Extended Reality in Applied Sciences Education: A Systematic Review

Abstract

Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) technologies—collectively known as Extended Reality (XR)—have ushered in a new era of immersive and interactive instruction in applied sciences education. This systematic literature review aims to examine the application of XR technologies across various scientific and educational domains, evaluate their impact on learning outcomes, and identify the challenges hindering their broader integration. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a literature search was conducted using Web of Science, ScienceDirect, and IEEE Xplore, focusing on empirical studies published between 1 January 2010 and 1 November 2024, resulting in the inclusion of 56 studies. Among these, 32 studies (53%) employed VR, 25 studies (42%) utilized AR, and 3 studies (5%) adopted MR, with 4 studies exploring the combined application of VR and AR. The findings indicate that VR is primarily applied in higher education settings, such as universities and graduate programs, whereas AR is more prevalent in primary and secondary education; although MR is less frequently used, it exhibits distinct advantages in disciplines requiring high interactivity and realism. Overall, each XR modality can enhance learning motivation, efficiency, and immediate knowledge acquisition in short-term interventions, while long-term implementation may contribute to improved memory retention, increased learner confidence, and sustained engagement. Despite persistent challenges—including high equipment costs, spatial and temporal constraints, small sample sizes, and insufficient longitudinal evidence—these findings underscore the transformative potential of XR technologies in applied sciences education.

1. Introduction

The integration of applied sciences within educational paradigms is fundamentally oriented toward equipping students with the ability to address real-world problems through hands-on practices, thereby enhancing both technical applicability and practical utility [1]. This emphasis on applied sciences education underscores its pivotal role in bridging theoretical knowledge and pragmatic skills, ensuring that learners are not only proficient in academic concepts but also capable of addressing industry-relevant challenges. Applied sciences education fosters critical thinking, creativity, and innovation, as students engage with real-world scenarios requiring interdisciplinary approaches and adaptive problem-solving strategies. Moreover, as technological advancements continue to redefine workplace requirements, the cultivation of these competencies has become increasingly essential in preparing students for future career landscapes characterized by rapid change and technological integration. With the continuous advancement of immersive technologies, Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) have increasingly demonstrated their pedagogical potential in applied sciences, redefining experiential learning through technologically enhanced instructional methodologies [2]. Milgram and Kishino (1994) proposed the Reality–Virtuality Continuum, a conceptual model delineating the spectrum between real and virtual environments [3]. As depicted in Figure 1, AR occupies the leftmost end of the continuum, seamlessly integrating virtual imagery into real-world settings, while VR represents the complete immersion within virtual environments, offering learners a wholly synthetic instructional experience. MR resides at the intersection of these modalities, blending real and virtual spaces to provide highly flexible and interactive user experiences. Collectively referred to as Extended Reality (XR), these technologies augment user engagement and interactivity, thereby broadening their applicability across diverse educational contexts [4].

These three technologies fall under the broader category of Extended Reality (XR) but exhibit significant differences in immersion levels, hardware requirements, and learning contexts. Virtual Reality (VR) provides users with a fully immersive digital environment, typically achieved through head-mounted displays (HMDs) or other sensor-based devices, effectively detaching them from the real world [5]. In educational settings, VR enables the simulation of complex surgical scenarios, allowing students to practice repeatedly in low-risk environments [6]. Augmented Reality (AR) overlays digital information or objects onto the physical environment, enabling users to perceive both real and virtual elements simultaneously, usually via mobile devices such as smartphones or tablets [7]. AR can be used for concretizing abstract concepts, such as molecular structures and chemical reactions, by offering visualizations that enhance comprehension [8]. Mixed Reality (MR) offers a more advanced integration, not only merging virtual and real environments visually but also enabling bidirectional interaction between users and digital objects in physical space [9]. MR supports highly interactive learning scenarios, such as mechanical assembly simulations in engineering disciplines, where students manipulate virtual models to observe their impact on real-world systems [10]. Furthermore, these applications provide an opportunity to customize learning experiences for individual students, accommodating different learning paces and preferences, thereby enhancing inclusivity and accessibility in education.

However, the adoption of different XR technologies is contingent upon their respective hardware and software requirements. VR systems generally require high-performance graphics processing units (GPUs) and enclosed head-mounted devices to deliver a fully immersive experience. While AR offers greater accessibility, its display size and interaction precision are constrained by mobile device capabilities. MR headsets, such as the HoloLens, provide superior immersion and interactivity but come at a significantly higher cost, posing challenges for large-scale educational deployment [9,11,12].

Despite the advancements in XR technologies over the past two decades, their adoption in educational contexts remains uneven. Most research has focused on niche domains such as healthcare, with limited cross-disciplinary integration due to high technological costs, resource constraints, and limited scalability [9,13]. These challenges highlight the need for cost-effective strategies and resource-sharing mechanisms to democratize access to XR technologies in education. To address these gaps, this study undertakes a comprehensive review of the current state of XR applications in applied sciences, with an emphasis on their interdisciplinary utility, learning outcomes, and regional and educational-stage variability. Additionally, the study explores how advancements in XR hardware, such as lightweight headsets and mobile-compatible platforms, can facilitate broader adoption by reducing barriers to entry. The findings aim to inform future curriculum development and pedagogical strategies while fostering a deeper understanding of how XR technologies can bridge theoretical knowledge and practical skills.

Specifically, this study is guided by the following research questions:

• What is the distribution of XR technologies across diverse educational domains, and what key areas of implementation and emerging trends can be identified?
• What technical configurations are adopted across various disciplines, and how do the prevalence and affordances of VR, AR, and MR differ?
• How do XR technologies impact learning outcomes, particularly in terms of effectiveness, adaptability, and their potential to enhance critical thinking, problem-solving, and collaboration skills?
• What limitations and challenges are associated with the integration of XR in applied sciences education, and what actionable recommendations can address these barriers?

By synthesizing evidence from multiple contexts, this study aspires to contribute to the broader discourse on XR technologies as transformative tools in education, ultimately enabling more equitable and effective learning experiences. In doing so, it aims to bridge the gap between technological innovation and pedagogical practice, ensuring that XR applications are not only innovative but also aligned with the evolving needs of educators and learners. This holistic approach underscores the importance of interdisciplinary collaboration, policy support, and ongoing research to maximize the potential of XR technologies in shaping the future of education.

2. Materials and Methods

To better understand the interdisciplinary application and educational impact of XR technologies across applied sciences, this study conducted a comprehensive literature review using the Web of Science (WoS) database. Recognized for its extensive multidisciplinary scope, WoS provides a robust platform for systematic literature analysis, facilitating the exploration of how specific technologies are applied across various academic domains. Mixed Reality (MR), an advanced convergence of Virtual Reality (VR) and Augmented Reality (AR), exemplifies the next phase in immersive technology by offering heightened interactivity and immersion in learning environments. Consequently, this study prioritized MR in its initial search, employing the keywords: (“mixed reality”) AND (“applied sciences” OR “scientific research”) AND (“Education” OR “Learning” OR “Teaching” OR “Instruction”). These keywords were selected to capture the interdisciplinary applications of MR technology, particularly its role in enhancing educational methodologies across the applied sciences. The combination of terms ensures a focus on both the technological and pedagogical dimensions, aligning with the study’s objective to explore the integration of MR in facilitating practical and innovative learning experiences. Preliminary search results indicated a notable increase in research addressing MR applications in applied sciences education starting from 2010. Accordingly, the study defined its temporal scope for literature retrieval as from 1 January 2010 to 1 November 2024 to capture critical advancements in XR technologies within educational contexts.

