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Review

Augmented Reality in Biology Education: A Literature Review

by
Katja Stanič
and
Andreja Špernjak
*
Faculty of Natural Sciences and Mathematics, University of Maribor, 2000 Maribor, Slovenia
*
Author to whom correspondence should be addressed.
Multimodal Technol. Interact. 2025, 9(12), 117; https://doi.org/10.3390/mti9120117
Submission received: 20 August 2025 / Revised: 2 November 2025 / Accepted: 20 November 2025 / Published: 25 November 2025
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Abstract

This systematic review summarises the latest research on the use of augmented reality (AR) in biology education at primary, secondary and tertiary levels. Searching Web of Science, Scopus and Google Scholar, we found 40 empirical studies published up until early 2024. For each study, we analysed biological content, technical features, learning practices and pedagogical impact. AR is most used in human anatomy, particularly in the circulatory and respiratory systems, but also in genetics, cell biology, virology, botany, ecology and molecular processes. Mobile devices dominate as a mediation platform, with marker-based tracking and either commercial apps or self-developed Unity/Vuforia solutions. Almost all studies embed AR in constructivist or inquiry-based pedagogies, and report improved motivation, engagement and conceptual understanding. Nevertheless, reporting on the technical details is inconsistent and the long-term effects are not yet sufficiently researched. AR should therefore be viewed as a pedagogical tool rather than a technological goal that requires careful instructional design and equitable access to ensure meaningful and sustainable learning.

