Particularly, Scopus is recognized for its expansive collection of peer-reviewed content, excelling in the fields of science, technology, and education. It offers a comprehensive array of journals and conference proceedings, ensuring a rich amalgamation of research pertinent to the academic and practical dimensions of STEM education. Its advanced indexing capabilities facilitate an exhaustive retrieval of contemporary and archival studies.

Similarly, Web of Science complements Scopus with its rigorous selection of quality research articles and robust citation indexing, which is invaluable for tracing the influence and evolution of key research within the field. It provides a structured and academically robust platform for accessing influential studies that have shaped the current landscape of immersive technology in education.

We also included PubMed due to its strong emphasis on biomedical and life sciences, which are integral to the broader STEM education framework. PubMed provides access to a vast repository of biomedical literature, including studies on the educational applications of immersive technologies in health and medical training. Its comprehensive indexing and advanced search functionalities ensure the inclusion of high-quality, relevant studies that contribute to our understanding of immersive technologies in various STEM disciplines.

Full-length original research articles: We excluded editorials, brief communications, reviews, and commentaries to maintain the integrity of empirical evidence provided by detailed research articles.

Focus on STEM education and training: Articles must explicitly address STEM education and training, ensuring relevance to our research question on immersive technologies in these disciplines.

Evaluation of VR, AR, or IVEs: Only studies evaluating the use of virtual reality (VR), augmented reality (AR), or immersive virtual environments (IVEs) as educational tools were included.

Implementation of simulators or learning outcomes: Studies must investigate the use of simulators or assess learning outcomes related to STEM integration through immersive technologies, aligning with our PICOS framework.

Application of AR and VR technologies: articles needed to delineate the application of augmented reality (AR) and virtual reality (VR) technologies within STEM-focused educational contexts.

Emphasis on immersive technologies for learning and teaching: the focus was on using immersive virtual or augmented reality as tools for learning and teaching within STEM education.

Educational objectives within STEM disciplines: the utilization of virtual environments had to predominantly serve educational objectives within STEM disciplines.

Influence of immersive technology interventions: impact on student performance and engagement.

Type of immersive technology employed: distinguishing between VR and AR interventions.

Observed effects: results from the implementation of these technologies.

Participant demographics and roles: including sample size and participant roles.

Architecture and instructional design: design of the VR or AR tools used in the studies.

Learning materials: nature and creation of materials within the virtual environment.

Cognitive demands and time management: cognitive load imposed by the technologies and implications for time management.

Feedback mechanisms and interactivity: presence of feedback systems and level of interactivity afforded by the technologies.

Stratification of participants: sorting participants by their roles and degrees of involvement.

Performance: the effect of these interventions on performance is analyzed, focusing on the enhancement of skill acquisition and knowledge retention. This analysis spans a broad range of outcomes, from increased proficiency in educational practices to improved accuracy in applying STEM methodologies. Performance, in this context, is crucial as it directly correlates with the essential competencies that professionals in science, technology, engineering, and mathematics need to develop and refine throughout their careers.

Engagement: this aspect evaluates the diverse ways in which students engage with and embrace VR/AR technologies within their STEM education. Indicators of engagement include a heightened readiness to incorporate these technologies into the learning environment, active participation in tech-driven educational tasks, and a persistent interest in the evolution of immersive tools. Engagement is a vital measure, reflecting both the integration of these technologies in STEM fields and their capacity to foster transformative educational approaches.

Positive Effects underscore the beneficial outcomes of employing immersive technologies in STEM education, encompassing enhanced academic performance, elevated motivation among learners, and a more engaging learning environment.

Increased Proficiency signifies the marked enhancement in students' STEM capabilities and understanding, facilitated by the interactive and hands-on learning experiences that VR and AR offer.

Effectiveness gauges the achievement of educational objectives through VR and AR interventions, emphasizing their role in bolstering engagement, improving performance metrics, and aiding the retention of knowledge in STEM disciplines.

Nadan et al. (2011) utilized VR technologies like CAVE and PowerWall in educational settings, observing a positive impact on student engagement.

Nagata et al. (2017) employed AR for mobile learning to enhance comprehension in STEM, noting positive effects on both performance and engagement.