To ensure a comprehensive and representative dataset, the literature review was extended to include three complementary databases: Web of Science (WoS), ScienceDirect, and IEEE Xplore. WoS was chosen for its extensive multidisciplinary indexing capabilities, ScienceDirect for its rich repository of research in natural and applied sciences, and IEEE Xplore for its specialized focus on engineering and computational sciences. Together, these databases provide a broad and balanced perspective, ensuring the inclusion of diverse and high-quality studies across relevant fields. Acknowledging that XR technologies encompass VR, AR, and MR, the finalized search string included: (“mixed reality” OR “Virtual Reality” OR “Augmented Reality”) AND (“applied sciences” OR “scientific research”) AND (“Education” OR “Learning” OR “Teaching” OR “Instruction”). The search results underwent meticulous screening based on inclusion criteria that prioritized English-language publications while excluding review articles, conference proceedings, studies unrelated to applied sciences education, and works without available abstracts or full texts. All screening and data extraction procedures were independently conducted by two authors and jointly reviewed to ensure consistency in understanding.

To systematically evaluate the retrieved literature, the study adopted the PICOS (Population, Intervention, Comparison, Outcomes, Study design) framework [14]. This framework is widely used in systematic reviews to ensure a structured and comprehensive approach, where “Population” identifies the target group, “Intervention” specifies the focus or treatment being studied, “Comparison” explores alternatives, “Outcomes” highlight the expected results, and “Study design” ensures methodological consistency. Specific screening criteria, detailed in

Table 1. PICOS framework.

Framework	Description	Inclusion	Exclusion
Population	Participants are students spanning all educational levels	Includes students in elementary school, junior high school, senior high school, university, and graduate school or above	Non-student populations or individuals not engaged in educational activities
Intervention	Utilization of XR virtual technologies (VR, AR, MR) for instructional purposes	Includes the use of head-mounted devices, specialized glasses, mobile applications, etc.	Teaching methods that do not incorporate any form of virtual technology
Comparison	Comparison of outcomes before and after XR-based instruction	Includes comparisons of pre- and post-intervention outcomes or comparisons between XR-based instruction and traditional methods (e.g., lectures, face-to-face classroom interaction, printed materials)	Studies that do not include a pre- and post-XR instructional comparison or do not compare XR instruction to traditional teaching methods
Outcome	Effectiveness and acceptance of virtual technologies in applied science education	Involves improvements in learning outcomes (e.g., knowledge mastery, skill enhancement) or acceptance of virtual technologies (e.g., learning satisfaction, technology acceptance)	Studies that do not provide specific assessments of learning outcomes or technology acceptance
Study	Research on the application of virtual technologies in applied science education	English-language publications from 2010 to 2024	Studies unrelated to applied science education or non-research articles (e.g., review articles, meta-analyses)

, were applied to ensure methodological rigor. Moreover, the study employed Abd’s (2018) definition of applied sciences, encompassing disciplines such as applied biology, physics, chemical engineering, artificial intelligence, industrial arts, and business administration—all of which emphasize the practical implementation of theoretical knowledge [15]. Using this definition as a benchmark, the review rigorously filtered and selected literature aligned with the objectives of applied sciences education research. This rigorous approach ensures a robust foundation for subsequent analysis, advancing the understanding of XR technologies’ transformative potential in education. It highlights how these technologies can bridge theoretical learning and practical application, fostering innovation and improving learner engagement across applied sciences disciplines. For each included study, key data items such as publication year, country, XR technology type (VR, AR, MR), educational level, academic discipline, frequency of technology use, observed learning outcomes, and study limitations were extracted and summarized for analysis.

Subsequently, a systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, which are widely recognized for promoting rigor and transparency in systematic reviews. These guidelines provide a standardized framework for data collection and literature screening, ensuring that the review process is both thorough and replicable. A total of 4981 relevant articles were retrieved. The screening process is illustrated in Figure 2’s PRISMA flow diagram, where duplicates (n = 14) and articles lacking full text, non-journal publications, or non-English articles (n = 3142) were excluded, leaving 1825 articles. Titles and abstracts were then reviewed to eliminate articles unrelated to the study’s focus (n = 1548), resulting in 277 articles. The exclusion criteria included studies that did not address educational applications of XR technologies, lacked relevance to applied sciences, or focused on theoretical rather than practical implementations. A full-text review was subsequently conducted, leading to the exclusion of 221 articles that did not align with the study’s objectives. Examples of excluded articles include those that focused on unrelated technological domains, lacked empirical data, or provided only theoretical frameworks without practical educational applications. Ultimately, 56 articles were selected for analysis. The main results extracted from the studies are summarized in

Table A1. Screening results.