1. Introduction

In recent decades, modern technology has increasingly influenced various aspects of human activity, including education [1]. In the educational context, information and communication technology (ICT) improves access to knowledge and enables the efficiency of learning processes. Its inclusion promotes active, cooperative, collaborative, creative, integrative and evaluative learning and enables the transfer of theoretical content into practice through interactive approaches. ICT also removes geographical limitations as it provides the opportunity to learn remotely and connect people [2]. The integration of modern technological tools into the curriculum contributes to a higher quality of education [3].
One of the technologies that has been increasingly used in education in recent years is Augmented Reality (AR). The term AR first appeared in the 1990s without a clear definition. The most commonly used definition today comes from Ronald Azuma from 1997 [4,5,6,7,8]. He defined AR as a technology that combines a realistic environment with virtual displays [9]. Some authors [5,10,11,12] summarised Azuma’s main characteristics of AR: the combination and coordinated function of virtual and real objects, the inclusion of 3D displays and an interactive user experience. However, a simple QR code that leads to a standalone 3D animation does not quite fulfil the strict definition of AR, which generally requires a real-time adaptation of virtual objects to the physical environment. AR, as part of the mixed reality spectrum, combines real and virtual elements [13]; however, our focus is on its educational applications rather than technical classifications.
AR technology does not replace reality but complements it. In such an environment, users have the feeling that real and virtual objects coexist in the same environment [14]. In an educational context, AR complements rather than replaces reality by enabling learners to explore invisible or complex phenomena in authentic environments, thus bridging abstract concepts with experiential learning. The technology described enables the creation of various digital displays that are of visual, textual or audio origin [11,12,15]. These properties are one of the reasons why AR can be used for different purposes and in different disciplines such as architecture, medicine, the military and sport.
AR has already been integrated into various fields of biology education [16]. Several authors have reviewed the literature in recent years in which researchers link AR technology to the learning or teaching of biology. Permana et al. [17] used a systematic literature review (SLR) to examine 35 studies from the Scopus database published between the years 2015 and 2023. The analysis focused on several aspects, including the year of publication of the article, the type of research method, the forms of AR used in the learning process and the nationality of the authors. The authors found that over the past six years, the number of research papers on AR in the context of biology has tended to increase. Among the studies examined, qualitative research predominates. Permana et al. [17] noted that AR is used in combination with 3D model printing, with some authors of the reviewed articles presenting the use of models of different cell types and explanations of the concepts involved. Several of the studies reviewed wrote about the use of AR applications to support the learning of biology topics, such as the human respiratory system. AR is not only a teaching tool for teachers, but is also used for activities such as presentations, simulations of device performance and object estimations. The main advantage of AR as an educational tool lies in its interactive and immersive features that make it a powerful resource for modern biology education, improving understanding, engagement and retention of complex biological concepts [18,19,20,21].
Azzahra et al. [22] reviewed 23 studies on AR in biology education (2015–2023) and found that most targeted university students rather than teachers or younger learners. Publication numbers have grown since 2015, peaking in 2020, a trend similar to that reported by Permana et al. [17]. Research on AR in biology lessons shows which biological topics are most frequently enriched with this technology. The identified areas of application include human anatomy and organ systems, morphology of living organisms, biochemistry, genetics, biotaxonomy, viruses, cell biology and processes such as photosynthesis, evolution and climate change, while studies on the use of AR in living animals are still scarce. Subran and Mahmud [16], based on a systematic literature review of 29 articles published in four major databases (Scopus, Web of Science, ERIC, OpenAIRE) between 2019 and 2023, reported that AR is most commonly applied in anatomy (43.24%), followed by cytology (18.92%), entomology and physiology (8.11% each), ecology (5.41%) and to a lesser extent biotechnology, virology and taxonomic classification (less than 3% each); three studies did not specify a biological field.
AR has a remarkable impact on biology education by strengthening several aspects of the learning process. It increases students’ self-efficacy and motivation by making abstract and complex concepts more concrete and engaging [20,23]. By overlaying dynamic 3D virtual information with real-world environments, AR enables clearer visualisation of microscopic and abstract biological processes, which deepens understanding and reduces cognitive load [20,24]. AR also supports both independent and collaborative learning; for example, students using an AR-based biology lab application showed a more positive attitude towards self-directed learning and gained a better understanding of lab knowledge through interactive activities [18]. In addition, the technology improves the spatial understanding and retention of anatomical details, which proves particularly valuable in fields that require the development of practical skills, including medical education [21,25,26,27].
To evaluate the effectiveness of AR technology for biology learning, Hallaby and Syahputra [28] examined the literature on AR in relation to biology. The authors searched the Google Scholar database for articles published between 2020 and 2024. Part of the analysis focused on identifying biological concepts that are represented using AR technology. The literature identified an enrichment of biology education at different educational levels. In elementary school, AR technology was used to teach about the digestive tract and the human circulatory system; in middle school, about the human reproductive system; in high school, about arthropods, the life cycle of plants, the sense of hearing and the structure and function of animal and plant tissues; and at the university level, about the concept of the cell. The authors [28] also mentioned a study describing the integration of AR for pre-schoolers using the mentioned technology to teach the names of fruits.
Despite several studies, our aim was to conduct a literature review that examined the intersection of biology education and AR technology to identify potential research that could guide our further research to identify underrepresented topics in the biology curriculum. In contrast to previous reviews that focused primarily on listing journal articles, we examined the digital technology used to implement AR, determined the teaching practice used, and conducted a journal impact factor (IF) assessment to gain insight into the publication landscape of journals in which the relevant articles were published.
While previous systematic reviews [16,17,22] have primarily focused on human anatomy or cell-based biology, our synthesis reveals a notable gap: almost no studies use AR for learning about animals or zoological topics. Although biology is the study of life in all its forms, AR-based learning remains predominantly anthropocentric. The lack of zoological applications represents an overlooked opportunity for educational innovation. Addressing this gap is a key contribution and point of novelty in this review.

2. Methods

This article is a literature review for which we used the Web of Science (WoS), Scopus and Google Scholar databases. A systematic literature review approach was used to choose and evaluate pertinent studies. The process of article search and selection in this review followed the PRISMA [29] guidelines and is represented in Figure 1. While WoS and Scopus allow the application of detailed filtering options such as language or document type, Google Scholar does not offer such functionality. Therefore, records retrieved from Google Scholar were manually screened to exclusion. The selection of keywords regarding AR and the educational context was based previous testing variant combinations of keywords and based on those of other related study [22]. The keywords used for the literature search were combinations of the following terms: “augmented reality” and “biology learning”; “augmented reality” and “biology education”; and “augmented reality” and “biology teacher”.
We cannot match the criteria for the Google Scholar database with the other two databases or represent the research steps equally in the PRISMA flowchart. Figure 1 shows the complete PRISMA flowchart [29]. The search query was conducted in February 2025 using the WoS, Scopus and Google Scholar databases. The query identified 100 documents from WoS and Scopus, and several thousand from Google Scholar. Given the large number of results, we examined the first fifty hits of each combination, using relevance as a sorting criterion. After removing duplicates, 143 documents remained. To further refine the selection, we applied a set of inclusion and exclusion criteria. Only articles published in journals, edited publications, or conference proceedings were considered, as these are peer-reviewed sources that ensure scientific quality. Articles also had to be written in English to allow for accessibility and comparability within the international research community. We limited the publication years to 2017 onwards. The decision to use 2017 as the starting year was based on two previous reviews [17,22] that identified 2017 as the most recent year in which only a single article was published that addressed the link between AR technology and biology education. We did not limit the selection to open access articles; however, the abstracts had to provide sufficient information to evaluate the relevance of the study. Finally, only articles that described the development and testing of AR materials in specific biology topics, or those tested with student groups at different educational levels, were included. Studies that only presented AR applications without empirical testing, or that relied solely on questionnaires, were excluded. Ultimately, 40 articles from the three databases met the criteria and were included in the final review and analysis. As mentioned, only 50 results per keyword combination from Google Scholar were examined. This limitation was chosen because the first results contained numerous review articles and studies that had already been selected from the WoS and/or Scopus databases. By reviewing the number of results compared to WoS alone twice, we ensured comprehensive coverage that also encompassed Scopus records.

