodological approaches, including validated questionnaires, physiological measurements such as heart rate variability or electrodermal activity, and interaction analytics derived from digital learning platforms.

The findings show a trend toward a major transformation of educational environments, in which technology serves as a mediator, reshaping physical spaces to promote both inclusivity and sustainability. The systems proposed by Ye et al. (2025), which allow “reorganizing educational spaces based on actual occupancy and user dynamics, thus integrating sustainability and inclusion from an infrastructural perspective”, illustrate this technological approach. However, this dependence on technology as the main solution to achieve inclusion and sustainability goals can be problematic because it oversimplifies these difficult topics discussed throughout the review, since without comprehensively considering the social, pedagogical, or structural dimensions involved in inclusion and sustainability, there is a risk of thinking that merely using technology will solve everything. Other problems must also be analyzed, including geographic location, socioeconomic inequalities, cultural issues, and unconsidered environmental impacts.

Finally, other limitation of this review lies in the selection of search sources. The automatic search was performed in major domain-specific digital libraries instead of multidisciplinary indexing databases such as Scopus and Web of Science. While these libraries offer strong coverage of Computer Science publications, the absence of indexing databases may have reduced the likelihood of identifying relevant studies from related disciplines.

4.3 Future work

This SLR reveals that integrating digital technologies to promote sustainability and inclusivity in educational spaces represents a dynamic and promising field, exemplified by successful cases ranging from the Smart Lab UJAmI (Ángeles Verdejo et al., 2022) to AIED Unplugged (Portela et al., 2024). However, challenges remain, such as achieving long-term sustainability and equity in access, which future work must address while continuing to explore the potential of these technologies to create inclusive, sustainable, and effective educational systems.

Research is needed to document sustained impact past the immediate improvements reported, such as the “48.3% improvement in the accuracy of constructive decisions” reported by Jarrin et al. (2024), or the improvements in concentration documented by Jung et al. (2025). It is necessary to examine the factors that facilitate the transition from pilot implementations to large-scale deployments, such as AIED Unplugged (Portela et al., 2024), while considering different sociocultural contexts, such as those analyzed by Alam et al. (2023).

Consequently, future research should focus on developing integrated guidelines for the effective incorporation of emerging technologies into neuroarchitectural solutions to enhance well-being, accessibility, inclusion, and sustainability within educational environments. Also, future work should explore how technologies can be “culturally relevant and contextually appropriate,” expanding the AIED Unplugged by Portela et al. (2024) approach that seeks “alignment with the principle of ‘leaving no one behind.” It is also necessary to further examine long-term economic viability, especially considering the investment required in infrastructure, such as the “more than 130 devices” of the Smart Lab UJAmI (Ángeles Verdejo et al., 2022) vs. low-cost solutions like those proposed in AIED Unplugged (Portela et al., 2024).

In this context, neuroarchitecture offers a key dimension for the design of educational spaces. The incorporation of neuroarchitectural principles allows the creation of environments that support concentration, well-being, and sensory inclusion, especially when combined with adaptive technologies and environmental sustainability criteria. This combination of physical design, technology, and environmental awareness enhances not only the learning experience but also equity and accessibility in diverse contexts. Therefore, it is vital to conduct multiple studies to combine these concepts, which are key to achieving the main objectives of inclusion and sustainability in the educational field and globally, as they could easily be adapted not only to the educational context but to society in general.

5 Conclusions

This SLR shows that technology is fundamental for creating educational spaces that integrate inclusion and sustainability. This analysis has demonstrated that tools such as AI, the IoT, VR/AR, and immersive environments like the Edu-Metaverse are redefining not only the way learning is conducted but also how educational spaces are designed, managed, and adapted. The reviewed technologies enable the promotion of inclusion by adapting to the cognitive, sensory, physical, and geographic diversity of students, particularly those in vulnerable situations or with disabilities. They also promote sustainability through the integration of smart infrastructures that optimize resources such as energy, space, and materials, in alignment with the SDGs, particularly SDG 4 (quality education), SDG 10 (reduced inequalities), and SDG 17 (partnerships for the goals). However, the study also reveals key challenges that need to be addressed: there is low integration among the fields of neuroarchitecture, inclusion, and sustainability, which limits the development of educational solutions that combine these areas.

This review also shows that neuroarchitectural approaches remain infrequently integrated within research on technology-mediated education. Future studies should therefore explore interdisciplinary frameworks that combine spatial design principles, neurocognitive indicators, and HCI methodologies in order to better understand how built environments and digital technologies jointly shape inclusive and sustainable learning experiences. Therefore, the following actions are proposed to advance the design and implementation of inclusive and sustainable technologies in education: Design comprehensive systems that combine neuroarchitectural principles, sustainability indicators (such as biophilia, energy efficiency, or indoor environmental quality), and inclusive pedagogies oriented toward personalized learning. Promote scalable, low-cost solutions, especially for rural areas or those with infrastructure limitations, prioritizing offline platforms, accessible technologies, and adaptive content capable of facilitating teaching and learning processes in diverse contexts. Foster strategic partnerships among governments, universities, technology companies, and social organizations to democratize access to educational innovations and ensure that no group is left behind. Lastly, promote interdisciplinary research that measures the real impact of these technologies on variables such as performance, motivation, mental health, institutional sustainability, and educational equity.

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