Ref.	Year	Country	XR Technology	Education Level	Subject Domain	Frequency of XR Usage	Learning Achievement	Technological Limitations
[59]	2012	Europe	AR	University	Industrial Design and Engineering	2–5 times	Enhanced learning experience/motivation, increased satisfaction, improved learning efficiency	–
[41]	2013	Asia	VR	University	Medical Science and Technology	2–5 times	Enhanced learning experience/motivation, improved knowledge, improved learning efficiency, increased learning confidence	–
[35]	2013	Europe	VR	University, Graduate School	Engineering Education	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, increased participation	High cost, spatial/temporal constraints
[63]	2015	Oceania	AR	University	Medical Science and Technology	1 time	Enhanced learning experience/motivation, improved knowledge	Spatial/temporal constraints
[36]	2017	Europe	VR, AR	University	Architecture and Civil Engineering	Entire semester	Enhanced learning experience/motivation, increased satisfaction	–
[5]	2019	Asia	VR	University	Engineering Education	1 time	Increased participation, increased satisfaction, improved knowledge, enhanced learning experience/motivation	–
[31]	2019	Europe	VR	University	Industrial Design and Engineering	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved memory retention, improved learning efficiency, increased participation	–
[46]	2020	Europe	AR	University	Engineering Education	1 time	Improved learning efficiency, increased satisfaction, improved knowledge, enhanced learning experience/motivation	–
[47]	2020	Europe	AR	Junior High School, Senior High School	Engineering Education	1 time	Increased participation, increased learning confidence, improved knowledge, enhanced learning experience/motivation	–
[7]	2020	Europe	AR	Junior High School	Engineering Mathematics and Applications	2–5 times	Enhanced learning experience/motivation, improved knowledge, improved learning efficiency, increased participation	Spatial/temporal constraints
[56]	2020	Oceania	AR	University, Graduate School	Architecture and Civil Engineering	Entire semester	Enhanced learning experience/motivation, improved learning efficiency	–
[21]	2020	America	VR	University, Graduate School	Engineering Education	1 time	Enhanced learning experience/motivation, increased satisfaction, improved memory retention	–
[60]	2020	Asia	AR	Senior High School, University	Applied Natural Sciences	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency	–
[34]	2020	Europe	VR	University	Medical Science and Technology	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved memory retention, increased participation	–
[39]	2020	Europe	VR	University	Engineering Education	2–5 times	Enhanced learning experience/motivation, improved knowledge, improved learning efficiency	–
[13]	2021	Asia	VR, AR	University	Medical Science and Technology	Entire semester	Improved learning efficiency, improved knowledge, increased satisfaction, enhanced learning experience/motivation	High cost, spatial/temporal constraints
[9]	2021	Europe	MR	University	Medical Science and Technology	1 time	Improved knowledge, enhanced learning experience/motivation	Spatial/temporal constraints
[16]	2021	Asia	VR, AR	Junior High School	Applied Natural Sciences	1 time	Increased satisfaction, enhanced learning experience/motivation, improved knowledge	Spatial/temporal constraints
[18]	2021	America	VR	Graduate School	Architecture and Civil Engineering	Entire semester	Enhanced learning experience/motivation, increased satisfaction	Variations in acceptance
[52]	2021	Asia	AR	Elementary School	Applied Natural Sciences	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency	–
[54]	2021	Middle East	AR	Junior High School	Applied Natural Sciences	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency, increased learning confidence	–
[28]	2021	America	VR	Senior High School	Applied Natural Sciences	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved memory retention, improved learning efficiency, increased participation	Variations in acceptance
[65]	2021	Europe	MR	University	Architecture and Civil Engineering	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, increased participation	–
[37]	2021	Europe	VR	University	Industrial Design and Engineering	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency, increased participation	Variations in acceptance, spatial/temporal constraints
[43]	2021	America	VR	University	Industrial Design and Engineering	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved memory retention, improved learning efficiency	Small sample size, variations in acceptance
[25]	2022	Europe	VR	University	Industrial Design and Engineering	≥6 times (excluding entire semester)	Enhanced learning experience/motivation, improved knowledge, improved learning efficiency	Small sample size
[45]	2022	Africa	AR	University	Medical Science and Technology	1 time	Improved memory retention, increased satisfaction, enhanced learning experience/motivation	–
[17]	2022	Asia	VR	University	Industrial Design and Engineering	Entire semester	Improved learning efficiency, increased satisfaction, improved knowledge, enhanced learning experience/motivation	Variations in acceptance, spatial/temporal constraints
[49]	2022	Asia	AR	University	Medical Science and Technology	≥6 times (excluding entire semester)	Enhanced learning experience/motivation, improved knowledge, improved learning efficiency	–
[57]	2022	Europe	AR	University	Medical Science and Technology	≥6 times (excluding entire semester)	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency, increased learning confidence	Small sample size
[30]	2022	Asia	VR	University	Architecture and Civil Engineering	1 time	Enhanced learning experience/motivation, improved knowledge, improved learning efficiency, increased learning confidence	Spatial/temporal constraints
[44]	2022	Europe	VR	University	Social Sciences	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency	High cost, spatial/temporal constraints
[11]	2023	Asia	VR	Senior High School	Applied Natural Sciences	2–5 times	Improved learning efficiency, increased satisfaction, improved knowledge, enhanced learning experience/motivation	Small sample size, variations in acceptance, high cost
[12]	2023	Middle East	AR	Junior High School	Engineering Education	2–5 times	Enhanced learning experience/motivation, improved knowledge, improved memory retention	Small sample size, high cost
[19]	2023	Asia	VR	University	Medical Science and Technology	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency	Spatial/temporal constraints
[55]	2023	Asia	AR	Senior High School	Applied Natural Sciences	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction	–
[53]	2023	Middle East	AR	Junior High School	Applied Natural Sciences	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency, increased participation	–
[22]	2023	Europe	VR	University	Engineering Education	Entire semester	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, increased learning confidence	Limited battery life
[23]	2023	Europe	VR	Senior High School	Applied Natural Sciences	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved memory retention	–
[24]	2023	Asia	VR	University	Architecture and Civil Engineering	1 time	Improved knowledge, increased satisfaction, improved memory retention	Variations in acceptance, spatial/temporal constraints
[27]	2023	Middle East	VR	University	Applied Natural Sciences	≥6 times (excluding entire semester)	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, increased learning confidence	–
[58]	2023	Asia	AR	Junior High School	Engineering Mathematics and Applications	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, increased participation	–
[29]	2023	Middle East	VR	University	Medical Science and Technology	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency, increased learning confidence	Small sample size
[32]	2023	Middle East	VR	University, Graduate School	Medical Science and Technology	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency, increased learning confidence	–
[38]	2023	Europe	VR, AR	University	Medical Science and Technology	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, increased learning confidence, increased participation	–
[40]	2023	Europe	VR	University	Industrial Design and Engineering	≥6 times (excluding entire semester)	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency, increased learning confidence, increased participation	Small sample size
[50]	2024	Europe	AR	University	Medical Science and Technology	1 time	Improved knowledge, increased satisfaction, improved learning efficiency, increased learning confidence	Small sample size
[48]	2024	Middle East	AR	Graduate School	Medical Science and Technology	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency	Limited battery life, variations in acceptance
[51]	2024	Europe	AR	University	Architecture and Civil Engineering	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency	–
[20]	2024	Asia	VR	Graduate School	Medical Science and Technology	≥6 times (excluding entire semester)	Enhanced learning experience/motivation, improved knowledge, improved learning efficiency, increased participation	Small sample size
[64]	2024	Europe	MR	University, Graduate School	Medical Science and Technology	1 time	Improved knowledge	Small sample size, variations in acceptance
[26]	2024	Europe	VR	University	Marine Science	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction	Small sample size, spatial/temporal constraints
[61]	2024	Asia	AR	University	Medical Science and Technology	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved memory retention, improved learning efficiency	–
[33]	2024	Asia	VR	University	Medical Science and Technology	2–5 times	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved memory retention, improved learning efficiency, increased learning confidence	–
[62]	2024	Europe	AR	Senior High School	Engineering Education	≥6 times (excluding entire semester)	Enhanced learning experience/motivation, improved knowledge, increased satisfaction	Small sample size
[42]	2024	Middle East	VR	University	Medical Science and Technology	1 time	Enhanced learning experience/motivation, improved knowledge, increased satisfaction, improved learning efficiency	–

.

3. Results

The analysis of Figure 3 reveals that among the 56 selected studies, 32 (53%) utilized virtual reality (VR) ([5,11,13,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44]), 25 (42%) employed augmented reality (AR) ([7,12,13,16,36,38,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63]), and 3 (5%) implemented mixed reality (MR) technologies ([9,64,65]). VR, known for its immersive teaching experiences, has been extensively applied in high-presence educational settings such as medical simulations or industrial training. In contrast, AR, which integrates real-world environments with virtual information, has been utilized in courses requiring field observation or hands-on activities, such as engineering and natural sciences. MR, due to its higher technological and equipment requirements, appears to be primarily adopted in advanced courses with significant interactive demands, such as design and architectural simulations. Notably, four studies explored the simultaneous application of VR and AR technologies in educational contexts.