Biological Content Indicators

Our review focuses on AR in biology education, so we captured the specific biology content covered (e.g., the human circulatory system, respiratory system, organ systems). These metrics were not used as inclusion or exclusion criteria and are not intended as a measure of study quality; they merely serve to contextualise the prevalence of the various biological subfields represented in our sample within the scientific community. When full texts were unavailable, studies were retained based on detailed abstracts and cross-referenced descriptions from other databases. This ensured comprehensive coverage despite accessibility limitations.
We defined the following research questions (RQ):
RQ1.
Which biological content do teachers at all levels of education supplement with AR technology?
RQ2.
Which types of technical choices (hardware, software, type of AR) did the researchers make when trialling AR in biology lessons?
RQ3.
Which types of teaching practices or pedagogical processes did the researchers use when trialling AR in biology lessons?

3. Results

Recent studies published after January 2023 broaden the landscape of AR use in biology education. Several studies report teacher-centred analyses documenting how lesson design, classroom constraints and teacher decision-making influence AR implementation and learning outcomes. A growing body of work demonstrates the effectiveness of mobile and web-based AR in fully online environments and shows significant increases in student motivation, self-efficacy and engagement beyond traditional classroom environments. Several papers introduce AR to primary school students using concept association tasks that strengthen basic biological understanding and improve learning achievements and attitudes. In terms of content coverage, the literature after January 2023 goes beyond the anatomy focus identified by Subran and Mahmud [16] and adds ecology modules, virology activities targeting higher order cognitive skills and AR-enhanced virtual field tours. Integration with other technologies is also becoming more prominent: some studies describe linking AR with learning management systems or combining it with AI-driven feedback to extend the measured outcomes to critical thinking and digital literacy.
Meta-analytical and large-scale review papers from 2023–2024 further confirm positive effects on learning and motivation, but at the same time emphasise that the effects vary depending on experimental design, intervention duration and task structure. Together, these findings illustrate a shift from merely identifying ‘where’ AR is used to understanding ‘how’ AR is implemented and the pedagogical mechanisms behind its success.
Figure 2 is a diagram in which the citations of the examined literature from three databases are shown. The majority of the reviewed literature was sourced from Google Scholar. 7 articles were identified from all three databases. Scopus has 4 articles in common with the other two databases, while there is no direct overlap only between WoS and Google Scholar. Although some overlap between databases is expected, the mapping in Figure 2 provides transparent documentation of the data sources and demonstrates the reproducibility of the selection process.
Of the 40 reviewed studies, 21 focused on human anatomy and physiology, 8 on plant-related content and 6 on molecular or cellular processes, and only 2 studies (5%) explicitly addressed animals (arthropods or dissection simulations). This imbalance highlights a significant research gap: AR applications in biology education are largely concentrated on humans, while animal-related topics are almost entirely absent. Table 1 provides data on the research papers found and lists the biological content that teachers most often upgrade with AR. Table 1 shows that the most frequently AR-enhanced biological content is the anatomy of organisms.
Most reviewed documents (30) were published in different journals, and others are part of a publication or conference proceedings [35,37,43,49,51,55,60,64,65]. Additional information was collected about the journals, including 2-year JCR and SNIP impact factors (IFs) based on the year of article distribution, as well as the JCR and SNIP quartile data. The Impact Factor (IF) is calculated as the average number of citations received in a particular year by papers published in the journal during the two preceding years (Clarivate Journal Citation Reports). The Source Normalised Impact per Paper (SNIP) accounts for field-specific citation practices and is derived from Scopus data (CWTS Journal Indicators). The data show that more journals provide SNIP metrics than JCR metrics. According to the JCR data, the distribution of journals with IF is evenly distributed across the quartiles, but the majority of journals with SNIP IFs (9 out of 15) are classified in the first quartile. Although citation metrics such as IF and SNIP provide an insight into the visibility of journals, they fluctuate annually and do not capture the pedagogical quality of the studies included. They are therefore provided for descriptive purposes only.