Hsu et al. (2017) explored the role of AR in medical surgery lessons, finding an increase in STEM interest and comprehension.

Abd Majid and Abd Majid (2018) leveraged AR for interactive content on atomic structures, enhancing comprehension and engagement positively.

Cooper et al. (2019) investigated the perceptions of VR in pre-service teachers, marking an increased engagement in educational settings.

Jesionkowska et al. (2020) used AR in extracurricular STEAM workshops, observing positive outcomes in both performance and engagement.

Dayarathna et al. (2020) introduced a VR module on queuing theory, showing increased performance in learning manufacturing systems.

Lasica et al. (2020) and Rowe et al. (2020) assessed the AR and XR pedagogical value, respectively, each noting positive impacts on performance.

Mohammadi et al. (2019) and Holly et al. (2021) demonstrated the positive influence of VR on engagement in online experiential learning and physics education.

Montalbo (2021) and Shu and Huang (2021) utilized AR for chemistry education and VR in Maker education, respectively, with positive effects on performance and effectiveness in engagement.

Miller et al. (2021), Wu et al. (2021), and Hobbs and Holley (2022) each reported positive impacts of MR and VR on performance and engagement through immersive learning designs and curriculum integration.

Kao and Ruan (2022), Lindner et al. (2022), and Campos et al. (2022) found increased engagement and performance through interactive AR modes and applications in programming and environmental science.

McNerney et al. (2023) and See et al. (2023) explored the role of XR and AR in simulation learning and remote sensing education, noting positive outcomes.

Chiang and Liu (2023) examined XR technologies in STEM activities, observing positive impacts on learning response and performance.

Evaluation Stage: AR was used in five studies, VR in 3, and XR in 1, but no MR was utilized. This indicates that AR is the preferred technology during the evaluation phase of research.

Development Stage: Both AR and VR were used in three studies each, with XR and MR each being used in one study. This demonstrates an equal preference for AR and VR during the development phase, with some consideration given to mixed or extended realities.

Development and Evaluation Stage: Only AR was used in one study. No instances of VR, XR/AR/VR, or MR were recorded at this stage.

Development and Testing Stage: AR was used in two studies, and VR in 1, with no use of XR/AR/VR or MR.

Chi-squared Value: 4.754.

Degrees of Freedom: 12.

p-value: 0.966.

Performance: AR was used in 36.4% of the studies, and VR in 28.6%.

Engagement: AR featured heavily at 71.4%, confirming a strong preference for AR in studies examining engagement.

Performance and Engagement: the combination of AR and VR was used in 50% of studies each, suggesting an equal distribution for studies that looked at both variables simultaneously.

Chi-squared Value: 9.752.

Degrees of Freedom: 8.

p-value: 0.283.

Increase: the effect classified as “Increase” was observed in 27.3% of studies using AR and 28.6% of studies using VR, with no occurrences in XR/AR/VR or MR.

Positive: most effects classified as “Positive” were observed in studies using AR (72.7%), followed by VR (57.1%), XR/AR/VR (100%), and MR (100%). This indicates that studies using AR and VR frequently report positive outcomes, and those that include a mix of technologies or MR always report positive outcomes.

Effectiveness: “Effectiveness” was observed in 14.3% of VR studies, with no recorded effectiveness in AR or combined technologies, and no studies were reporting on MR under this category.

Chi-squared value: 3.900.

Degrees of freedom: 8.

p-value: 0.866.

Constructivist learning theory: constructivist learning theory posits that learners construct knowledge through experiences and interactions with their environment (Marougkas et al., 2023). Immersive technologies such as VR and AR align well with this theory by providing interactive and experiential learning environments. These technologies enable learners to actively engage with content, facilitating deeper understanding and retention of complex STEM concepts.

Technology Acceptance Model (TAM): the Technology Acceptance Model explains how users come to accept and use a technology (Rejali et al., 2023). It suggests that perceived ease of use and perceived usefulness significantly influence users' attitudes toward technology. By integrating VR and AR into STEM education, this model helps explain how these technologies can be effectively adopted by both educators and students, enhancing engagement and performance.