The regional distribution of XR-related research exhibits significant disparities, with varying degrees of emphasis on different types of XR technologies across regions. Europe serves as a major hub for XR research, particularly excelling in studies on VR and AR technologies. The region accounts for 13 studies on VR ([22,23,25,26,31,34,35,36,37,38,39,40,44]) and 10 on AR ([7,36,38,46,47,50,51,57,59,62]), making it the only area that includes MR-related research ([9,64,65]), with a total of three studies. Asia, recognized as a critical region for emerging technological development, contributes 11 studies on VR ([5,11,13,16,17,19,20,24,30,33,41]) and 8 on AR ([13,16,49,52,55,58,60,61]). The Middle East has four studies each on VR ([27,29,32,42]) and AR technologies ([12,48,53,54]). Oceania has only two studies focusing on AR ([56,63]). In contrast, the Americas show relatively limited contributions to XR research, with just four studies on VR ([18,21,28,43]). This trend may be attributed to differences in research focus or data collection criteria, warranting further investigation. Africa has a single study on AR, highlighting the region’s limited resources for advancing educational technologies.

3.1. Application of XR Technologies Across Educational Levels

Based on the literature analysis results, Figure 4 illustrates that in higher education, universities and graduate schools are the primary settings for the application of XR technologies. At the university level, 26 studies (74%) utilized VR ([5,13,17,19,21,22,24,25,26,27,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44]), 14 studies (50%) applied AR ([13,36,38,45,46,49,50,51,56,57,59,60,61,63]), and 3 studies (75%) employed MR ([9,64,65]). At the graduate level, five studies (14%) used VR ([18,20,21,32,35]), two studies (7%) applied AR ([48,56]), and only one study (25%) adopted MR ([64]). Additionally, five studies implemented XR technologies across both university and graduate levels ([21,32,35,56,64]). This concentration in higher education is largely due to the emphasis on integrating theoretical and practical learning in advanced curricula.

The results also indicate that MR, due to its high cost and operational complexity, was not employed at any educational stage below the university level. At the high school level, VR and AR were the dominant technologies, with three studies (9%) using VR ([11,23,28]) and four studies (14%) using AR ([47,55,60,62]). AR was more widely applied in junior high schools and elementary schools, with seven studies (25%) in junior high schools ([7,12,16,47,53,54,58]) and one study (4%) in elementary schools ([52]). Additionally, one study (3%) applied VR in junior high school settings ([16]). AR’s characteristics make it particularly suitable for the educational needs of middle and elementary schools, as it combines virtual information with real-world settings, offering highly interactive and engaging learning experiences.

Although XR technologies are primarily used in higher education, the results reveal a growing trend of adopting emerging technologies at the middle and elementary school levels, enhancing student engagement in learning.

3.2. Integration of XR Technologies Across Scientific and Educational Disciplines

Figure 5 illustrates the application of XR technologies across various scientific and educational disciplines. In the field of medical sciences and technology, particular emphasis is placed on the integration of XR technologies, including medical training simulations and surgical rehearsals. Within this field, MR technology is applied in 2 studies ([9,64]), AR technology in 9 studies ([13,38,45,48,49,50,57,61,63]), and VR technology is the primary technology utilized, appearing in 10 studies ([13,19,20,29,32,33,34,38,41,42]).

In the industrial design and engineering domain, VR technology is employed in six studies ([17,25,31,37,40,43]), while AR technology is used in one study ([59]). In applied natural sciences, AR technology dominates with six studies ([16,52,53,54,55,60]), followed by VR technology with five studies ([11,16,23,27,28]).

In the architecture and civil engineering field, VR technology is applied in four studies ([18,24,30,36]), AR technology in three studies ([36,51,56]), and MR technology in one study ([65]). In engineering education, AR technology is featured in four studies ([12,46,47,62]), and VR technology in five studies ([5,21,22,35,39]). In the field of engineering mathematics, only two studies employ AR technology ([7,58]). Additionally, one study in social sciences ([44]) and one study in marine sciences ([26]) utilize VR technology.

XR technologies are not only widely adopted in medical sciences and technology but are also increasingly used in engineering education and engineering mathematics as assistant teaching resources, reflecting the deep integration of XR technologies across diverse academic disciplines.

3.3. Impact of XR Technology Usage Frequency on Short-Term and Long-Term Learning Outcomes

The results presented in Figure 6 indicate that the integration of XR technologies in teaching leads to a diverse range of learning outcomes. Some studies reported multiple benefits simultaneously, such as increased satisfaction, enhanced learning experience and motivation, and improved subject-specific knowledge, which are key advantages of XR technology applications.

In terms of enhancing learning experience and motivation, VR technology was mentioned in 31 studies ([5,11,13,16,17,18,19,20,21,22,23,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44]), AR technology in 24 studies ([7,12,13,16,36,38,45,46,47,48,49,51,52,53,54,55,56,57,58,59,60,61,62,63]), and MR technology in 2 studies ([9,65]). For improving knowledge acquisition, VR technology was highlighted in 29 studies ([5,11,13,16,17,19,20,22,23,24,25,26,27,28,29,30,31,32,33,34,35,37,38,39,40,41,42,43,44]), AR in 21 studies ([7,12,13,16,38,46,47,48,49,50,51,52,53,54,55,57,58,60,61,62,63]), and MR in 3 studies ([9,64,65]). In studies focusing on increased satisfaction, VR technology appeared in 27 studies ([5,11,13,16,17,18,19,21,22,23,24,26,27,28,29,31,32,33,34,35,36,37,38,40,42,43,44]), AR in 19 studies ([13,16,36,38,45,46,48,50,51,52,53,54,55,57,58,59,60,61,62]), and MR in 1 study ([65]).

A total of 34 studies supported the enhancement of learning efficiency, with 19 studies employing VR technology ([11,13,17,19,20,24,28,29,30,31,32,33,37,39,40,41,42,43,44]) and 15 studies using AR technology ([7,13,46,48,49,50,51,52,53,54,56,57,59,60,61]), demonstrating the significant potential of XR technologies to reduce students’ learning curves. Other learning outcomes included improved learning confidence, reported in 14 studies (9 using VR ([22,27,29,30,32,33,38,40,41]) and 5 using AR ([38,47,50,54,57])), and enhanced course engagement, also in 14 studies (9 using VR ([5,20,28,31,34,35,37,38,40]), 5 using AR ([7,38,47,53,58]), and 1 using MR ([65])). Lastly, memory retention was addressed in eight studies using VR ([21,23,24,28,31,33,34,43]) and three using AR ([12,45,61]). Although these learning outcomes were mentioned in a relatively smaller proportion of studies, they still highlight the multifaceted potential of XR technologies in education.