4. Discussion

This updated synthesis of studies published up to early 2024 provides a broader and more balanced view of AR use in biology education. By extending the scope of previous reviews, it integrates pedagogical and technical perspectives and identifies a major research gap: the absence of AR-based content addressing animals or zoological themes. While previous reviews focused mainly on anatomy-related classroom studies up to January 2023, our analysis captures new topics (ecology, virology, virtual tours), new contexts (primary education, outdoor learning, online and blended formats) and crucially, deeper pedagogical insights not previously reported. By highlighting implementation details, teacher roles and integrations with learning management systems or AI tools, we show how AR in biology education is evolving from a novelty visualisation aid to a flexible component of contemporary teaching practice. In the first research question (RQ1), we examined which biological content is most frequently supplemented with AR technology by teachers working at different levels of education. Across the 40 studies analysed, AR is most frequently integrated into the teaching of different fields of organismal anatomy [4,20,43,45,46,48,49,50,53,56,57], with the circulatory system standing out [44,47,52,54,55]. This focus is not surprising, since many internal organ systems, particularly the circulatory system, involve highly abstract processes (e.g., blood flow, oxygen exchange, heart function) that are difficult to visualise with static images in textbooks. AR enables learners to explore these systems dynamically in 3D, and observe processes that are otherwise hidden, thereby supporting spatial understanding.
AR proves to be a valuable tool for visualising structures that are otherwise not visible to the naked eye and making abstract and complex biological concepts easier to understand. This is particularly important for teaching about enzymes [33], macromolecules [30,31], viruses [34,35,36], cells [39,62] and biological processes such as glycolysis [32], digestion and absorption [51], because internal organs and microscopic processes are difficult to visualise with static images, and AR enables learners to explore these systems dynamically in 3D, observe hidden mechanisms and develop strong spatial understanding. Beyond anatomy, AR is also used in botany, especially in teaching about plants [59,60] and their physiological processes [58] and cell structures [41]. In zoology, it enhances the study of arthropods [61] and a notable article example depicts the use of a virtual frog to observe various structures and teach dissection [62]. AR has been used in various fields of biology, generally in teaching genetics [37,38,65], cytology [65], ecosystems and environmental change [64,65] and food biotechnology [6], and it covers different levels of biological organisations, as highlighted in studies by authors [10,23,40,42].
Peterson et al. [31] developed and tested an exercise to improve the understanding of 3D macromolecular structures using AR. In addition to testing the effectiveness of this approach, students completed a survey that revealed that AR technology had an increasing impact on their interest in the knowledge of molecular structure concepts. This is part of the answer to RQ2. A review of 40 articles reveals a clear pattern in the technical choices. When choosing hardware, almost all implementations rely on mobile devices— smartphones or tablets—due to their ubiquity and low cost. Software and content creation solutions range from commercial off-the-shelf apps (Anatomy 4D, The Brain App, Halo AR) to fully customised solutions using Unity, Vuforia, RealityKit, Blender or 3Ds Max. Some combine physical artefacts with AR, such as comic books or an AR-enabled lab coat, demonstrating the creative potential of merging tangible and digital media. Different AR types were used in the research. Most studies use marker-based tracking (QR codes, printed images, textbook markers) to facilitate application and ensure scalability in the classroom. A growing minority use markerless AR or hybrid approaches (e.g., Merge Cube, RealityKit, zSpace) for greater immersion. These details, rarely emphasised in previous reviews, are a prerequisite for replicability and allow other educators to assess the feasibility in their own context. From a technical perspective, marker-based AR remains the dominant approach due to its simplicity and classroom scalability. However, emerging markerless systems, such as the Merge Cube and RealityKit, offer greater interactivity but require more technical resources and teacher training. Comparative evaluations of the pedagogical effectiveness of these tools are still rare and should be prioritised in future studies. Vega Garzón et al. [32] relied on an existing app called Augmented Reality Metabolic Pathways (ARMET), while Arslan et al. [62] developed their own application useful in different biology courses. The development phase was followed by testing with students and professionals and finally the improvement phase based on user feedback. The analysis of the results showed that all students approve of the AR application and justified that it increases their success in biology classes, which is motivating, easily available and easy to use. It also helps users to understand the 3D environment and is useful for experimental work. Finally, the testers suggested other topics and contents that should be prepared with AR. Based on these results, we can recognise the effects on education. Despite the different frameworks, the results are consistent in