Self-Regulated Learning Theory: self-regulated learning (SRL) refers to the process where learners proactively manage their learning by setting goals, monitoring progress, and reflecting on outcomes (Chocarro et al., 2023). Immersive technologies support SRL by providing personalized and adaptive learning experiences. Features such as immediate feedback and interactive simulations empower students to take control of their learning process, promoting autonomy and motivation.

SAMR Model: the Substitution, Augmentation, Modification, Redefinition (SAMR) model provides a framework for integrating technology into education (Hamilton et al., 2016). It categorizes the use of technology into four levels, from the basic substitution of traditional methods to the transformative redefinition of learning tasks. This model helps in evaluating how VR and AR can be used to not only enhance but also transform STEM education practices.

Nadan et al. (2011) contributed to the understanding of VR's memorability, laying foundational work for its potential to enhance learning experiences in STEM.

Nagata et al. (2017) offered a pioneering application of AR in mobile learning, enhancing the comprehension of STEM disciplines in real-world contexts.

Hsu et al. (2017) examined AR's impact on stimulating interest in STEM fields through medical surgery simulations, addressing the need for engagement in high school students.

Abd Majid and Abd Majid (2018) contributed an AR application designed to support guided discovery learning, providing an innovative approach to complex STEM subjects.

Cooper et al. (2019) explored VR's transformative potential in classrooms, capturing pre-service teachers' perceptions and apprehensions.

Jesionkowska et al. (2020) showed the effectiveness of AR in active STEAM learning, allowing students to create their own AR applications.

Dayarathna et al. (2020) provided insight into the gender-based effects of VR teaching modules on learning manufacturing systems, contributing to the inclusivity in STEM education.

Lasica et al. (2020) developed a TPD program to examine AR's impact on teaching, adding value to teachers' professional development in STEM education.

Rowe et al. (2020) ventured into K-12 perceptions of XR and smart building sensors, pioneering the use of such technologies in early education.

Mohammadi et al. (2019) studied the benefits of online experiential learning, particularly for workforce development and inclusion in STEM fields.

Holly et al. (2021) focused on VR for teaching physics, addressing both the design challenges and the pedagogical benefits of immersive experiences.

Montalbo (2021) developed an AR-enhanced TLM, providing evidence for the effectiveness of AR in enhancing spatial skills in chemistry education.

Shu and Huang (2021) combined VR with Maker education to address COVID-19 challenges, demonstrating its positive impact on learning effectiveness and self-efficacy.

Wu et al. (2021) integrated SSM with mixed reality to optimize RFID education, paving the way for better alignment of technology education with stakeholder needs.

Miller et al. (2021) revealed the benefits of IVR activities on organic chemistry performance, particularly for first-generation college students.

Hobbs and Holley (2022) discussed AR's role in curriculum redesign, emphasizing its effectiveness in engaging students and developing project-based learning skills.

Kao and Ruan (2022) introduced an interactive AR system for programming learning, showing that high interactivity can improve learning outcomes.

Lindner et al. (2022) leveraged AR in teaching remote sensing through the UN SDGs, illustrating how technology can make complex subjects accessible and engaging.

Campos et al. (2022) investigated the use of VR for teaching vectors in physics, showing its potential for enhancing understanding of three-dimensional concepts.

See et al. (2023) described a transdisciplinary approach to teaching XR solution creation, adding to the repertoire of technology education models.

McNerney et al. (2023) piloted the SatelliteSkill5 AR app in schools, exemplifying the successful integration of AR into geography and remote sensing lessons.

Chiang and Liu (2023) analyzed the effects of XR on students' learning responses in STEM education, providing evidence for the efficacy of XR in improving performance and engagement.

AR and VR have been consistently shown to increase student engagement. The immersive nature of these technologies captivates students' attention and increases their willingness to participate in learning activities. For instance, Nadan et al. (2011) and Cooper et al. (2019) documented how VR created memorable learning experiences that actively engaged students.

The use of IVT supports complex concept visualization, making abstract STEM concepts more concrete. Abd Majid and Abd Majid (2018) demonstrated how AR can facilitate the understanding of atomic structures, enhancing students' grasp of intricate subjects.