Although most studies confirm that XR technologies enhance various aspects of learning outcomes, an in-depth exploration of learning outcomes should incorporate the critical factor of learning duration. Current literature primarily examines learning outcomes through a cross-sectional lens. This study adopts a longitudinal perspective to analyze the impact of learning duration on learning outcomes when XR technologies are integrated into teaching. The findings indicate that most collected studies focus on the outcomes of single-use interventions, with 22 studies reporting single-use applications ([5,9,16,19,21,24,26,29,30,32,42,45,46,47,48,50,51,52,55,60,63,64]), 14 studies involving 2–5 uses ([7,11,12,23,33,37,38,39,41,53,54,58,59,61]), 7 studies reporting 6 or more uses (excluding an entire semester) ([20,25,27,40,49,57,62]), and 13 studies conducting experiments over an entire semester ([13,17,18,22,28,31,34,35,36,43,44,56,65]), as illustrated in Figure 7. The data reveal that short-term interventions with emerging technologies dominate, while discussions on the effects of long-term implementations are relatively limited. Subsequently, this study further analyzes the influence of learning duration on learning outcomes across these studies.

Short-term learning outcomes refer to the immediate results achieved following the initial application of XR technologies. XR technologies enable learners to accomplish learning objectives more efficiently and accurately within a short period, thereby enhancing learning efficiency. Additionally, the immersive learning process fosters greater sensory and emotional engagement, encouraging learners to focus more attentively. These positive experiences further influence overall satisfaction with course design, ultimately promoting the short-term acquisition and understanding of knowledge. In contrast, long-term learning outcomes are the cumulative results achieved through sustained application of XR technologies over an extended period. Continuous use of these technologies enhances learner engagement and increases behavioral involvement in courses, such as task completion rates and interaction frequency. Through repeated successful learning experiences, learners gradually develop a stronger sense of self-efficacy and demonstrate greater confidence in practical applications. Moreover, these long-term learning outcomes are reflected in improved memory retention, as the immersive nature of XR technologies helps learners consolidate knowledge more effectively and maintain subject matter retention over time.

According to Figure 8, the relationship between learning outcomes and the frequency of XR technology usage reveals three main patterns (Cases A, B, and C).

• Case A: short-term learning outcomes

The short-term learning outcomes are more pronounced when XR technologies are used only once (lower section of Figure 8). For instance, improved knowledge in 20 studies ([5,9,16,19,24,26,29,30,32,42,46,47,48,50,51,52,55,60,63,64]), enhanced learning experience/motivation was mentioned in 19 studies ([5,9,16,19,21,26,29,30,32,42,45,46,47,48,51,52,55,60,63]) and increased satisfaction was reported in 17 studies ([5,16,19,21,24,26,29,32,42,45,46,48,50,51,52,55,60]), while learning efficiency was highlighted in 11 studies ([19,29,30,32,42,46,48,50,51,52,60]). When the usage frequency increased to 2–5 times, enhanced learning experience/motivation was mentioned in 14 studies ([7,11,12,23,33,37,38,39,41,53,54,58,59,61]), improved knowledge in 13 studies ([7,11,12,23,33,37,38,39,41,53,54,58,61]), learning efficiency in 10 studies, and increased satisfaction in 10 studies ([11,23,33,37,38,53,54,58,59,61]). For usage beyond six times but less than an entire semester, enhanced learning experience/motivation was mentioned in seven studies ([20,25,27,40,49,57,62]), improved knowledge was noted in seven studies ([20,25,27,40,49,57,62]), learning efficiency in five studies ([20,25,40,49,57]), and increased satisfaction in four studies ([27,40,57,62]). Finally, in cases of continuous application throughout an entire semester, enhanced learning experience/motivation was mentioned in 13 studies ([13,17,18,22,28,31,34,35,36,43,44,56,65]), increased satisfaction was mentioned in 12 studies ([13,17,18,22,28,31,34,35,36,43,44,65]), learning efficiency was noted in 7 studies ([13,17,28,31,43,44,56]), and improved knowledge in 10 studies ([13,17,22,28,31,34,35,43,44,65]). These findings suggest that the use of XR technologies during mid-term phases may face challenges such as “loss of novelty” or “insufficient alignment with instructional models”, which could lead to underrepresentation in research.

However, the upper section of Figure 8, although reflecting fewer studies overall, reveals distinct trends in how the duration of XR technology intervention influences both long-term and short-term learning outcomes, highlighting two additional patterns related to extended XR usage:

• Case B: positive or sustained long-term outcomes

A subset of longer-term interventions reported continued improvements in participation, memory retention, and learning confidence. When the usage frequency increased to 2–5 times, participation was highlighted in five studies ([7,37,38,53,58]), while memory retention ([12,23,33,61]) and learning confidence ([33,38,41,54]) were mentioned in four studies each. Similarly, during semester-long applications, five studies reported increased participation ([28,31,34,35,65]), four studies noted improvements in memory retention ([28,31,34,43]), while learning confidence was documented in only one study ([22]).

• Case C: inconclusive or diminishing long-term outcomes

Not all studies on extended XR usage demonstrated consistent learning gains. For instance, when XR technologies were applied more than six times but for less than an entire semester, participation ([20,40]) and learning confidence ([27,40,57]) were mentioned in only two and three studies, respectively, with no studies reporting improvements in memory retention. Moreover, even among semester-long interventions, only a small number of studies reported significant effects—five studies documented increased participation ([28,31,34,35,65]), four studies addressed improved memory retention ([28,31,34,43]), and one study noted enhanced learning confidence ([22]). These findings indicate that while prolonged XR usage may support certain long-term benefits, it does not necessarily enhance all learning outcomes uniformly.

The results suggest that Case A is well-supported by numerous short-term studies, highlighting XR’s ability to enhance immediate engagement and motivation. However, Cases B and C demonstrate that the long-term impact of XR is less frequently examined and can yield mixed findings. This underscores the need for additional longitudinal research, as long-term learning outcomes may be influenced by other limiting factors.

3.4. Challenges and Limitations in the Educational Application of XR Technologies

Figure 9 illustrates the various limitations associated with the application of XR technologies in the educational domain. While some studies did not explicitly address these constraints, others highlighted multiple dimensions of challenges. The most commonly reported limitations are spatial and temporal constraints, with VR accounting for 10 studies ([13,16,17,19,24,26,30,35,37,44]), AR for 4 studies ([7,13,16,63]), and MR for 1 study ([9]).

The second most frequently mentioned limitation is small sample size, noted in 12 studies, including 7 that employed VR ([11,20,25,27,29,40,43]), 4 using AR ([12,50,57,62]), and 1 utilizing MR ([64]). Variations in student acceptance were highlighted in 9 studies, with 7 studies on VR ([11,17,18,24,28,37,43]) reporting issues such as dizziness or discomfort when using head-mounted devices, while AR ([48]) and MR ([64]) were each mentioned in one study.

The high cost of XR technologies was primarily associated with VR, discussed in four studies ([11,13,35,44]), with AR mentioned in one study ([12]). Finally, limited battery life was cited in two studies, one involving VR ([22]) and the other AR ([48]). This issue can impact extended class durations or experiments requiring continuous operation, as battery depletion or device overheating may force interruptions in educational activities.