terms of several positive outcomes. The use of AR improved students’ conceptual understanding. Studies report medium to high learning gains in complex topics [6,17,31,35,40,45,48,50,52,54,56,57,59,61] such as genetics [30,38], molecular biology [30,31,33] and plant physiology [41,42,58]. The authors confirm higher levels of motivation and engagement [10,39,47,51,53,58,60], as almost all interventions describe increased curiosity and enjoyment of learning, with some noting improved self-efficacy and confidence [17,23,34,36,37,41,46,49]. Research-based AR activities promote higher-order skills such as critical thinking, creativity and problem solving, especially when combined with social science topics or collaborative design tasks [4,6,17,31,32,38,40,44,47,50,52,57,59,61]. Finally, authors should not neglect teachers’ professional development by gaining experience with innovative lesson planning and reflective teaching practice. A particularly notable finding of this review is the lack of AR applications focused on animals. Zoological content—including animal anatomy, physiology, behaviour and ecology—is almost entirely absent from the current body of AR research in biology education. This omission limits the disciplinary balance of AR-based learning and presents a valuable opportunity for future development. Expanding AR use to zoological contexts would support a more comprehensive understanding of living systems and foster interdisciplinary links between digital technology and biological diversity.
In order to have a positive impact on education, teachers should choose appropriate learning practices. Safitri et al. [38] investigated the effectiveness of an AR application in improving high school students’ understanding of genetics. The research used a mixed methods approach consisting of a developmental phase and a quasi-experimental phase. In addition to the students participating in the hands-on activities, biology teachers and genetics experts provided feedback during a survey phase. An experimental group received lessons incorporating mobile learning and a control group was taught using traditional methods without AR tools. The results showed that the experimental group significantly outperformed the control group in mastering genetics concepts. The conclusion of the study is that AR learning tools can improve the understanding of genetic concepts and were positively received by the students. Putra et al. [56] reported similar results. The students’ responses showed that the user-friendliness of the application, the clarity of the information presented and the effectiveness of the application in supporting the learning process were perceived positively. Overall, the AR application showed its potential to improve the quality and effectiveness of biology teaching through advanced technology.
Although the use of AR in biology lessons is obvious, our synthesis also highlights risks and reservations. It is necessary to point out the technological distractions where striking visuals can distract from the actual learning objectives and create a novelty effect rather than deeper understanding. There are issues of accessibility and equity, as reliance on personal devices and (un)stable connectivity can widen the achievement gap between students and schools. Pedagogical alignment is crucial, as the use of AR is most effective when it is intentionally linked to curriculum objectives; poorly aligned or overly spectacular applications can obscure key biological concepts. The sustainability aspect raises the issue of developing and maintaining high-quality AR content, which requires time, technical expertise and constant updating, which can overwhelm teachers and institutions. Teachers should therefore treat AR as a pedagogical tool and not as an end in itself. Careful lesson planning, transparent reporting of technical specifications and a focus on engagement are essential to ensure that AR enriches rather than detracts from the core objectives of biology education.
All in all, it is clear that AR is a versatile and powerful addition to traditional biology lessons. It is most effective when integrated into a well-designed, inquiry-based classroom and when researchers provide detailed technical and pedagogical documentation. Future studies should examine long-term learning effects, compare marker-based and markerless approaches and explore how AR can support sustainable, equitable practices in different educational systems.
Almost every study categorises AR in constructivist or research-based pedagogy. The answer to RQ3, which types of teaching practices or pedagogical processes the researchers used when trialling AR in biology lessons, can be found in the following note. Frameworks such as the 5E learning model, problem-based learning, discovery learning and the ARCS motivational model are frequently applied. Teachers use AR to promote student autonomy, collaboration and reflective practice, while some projects show how educators become pedagogical designers by iteratively adapting lessons (e.g., the “Plant Hunt” field study) to integrate AR in a meaningful way and not just use it as an add-on. This consistent linking of AR with active learning emphasises that it is not the technology itself that drives learning, but the pedagogy. Across studies, mobile-based AR dominates due to its accessibility, while markerless and hybrid approaches demonstrate greater engagement potential. Pedagogically, constructivist models predominate, but few studies critically assess long-term learning outcomes. This imbalance highlights the need for more thorough pedagogical evaluation.