The novel and interactive experiences provided by IVT can inspire students to pursue STEM majors and careers. Hsu et al. (2017) found that AR increased students' interest in STEM fields, which is crucial for cultivating future scientists and engineers.

Technologies like AR help in developing spatial reasoning, a vital skill in STEM education. Montalbo (2021) showcased that AR could significantly improve students' spatial skills in chemistry.

IVT can accommodate various learning preferences, including auditory, visual, and kinesthetic, thus catering to a broader range of learning styles and needs. This is especially beneficial in STEM fields, where learners often face challenges with traditional teaching methods.

VR and AR can simulate real-world environments, allowing students to practice and refine their skills in a safe and controlled setting. For example, the work by Dayarathna et al. (2020) used VR for teaching manufacturing systems concepts, providing hands-on experience without the associated risks or resource constraints.

IVT offers flexible learning opportunities, enabling students to learn from anywhere. This was particularly evident in studies by Mohammadi et al. (2019) and Shu and Huang (2021), where VR and online experiential learning platforms facilitated education during the COVID-19 pandemic.

IVT not only benefits students but also supports teacher education, as seen in Lasica et al. (2020), where AR was used for teacher professional development programs, enhancing their confidence and ability to teach STEM subjects.

By simulating real-world scenarios, IVT like XR provides experiential learning opportunities that might otherwise be inaccessible. Rowe et al. (2020) explored this through the application of sensor data in smart buildings, expanding the horizons of what can be taught and experienced in a classroom.

The integration of arts with STEM (STEAM) through IVT encourages a holistic educational approach, promoting creativity and critical thinking. Jesionkowska et al. (2020) highlighted this by having students develop their own AR applications, bridging technology with artistic expression.

By providing scalable and potentially cost-effective solutions, IVT can democratize STEM education, making it accessible to larger and more diverse student populations.

Integrating real-world data, like remote sensing, into classroom lessons using AR, as in the work by Lindner et al. (2022), connects students with global issues, promoting problem-solving skills related to actual environmental challenges.

Potkonjak et al. (2016) focused on virtual laboratories, while our review encompasses a wider range of IVT applications, providing a broader understanding of immersive technologies in STEM education.

Unlike Barakabitze et al. (2019), which concentrated on African education systems, our review has a global perspective, considering studies from a variety of international contexts and acknowledging the universal relevance of IVT in STEM education.

While Pellas et al. (2020), Del Cerro Velázquez and Morales Méndez (2021), and Yegorina et al. (2021) reviewed specific technologies like VR and AR, our paper integrates a wider array of technologies including XR and MR, showcasing a comprehensive landscape of immersive technologies' applications.

Yegorina et al. (2021) and McDonald et al. (2022) focused on the undergraduate and primary school levels, respectively. In contrast, our review spans all levels of education, recognizing the importance of IVT across the entire educational spectrum.

Our systematic review paper employs an extensive, methodologically rigorous approach, enhancing the findings of Marrero-Galván and Hernández-Padrón (2022) by addressing some of the methodological deficiencies identified in their review.

We involved an interdisciplinary approach that exceeds the work of Palacios et al. (2022) by not only discussing the importance of new technologies but also critically analyzing their pedagogical implications across various STEM disciplines.

We delve deeper into the effects of IVT on both performance and engagement in STEM education, whereas Pellas et al. (2020) and Del Cerro Velázquez and Morales Méndez (2021) primarily focused on spatial skills and learning motivation. This allows for a more nuanced understanding of how these technologies impact educational outcomes.

As noted by Marrero-Galván and Hernández-Padrón (2022), VR and AR are becoming increasingly popular in educational settings. Our review situates this trend within the broader context of emerging technologies, thereby underscoring the timeliness and relevance of our analysis.

Develop powerful models for understanding scientific and mathematical concepts in K-12 education. Utilize scaffolding, visualizations, animations, and computer-based tools to help students construct, revise, and utilize mental models (Seel, 2017).

Implement mixed reality (MR) systems in lab activities to provide an intuitive understanding of complex scientific concepts, enhance accessibility, and foster collaboration among students (Barrett et al., 2018).

Use virtual reality (VR) simulations to create immersive and interactive learning experiences that enhance student engagement, learning attitude, and enjoyment, especially in non-STEM subjects (Sung et al., 2020).