4. Discussion

4.1. Phase-Based XR Technology Applications in Applied Sciences Education: Implications and Strategic Recommendations

To answer RQ1, our findings indicate that the distribution of XR applications varies significantly across educational levels (Figure 4). Higher education emerges as the core setting for XR technology application, largely due to the abstract and complex nature of teaching objectives in this domain. The immersive features of VR and MR technologies make them particularly well-suited for simulating highly complex scenarios, thereby fostering a deeper understanding of abstract theories and enhancing practical skills. Cabero-Almenara et al. (2021) noted that VR and AR technologies are well-suited for medical education, such as surgical simulations, which not only improve students’ clinical responsiveness but also enhance safety [65]. Specifically, MR technologies have been applied in medical and architectural fields, assisting in high-risk tasks like suturing techniques and internal body anatomy learning [9,64]. In architecture, MR enhances precision in measurements such as distance, offering a highly immersive learning environment [65]. Additionally, researchers increasingly prefer combining multiple technologies, integrating VR and AR to evaluate their potential in enhancing educational outcomes [13,16,36,38].

In high school education, AR is more prominently applied compared to VR, likely due to the inclusion of complex and abstract scientific concepts in high school curricula, such as atomic structures and molecular models in chemistry [60]. AR allows students to intuitively understand these abstract concepts while maintaining interactivity, further enhancing engagement and learning outcomes [27]. AR also improves safety in chemistry experiments by simulating reactions involving corrosive, flammable, or explosive materials, thereby reducing risks and reliance on experimental equipment—an important solution for resource-limited schools [60]. In contrast, the adoption of VR in secondary and elementary education remains limited due to its higher hardware requirements and costs. AR, on the other hand, is more cost-effective as it can be operated through students’ smartphones or tablets, integrating seamlessly with the real world to enhance the practicality of learning content [27].

In primary and secondary education, the extensive use of AR technologies highlights their advantages in foundational education. Due to their ease of operation and relatively low hardware requirements, AR technologies provide practical and innovative teaching solutions for resource-constrained primary and secondary schools. At the junior high level, where students require concrete representations of learning content, the visualization and interactivity of AR make it an ideal choice [66]. Furthermore, research has shown that AR not only significantly enhances student engagement but also effectively cultivates problem-solving skills and critical thinking, injecting new vitality and possibilities into foundational education.

In addition to examining the phase-based distribution of XR technologies, we also analyzed the authors’ keywords from our selected articles to identify emerging topics. Figure 10 presents a word cloud generated from all extracted keywords across the reviewed studies, offering a visual representation of research trends and highlighting frequently occurring terms. Given the diverse range of keywords associated with each article,

Table A2. Summary of keywords in XR technologies research.

Keyword	Ref.
virtual reality	[5,7,9,11,13,17,21,22,24,26,27,28,30,31,32,37,39,41,42,53,54,55,60,61]
augmented reality	[12,13,16,18,19,30,45,47,48,49,51,52,53,56,58,64]
e-learning	[21,53,56]
gamification	[25,36,61]
ICT	[25,60,65]
learning effectiveness	[11,19,36]
simulation	[27,56,60]
3D animation	[25,60]
active learning	[20,45]
education	[13,39]
endodontics	[7,27]
higher education	[26,32]
learning motivation	[11,19]
mixed reality	[9,23]
perceived ease of use	[24,34]
questionnaire survey	[16,57]
science education	[26,51]
simulation training	[49,54]
STEM education	[20,37]

includes only keywords that appeared in more than one study (with a frequency greater than one).

Table A2 summarizes the most frequently occurring keywords, while Figure 10 presents a word cloud illustrating their relative prominence. “Virtual reality” (24 mentions) and “augmented reality” (16 mentions) remain the most common terms, reflecting the established focus on these two XR modalities. Meanwhile, keywords such as “e-learning”, “gamification”, and “simulation” suggest a growing interest in interactive and digitally integrated teaching methods. Less frequent but noteworthy terms, such as “mixed reality”, “learning motivation”, and “learning effectiveness”, indicate potential directions for further investigation, including the design of immersive MR scenarios and the assessment of XR’s impact on learner engagement. Although “mixed reality” appears fewer times than VR and AR, its presence implies a gradual shift toward more advanced XR setups that combine real-time spatial mapping and virtual content. Additionally, terms like “ICT”, “3D animation”, and “stem education” signal broader trends in digital pedagogy and subject-specific applications. Collectively, these emerging keywords underscore the evolving landscape of XR research, pointing to future expansions in multi-user environments, gamified approaches, and data-informed evaluations of learning outcomes.

To further promote the application of XR technologies in education, institutions can adopt the following strategies:

• Develop Professional Development Programs: provide specialized training courses for teachers on XR technologies to support their use of innovative teaching methods in the classroom, thereby improving learning outcomes.
• Establish Comprehensive Support Systems: develop XR teaching guides and implementation manuals for educational applications, offering technical consultations and training to reduce the technical barriers faced by schools in adopting XR technologies.
• Encourage Public–Private Partnerships: foster collaborations between governments and industries to provide schools with necessary funding and equipment, particularly in foundational education, ensuring that technology costs do not become a barrier for institutions.
• Deepen Interdisciplinary Integration: incorporate XR technologies into curriculum design to promote interdisciplinary learning and innovation, with a focus on integrating STEM and humanities subjects.
• Conduct Long-Term Impact Assessments: undertake systematic empirical studies to analyze the long-term effects of XR technologies on student performance, engagement, and critical thinking development, providing evidence for educational policy and practice.

It is worth noting that the limited use of MR technologies in primary and secondary education may stem from their higher hardware costs and implementation thresholds. However, as the technology continues to mature and become more accessible, MR could potentially gain traction in foundational education. Incorporating more interdisciplinary and immersive learning scenarios in curriculum design could bring new possibilities to primary and secondary education. Additionally, collaborations between schools and industries may help reduce implementation costs, paving the way for MR technologies to be integrated into foundational education.

4.2. Domain-Specific XR Applications in Applied Sciences Education: Distribution Patterns and Pedagogical Implications

This study reveals that XR technologies have been applied across diverse academic disciplines, with the most extensive usage observed in the field of medical sciences and technology. VR technology stands out as the primary tool in this domain due to its immersive learning advantages, which effectively enhance knowledge retention and professional skill development. By simulating complex and high-risk medical procedures, VR provides a safe practice environment, significantly reducing the need for physical materials. It also allows students to improve their practical skills and operational precision through repeated practice, ultimately boosting their confidence [13,33].

In industrial design and engineering, VR technology is particularly prominent, as this field emphasizes creative product design and functional development processes, including structural assembly, aesthetic design, and functional testing. VR enables students to interact with 3D models and visualize complex structures, thereby improving spatial understanding and practical skills [40]. Conversely, in applied natural sciences, AR technology is favored for its ability to overlay virtual elements onto real-world environments, making abstract concepts, such as chemical structures, more tangible. It also simulates experimental scenarios, enhancing safety and helping students intuitively understand scientific principles [28].