5. Conclusions

In conclusion, this review contributes to the existing literature by (1) extending previous analyses with studies published up to early 2024, (2) providing a detailed synthesis of the pedagogical and technical implementation of AR in biology education, and (3) identifying a major research gap—the absence of AR-based materials related to animals. This insight offers new directions for future interdisciplinary research integrating zoological education, AR development and evidence-based pedagogy. AR is increasingly integrated into the biological education system at various levels of education. Our synthesis confirms that AR is most used to teach human anatomy, with the circulatory system standing out, but applications now also extend to genetics, cell biology, virology, botany, ecology and molecular processes, showing a steady expansion of content and pedagogical scope. This review has some limitations, including the relatively small number of keyword combinations used in the literature search, which may have led to the exclusion of some relevant studies. In addition, the use of Google Scholar presented a challenge, as the search cannot be filtered by language, document type or other detailed criteria as in WoS and Scopus, which may have affected the comprehensiveness of the search. In future studies, it may be beneficial to include additional databases to capture a broader range of relevant literature. Another limitation of our study is that we did not limit our search to open access sources, so some potentially relevant information from articles may have been overlooked. After reviewing 40 articles, we found that AR most frequently complements the process of teaching the human anatomy of organisms, with the human circulatory system standing out. Future work could focus on developing teaching materials and designing activities based on biological content. By trialling these materials and involving users, feedback can be gathered on the usefulness of AR. To summarise, it can be said that AR is not a goal in itself, but a pedagogical resource. When carefully aligned with curriculum objectives and sound lesson design, it can increase motivation, deepen conceptual understanding and make abstract biological phenomena tangible while reminding teachers to focus on meaningful learning rather than technological novelty.

Author Contributions

Conceptualisation, K.S. and A.Š.; methodology, K.S. and A.Š.; investigation, K.S.; writing—original draft preparation, K.S.; writing—review and editing, K.S. and A.Š.; visualisation, K.S. and A.Š.; supervision, A.Š.; funding acquisition, A.Š. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ARAugmented reality