Integrate augmented reality (AR) applications in primary school curricula to foster collaborative and gamified learning experiences, making subjects like geometry and geography more engaging and interactive (Yegorina et al., 2021).

Incorporate computational and simulation tools in undergraduate curricula to develop algorithmic thinking and problem-solving skills, transforming students from users to developers of innovative computational solutions (McDonald et al., 2022).

Use gamification and ICT tools in geometry teaching to create an engaging and interactive learning environment, utilizing AR and VR to visualize concepts and motivate students through gamified elements like points and badges (Moral-Sánchez et al., 2022).

Design and develop interactive learning environments using multimedia elements, such as 2D and 3D graphics, videos, and AR, to enhance understanding and retention of complex biological processes in subjects like animal developmental biology (Ramli et al., 2022).

Develop AR serious games to introduce and motivate young children toward subjects like chemistry, using tangible interfaces and storytelling to make learning fun and informative (Olim et al., 2023).

Utilize advanced technologies such as AR, CAD software, 3D printing, and GPS in mathematics education to make abstract concepts more tangible and applicable to real-world situations, encouraging creativity and problem-solving (Haas et al., 2023).

Implement gamification and extended reality technologies in courses to enhance student engagement and motivation, using VR and AR to create immersive and interactive learning experiences (Iacono, 2023).

Integrate advanced technologies such as robotics and augmented reality into educational video games to enhance learning outcomes and engagement for preschool children in STEM subjects (Méndez-Porras et al., 2021).

To boost engagement and motivation in STEM education with immersive technologies, design activities that let students actively interact with content, like using VR controllers for virtual experiments. Create immersive, high-quality experiences that make students feel present and in control. Use VR for tasks that benefit from 3D perspectives, such as visualizing molecules or exploring engineering designs (Johnson-Glenberg et al., 2021).

• For educators:

• For technology developers:

• For policymakers:

Long-term effects on learning outcomes: future research should focus on the long-term effects of immersive technologies on learning outcomes. While current studies provide valuable insights into immediate benefits, understanding how these technologies impact students' knowledge retention, skills development, and academic progression over extended periods is crucial. Longitudinal studies that track student performance and engagement with immersive technologies over several years will be particularly valuable in this regard.

Scalability in different educational contexts: investigating the scalability of immersive technologies across various educational contexts is another vital area for future research. Studies should explore how VR and AR can be effectively implemented in diverse settings, including primary and secondary schools, higher education institutions, and vocational training programs. Research should also address the challenges and opportunities associated with scaling these technologies, such as infrastructure requirements, cost-effectiveness, and teacher training.

Integration of pedagogical strategies: building on the findings of researchers like Nadan et al. (2011) and Nagata et al. (2017), future systematic reviews should conduct exhaustive examinations of how pedagogical strategies in VR and AR can be integrated effectively. Particular attention should be paid to enhancing student engagement and accommodating individual learning preferences. Identifying best practices for incorporating immersive technologies into STEM curricula will provide educators with practical guidance on maximizing their educational impact.

Adaptive and personalized learning models: developing and assessing adaptive educational models that utilize VR and AR as more than just interactive tools is essential. These models should cater to the unique learning styles and needs of students, offering personalized learning experiences that adapt to individual progress and preferences. Future research should explore how adaptive technologies can support differentiated instruction and personalized learning pathways in STEM education.

Ethical implications and privacy concerns: as VR and AR technologies continue to permeate STEM education, addressing their ethical implications and privacy concerns becomes increasingly important. Future research must thoroughly investigate data management practices within simulations and ensure the ethical deployment of these technologies for student assessments and educational experiences. Maintaining ethical integrity and privacy protections will be paramount as immersive technologies become more integrated into educational environments.

Evaluation of VR and AR platforms: a critical evaluation of current VR and AR platforms and systems used in STEM contexts is essential. Research should aim to discern which systems align best with diverse educational goals and user needs. Identifying the most effective educational practices and systems will provide invaluable guidance for educators and institutions when selecting and integrating VR and AR technologies into STEM curricula. Comparative studies that evaluate the effectiveness of different platforms and their impact on student outcomes will be particularly beneficial.