Engineering education focuses on applying theoretical knowledge to practical operations, requiring the integration of real-world scenarios to deepen understanding of abstract concepts. For example, AR technology can simulate chemical reactions to help students better grasp theoretical knowledge, whereas the high hardware demands of VR result in relatively lower adoption rates. AR’s ease of integration into courses and instructional materials makes it a more practical choice. In architecture and civil engineering, AR combines simulation modeling with real-world scenarios, aiding students in spatial planning and structural design. MR technology is also used in this field for immersive modeling of complex structures, enriching the learning experience [22].

In engineering mathematics and applications, AR facilitates students’ understanding of geometric concepts and enhances their ability to visualize real-world spaces [7]. In social sciences, VR technology simulates historical scenarios, enabling students to deeply comprehend social and cultural contexts through immersive learning [44]. In the marine sciences, VR allows for the simulation of ship engine room operations and marine ecosystems, providing students with opportunities to learn diagnostic and repair techniques in environments otherwise difficult to access [26].

Despite XR technologies’ demonstrated potential across disciplines, challenges remain. The high software development costs and equipment requirements of VR and MR technologies hinder their large-scale implementation in primary and secondary education. In contrast, AR technology, with its lower costs and ease of operation, is better suited to meet the practical needs of foundational education, making it more widely adopted in this context.

To answer RQ2, our findings indicate that the choice of XR modality is highly discipline-specific, with VR predominantly used for high-risk simulations, AR for conceptual visualization, and MR for hybrid physical–virtual interactions. VR technology is often adopted in fields where hands-on practice involves significant risk or resource constraints—such as medical sciences or industrial design—because it provides a fully virtual environment that allows repeated training without real-world hazards [5]. In contrast, AR technology is better suited for disciplines that benefit from concretizing abstract concepts and integrating real-world scenarios, such as applied natural sciences and engineering education, where theoretical knowledge can be superimposed onto physical objects to enhance students’ understanding [7]. Meanwhile, MR combines these advantages by enabling real-time interaction with virtual elements in physical space, making it especially useful for assembly tasks in engineering or architecture, where learners can manipulate digital components as if they were physically present [10]. Consequently, XR modality aligns with distinct pedagogical aims. VR for immersive and often risk-intensive simulations, AR for bridging theory and practice through overlays, and MR for highly interactive, mixed-environment learning experiences.

Future research could enhance XR experiences by incorporating greater interactivity and engagement, rather than primarily converting existing educational materials into static 3D digital content. For example, VR and MR technologies could be utilized to create immersive virtual laboratories where students actively test hypotheses, validate theoretical concepts, and explore subject matter in real time. These environments could integrate dynamic simulations and personalized feedback mechanisms features that foster deeper engagement and adaptability to individual learning needs [67,68,69]. By enriching interactivity and responsiveness, such approaches may not only enhance student immersion but also contribute to more meaningful and sustained learning outcomes. Additionally, interdisciplinary collaboration will be a critical driver for advancing XR technology. Educational researchers, technology developers, and subject matter experts must work together to create XR solutions tailored to disciplinary needs. By fostering cross-disciplinary integration, XR technologies can unlock their full potential in education, deepen students’ understanding of subject knowledge, and cultivate higher-order thinking skills such as problem-solving and critical thinking, essential for tackling future challenges.

4.3. Evaluating Short-Term Gains and Long-Term Retention: XR Technologies’ Impact on Learning Outcomes

The results presented in Figure 6 demonstrate that the application of XR technologies in education significantly enhances various dimensions of learning outcomes. The immersive and interactive features of XR technologies effectively engage students, increasing their focus and motivation. XR technologies can simulate realistic or complex experimental environments, helping students intuitively understand abstract concepts such as surgical procedures, chemical experiment processes, or engineering design operations. This enhances knowledge acquisition and practical skills, further optimizing the overall learning experience [46,49].

Moreover, the use of XR technologies reduces learning frustration and boosts students’ confidence [24]. Immersive learning environments allow students to practice and perform tasks repeatedly in a safe virtual space, avoiding the risks or high costs of real-world operations. For example, in applied natural sciences, VR technology facilitates the learning and application of rare metal materials, reducing experimental time and equipment costs while improving students’ operational proficiency and learning efficiency [5]. These applications also significantly improve course engagement and learning satisfaction, particularly in skill-based training courses and complex applied sciences disciplines. XR technologies effectively reduce cognitive load, enabling students to achieve learning objectives more efficiently [48].

The study also highlights the potential of MR technologies to enhance students’ knowledge acquisition and learning experience, while simultaneously boosting confidence and promoting self-directed learning. MR, as a mixed reality technology, combines real-world interactivity with the immersion of virtual content, creating opportunities for students to engage in autonomous learning [65].

The study reveals distinct differences between the short-term and long-term learning outcomes of XR technologies. Short-term outcomes, such as learning efficiency, satisfaction, and knowledge acquisition, often manifest after single or limited use. Among the reviewed literature, 41% involved single-session experimental courses, indicating that most studies focus on short-term effects. Students often find the immersive and interactive features of XR technologies highly engaging during initial use, which enhances motivation and focus compared to traditional teaching methods. In disciplines like chemistry, where experimental processes may involve long wait times or safety risks, XR technologies simulate experimental environments, reducing risks and wait times while improving learning efficiency and hands-on experiences [11,24,52].

However, as noted by Sprenger and Schwaninger (2021), the acceptance of VR technology may decline with repeated use, potentially due to initially high expectations and relatively simple instructional designs, which can negatively impact learning experiences and motivation [37]. Other studies suggest that the novelty of XR technologies may initially enhance the sense of presence, but this effect diminishes over time, especially if instructional content lacks adaptability, leading to reduced learning outcomes in mid-term applications [70]. These findings align with the results of this study. In contrast, long-term outcomes, such as increased participation, learning confidence, and memory retention, require sustained use or repeated applications to gradually emerge. Previous studies employing a gradual integration of XR technologies into curriculum design have demonstrated that step-by-step guidance helps students systematically construct knowledge structures. This approach prevents students from relying solely on rote memorization, instead fostering deeper engagement with course content [19,21]. In scenarios involving semester-long or high-frequency applications, students achieve greater absorption of learning content and maintain consistent course engagement. For instance, some studies have designed XR materials for at-home use, which encourages continuous learning motivation and promotes autonomous learning behaviors [12].

Regarding memory retention, delayed assessments have confirmed the long-term memory effects of XR technologies. While memory of theoretical knowledge may decline over time, the memory and application of practical skills tend to remain stable [24,30]. It is therefore recommended to use XR technologies as supplementary learning tools, combined with traditional teaching methods, to provide opportunities for repeated practice and reinforce students’ memory and understanding of theoretical knowledge.