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Mti 09 00117 g001
Figure 1. PRISMA flowchart [29].
Figure 1. PRISMA flowchart [29].
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Figure 2. Venn diagram showing the overlap of studies indexed in Web of Science, Scopus, and Google Scholar. Citations within the diagram correspond to works listed in the reference section of this article.
Figure 2. Venn diagram showing the overlap of studies indexed in Web of Science, Scopus, and Google Scholar. Citations within the diagram correspond to works listed in the reference section of this article.
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Table 1. Data from 40 reviewed articles (Biology Area, Educational Level, Learning Practices/Pedagogy and Technical Choices were rewritten from the articles).
Table 1. Data from 40 reviewed articles (Biology Area, Educational Level, Learning Practices/Pedagogy and Technical Choices were rewritten from the articles).
Bio. AreaContent SetEduc. LevelLearning Practices/PedagogyTechnical Choices
(a—Hardware, b—Software, c—AR Type)		Ref.
microbiology, biochemistry and geneticsbiomoleculesUN °Short course with wet-lab + AR dry-lab module; active in
quiry; independent installation on own devices.		(a) Student smartphones (Android and iOS).
(b) Augment app; PyMol for comparison.
(c) Marker-based (printed images/“trackers”).		[30]
macromoleculesActive learning modules in 4 undergraduate courses; worksheets and discussion.(a) Microsoft HoloLens visor.
(b) Holocule app; custom models created with UCSF Chimera + SketchUP.
(c) Immersive visor-based AR.		[31]
glycolysisGame mode and study mode; collaborative and step-by-step pathway construction.(a) Smartphone/tablet (iOS/Android).
(b) ARMET app built with Unity3D + Vuforia; 3D molecules from PDB/ChemSpider.		[32]
enzymesMolecular Case Study (story-based inquiry); active, research-like learning; cross-institutional undergraduate courses.(a) Smartphone/tablet with Merge cubes.
(b) Mol * Viewer for 3D scenes, converted to AR with Merge Object Viewer.
(c) Markerless object viewer.		[33]
virusesUS ***Development study using 4D (Define–Design–Develop–Disseminate) model.
Independent and teacher-guided exploration; students view 3D virus models and complete quizzes.		(a) Android smartphones.
(b) Custom AR app; 3D virus objects built in Blender, interface designed in Adobe Illustrator; voice-over and sound effects added.
(c) Marker-based.		[34]
virusesDevelopment research using ADDIE model (Analysis–Design–Development–Implementation–Evaluation). Focus on improving scientific literacy and retention.(a) Android-based e-module with built-in AR application (no app name given).
(b) AR triggered within e-module to visualise viral structures.		[35]
virusesDiscovery-learning framework: students identify problems, analyse data and test hypotheses while using AR visualisations.(a) Smartphone/tablet for e-module use.
(b) Custom e-module with embedded AR (development via ADDIE model).
(c) Markerless AR integrated inside interactive e-module.		[36]
geneticsInvestigates learning styles (e.g., visual, auditory) and influence on learning performance within an AR setting.(a)/(b) No hardware/software names.
(c) AR learning environment.		[37]
geneticsMixed-method design: app development plus quasi-experimental evaluation; constructivist mobile learning.(a) Smartphone/tablet.
(b) MAR-Gen mobile application.		[38]
cytology and histologycellUN °Inquiry and collaborative learning activities; students design and present cell-biology tasks using AR/VR.(a) Smartphone/tablet for AR; VR headsets for virtual environments.
(b) AR and VR apps (not all names specified).
(c) Mix of marker-based and markerless experiences.		[39]
cell organellesUS ***Research and development using IMSDD model. Independent exploration: students navigate a 3D virtual tour, observing and manipulating organelles.(a) Student smartphones; development on ASUS ROG laptop.
(b) Unity 2021, Blender 3.5, Photoshop, Vuforia.
(c) Markerless 3D virtual-tour AR, objects rotate 360°.		[40]
plant cell structureDescriptive case study with pre-/post-testing. Teacher-guided class sessions where students interacted with AR posters to memorise organelles.(a) Smartphones to scan AR posters.
(b) Custom AR-poster app (details not specified).
(c) Marker-based posters with 3D visualisations.		[41]
structure and function of plant and animal tissueND •Collaborative classroom action research. Discovery learning motivation questionnaires.(a) Smartphones.
(b) Halo AR mobile app.
(c) Marker-based with printed images.		[42]
anatomy and physiology (Animalia)human anatomyUN °Grounded in constructivist learning theory. AR apps to explore anatomical structures, collaborate and discuss findings.(a) Students’ own smartphones/tablets.
(b) Commercial AR apps.
(c) Mobile, markerless (apps overlay 3D anatomical models without printed triggers).		[43]
anatomic structure of human heartFour-stage laboratory procedure: introduction to MAR, AR-assisted lab, dissection of a real heart, reflection session; constructivist approach.(a) Smartphone/tablet.
(b) Mobile AR (MAR) application with marker-based tracking.		[44]
anatomy of the brain, eye, heart and
kidney, and their dissection processes		Mixed research method; apps used in laboratory environment suitable for 5E learning model based on constructivist approach; 7-week application process. Pre-service science teachers performed hands-on AR tasks and dissections.(a) Smartphone/tablet.
(b) Commercial MAR applications (not individually named).