To answer RQ3, this study finds that XR technologies significantly enhance learning effectiveness, particularly in terms of motivation, engagement, and skill acquisition; however, most effects are concentrated in short-term experiments, with their long-term impacts requiring further investigation. Future research should focus on designing studies that span entire semesters or involve repeated applications, allowing for a systematic exploration of the sustained effects of XR technologies. Additionally, our review highlights a notable gap in discussions on the development of collaboration skills. A primary limitation is XR devices are designed for individual use, lacking built-in multi-user interaction capabilities, which restricts opportunities for collaborative engagement. Future research should explore the development of multi-user XR environments and more advanced connectivity solutions, allowing learners to interact and collaborate seamlessly within shared virtual or mixed reality spaces, thereby enhancing teamwork and cooperative problem-solving in immersive learning environments.

4.4. Core Challenges and Sustainable Implementation Strategies for XR Technologies in Applied Sciences Education

This study systematically examines the core challenges faced by the application of XR technologies in education, including spatial requirements, development costs, insufficient sample sizes, variability in student acceptance, high procurement and maintenance costs for equipment, and limitations in battery life. These factors not only significantly hinder the widespread adoption of XR technologies but also pose severe challenges to their sustainability in educational practice.

XR technologies often require specific facilities and dedicated equipment for operation. Curriculum design must account for adequate operating space and equipment stability; unlike traditional computer-based learning tools, XR applications (particularly VR and MR) often necessitate open, unobstructed environments to ensure safety and functionality. For instance, VR simulations require sufficient movement space to prevent physical collisions, while MR-based applications may need specialized classrooms with minimal environmental interference to ensure seamless interaction between digital and physical elements [9]. In practical applications, institutions with limited classroom space may struggle to integrate XR-based activities into their curriculum, leading to underutilization of the technology despite its potential educational benefits. For example, many VR systems operate within a predefined spatial tracking range, restricting students’ movement and sometimes causing mismatches between their real-world motion and the virtual environment. Thus, further limiting their mobility and potentially diminishing the immersive experience [24].

The development of XR instructional materials involves significant time investment, particularly in designing 3D models, developing interactive content, and conducting usability testing. Unlike conventional digital learning resources, XR content often requires customized development, highlighting the high resource dependency of XR applications [24,44]. This challenge is further exacerbated for educators without programming expertise, as many XR development tools still require substantial scripting and technical customization [71]. As a result, teachers unfamiliar with these technical aspects may find the development process overly complex and time-consuming, creating an additional barrier to the widespread adoption of XR-based instruction, which extends development timelines.

Moreover, the insufficient sample sizes reported in many studies are often attributed to the high costs associated with XR technologies. A review of the literature indicates that studies with smaller sample sizes typically involve 15 to 40 participants [20,25,26,57], primarily due to the financial constraints imposed by these technologies. For instance, VR and MR applications frequently require expensive head-mounted displays, which significantly limit the purchasing capacity of educational institutions and hinder the widespread adoption of these tools [13]. Furthermore, many XR applications rely on high-performance hardware and computational resources, further exacerbating financial barriers. Advanced MR devices, such as the HoloLens 2, represent a substantial investment, making large-scale implementation impractical in many educational and research settings. As a result, many studies are constrained to small, convenience-based samples, which in turn limits the generalizability of their findings [67].

Student acceptance of XR technologies varies significantly. Some students experience discomfort, such as dizziness or visual fatigue, caused by head-mounted devices, which negatively affects their learning outcomes [18,22]. Additionally, the steep learning curve of emerging technologies can deter some students, who may find the complexity of operation or lack of interest a barrier to engagement [28,32]. To improve student acceptance, future research should focus on developing progressive instructional models that help students gradually adapt to XR technologies. Identifying the optimal integration points between technology and learning objectives is also critical. Furthermore, incorporating student feedback to refine the teaching process and designing learning activities grounded in real-world scenarios can enhance the appeal and engagement of these technologies.

Teachers’ acceptance and readiness play a critical role in the effective educational application of XR technologies. Studies indicate that many K-12 teachers feel unprepared to incorporate XR into their classrooms due to unfamiliarity with the technology, a lack of relevant training and resources, and concerns over operational complexity and classroom management challenges [53]. This resistance to technology integration presents a significant barrier to the promotion of XR technologies. Future research should prioritize the development of professional development programs and continuous training to enhance teachers’ familiarity with and ability to use XR technologies. Tailored instructional strategies should be designed to suit the needs of various disciplines.

The limited battery life of XR devices is an underexplored yet impactful challenge. In extended classroom teaching or continuous operational environments, insufficient battery capacity can interrupt teaching processes, disrupting the continuity of the learning experience [22,48]. This issue poses a significant limitation, particularly in high-energy-demand XR scenarios, affecting teaching schedules and student engagement. Additionally, the performance degradation of devices over frequent use and the challenges of hardware maintenance further add to the concerns of educational institutions when adopting these technologies.

To answer RQ4, these challenges have led most existing studies to focus on one-time applications of XR technologies, with limited exploration of their long-term potential. Future research should propose specific strategies to overcome these challenges, such as improving the portability of devices, enhancing the design of head-mounted equipment to reduce user discomfort, and leveraging technological innovations to lower costs. Furthermore, XR application models tailored to educational needs should be developed to effectively improve learning outcomes and promote broader adoption and sustainable development of these technologies in education.

Policymakers should also consider providing additional funding and support to reduce the barriers for educational institutions in adopting XR technologies. By aligning technological, pedagogical, and policy advancements, XR technologies hold the potential to significantly expand their impact and applicability in the educational domain, fostering deeper learning and long-term sustainability.

5. Conclusions

This systematic review demonstrates that Extended Reality (XR) technologies—encompassing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)—are increasingly integrated into applied sciences education, with VR showing the highest adoption rate across diverse regions and AR gaining traction at middle and elementary school levels. These technologies support hands-on and immersive learning experiences, as evidenced by enhancements in knowledge acquisition, motivation, satisfaction, and learner engagement. While short-term usage of XR appears to promote immediate gains in learning efficiency and motivation, more sustained implementations are associated with broader outcomes such as deeper subject retention, increased participation, and greater self-efficacy. Nevertheless, practical constraints persist. High equipment costs—particularly for MR—limited space for safe and sustained usage, and the potential for learner discomfort in prolonged sessions can hinder broader adoption. Additionally, research in this domain often relies on small sample sizes, raising questions about generalizability, and few studies conduct longitudinal examinations of XR’s impact on learning beyond single or short-term interventions.

With rapid technological progress, particularly the growing attention on artificial intelligence (AI), there is considerable potential to advance XR applications. AI-driven tools can support real-time data analysis, adaptive learning pathways, and intelligent tutoring systems, thereby making XR environments more personalized and responsive to learners’ needs. By integrating AI, future XR solutions could address existing limitations, such as limited user feedback and scalability, while opening avenues for enhanced collaboration and more meaningful, data-informed learning experiences in applied sciences.

Future inquiries should therefore strive to address these limitations by exploring cost-effective solutions, validating user comfort over sustained usage, employing more robust research designs, and examining longer-term applications in diverse educational contexts. Such efforts will provide a clearer understanding of how best to harness XR’s potential to foster interactive, meaningful, and enduring learning experiences in applied sciences.