(c) Marker-based activities combined with traditional lab work.		[45]
human neural anatomy and endocrine systemsConstructivist theories of learning anatomical concepts.(a) Tablet/smartphone with cameras.
(b) Commercial AR apps Anatomy 4D and The Brain iExplore; printed AR markers.
(c) Marker-based 3D anatomical visualisations. 		[4]
human organs and organ systemsUS ***12-week online course; constructivist and collaborative learning elements; interviews + quasi-experimental design.(a) Students’ own mobile phones.
(b) Commercial Human Anatomy Atlas + other mobile AR apps.
(c) Mobile markerless/marker mix (noted as “mobile AR”).		[23]
human coordination systemADDIE model; validation sheets, questionnaires, tests. Focus on critical thinking.(a) Smartphone/tablet.
(b) Custom AR viewer linked to printed comic book markers.
(c) Marker-based 3D objects over comic panels.		[46]
human blood circulatory systemSmall-group collaborative simulation sessions aligned with national science standards; inquiry and creativity emphasised.(a) zSpace® system (AR/VR monitor with stylus and 3D glasses providing haptic feedback).
(b) zSpace® Studio and related modules.
(c) Immersive AR/VR.		[47]
human respiratory systemSocioscientific-Issues (SSI) model; students debate social-scientific dilemmas and develop argumentation and critical thinking.(a) Smartphones.
(b) Mobile AR of Respiratory System (MARRS).		[48]
respiratory systemQuasi-experimental post-test-only control group design with 60 high-school students.(a) Smartphone/tablet.
(b) Platform not given.
(c) AR Sinaps learning media.		[49]
nervous systemQuasi-experimental pre/post test; focus on concept mastery (Bloom C1–C4) and digital literacy.(a) Student smartphone.
(b) Custom AR app with printed markers.
(c) Marker-based.		[50]
human digestion and absorptionUS ***ARCS (Attention, Relevance, Confidence, Satisfaction) motivation model. Pre-/post-tests; interviews. Mobile AR application learning vs. traditional methods learning.(a) Android smartphones.
(b) Custom AR app built with Vuforia toolkit and Huawei AR Engine for image/plane/body recognition.
(c) Marker-based AR.		[51]
human blood circulatory systemLS **Structure–Behaviour–Function (SBF) model; quasi-experimental (textbook vs. textbook + AR).(a) Tablets.
(b) Software: Mirage AR app with 2D/3D animations and film.
(c) Marker-based, linked to textbook images.		[52]
nutrition and the human digestive systemPS *, US ***Technology Acceptance Model survey of 188 students to assess ease of use and perceived usefulness.(a) Students’ own smartphones.
(b) Commercial mobile AR apps (specific names not given).		[53]
human blood circulatory systemPS *Inquiry-based lab activity; small-group discussion.(a) Smartphone/tablet.
(b) Mobile AR app for concept-association mapping.
(c) Marker/QR-triggered 3D models.		[54]
human respiratory systemConstructivist approach; pre/post conceptual test.(a) Mobile phones + custom AR app; marker-based.[20]
circulatory systemND •Using Borg and Gall model (first 9 stages). Pilot test.(b) Android application plus a physical lab coat made of cotton with QR-code triggers for each organ.
(c) App renders with QR codes are scanned.		[55]
human anatomyADDIE model. Questionnaires.(a) iOS phone.
(b) X Custom AR app built with RealityKit and 3D assets; developed using ADDIE model.
(c) Markerless interactive 3D simulations.		[56]
human movement systemClassroom implementation with paired t-test for cognitive gains; teacher-guided but interactive exploration of skeleton structures.(a) Smartphone/tablet.
(b) AR Human Skeleton app + Instagram filters.
(c) Marker-based.		[57]
botanyflowering plant physiologyUS ***Quasi experimental design with pre/post tests; using AR vs. using conventional methods. ADDIE model.(a) Mobile devices.
(b) Custom AR module built with Unity, Blippar, PlantAR, Canva and 3Ds Max; QR-code triggers for interactive content.
(c) Marker-based 3D models integrated into lessons.		[58]
plantsQualitative case study of one teacher’s lesson planning and classroom practice; constructivist orientation with emphasis on teacher reflection and adaptive AR use for 10-week period.(a) iPads and students’ smartphones.
(b) Multiple commercial AR apps (e.g., Merge Cube, AR anatomy apps).
(c) Mixed marker-based and markerless activities.		[59]
dicotyledonous plantsND •Qualitative simulation with direct AR use in class. Students worked in groups, scanned AR cards to view 3D plant structures, then discussed observations and completed a Likert-scale questionnaire.(a) Android smartphones.
(b) Augment mobile application.
(c) Marker-based using custom-designed AR cards created in Cinema 4D and uploaded to Augment.		[60]
zoologyarthropodsND •Pre-experimental one-group pre/post design; students used AR book for four class sessions as interactive learning media.(a) Students’ smartphones.
(b) Custom AR book with embedded markers and 3D models.
(c) Marker-based.		[61]
biotechnologyfood biotechnologyUS ***Quasi-experimental pre/post; multimedia learning theory; student attitude surveys.(a) Smartphone/tablet with AR-enabled print book.
(b) Custom AR book integrating 3D objects, audio, video.		[6]
mixedcell, animal anatomical structure, dissection processUN °, US ***Constructivist, inquiry-oriented activities designed to replace cadaver or animal specimens in lab work.(a) Android mobile devices.
(b) Unity3D + ARKit/Vuforia; custom 3D models developed by the authors.		[62]
protists, colonies, mushrooms, plants, animalsUS ***Quasi-experimental pre/post design; constructivist orientation; AR used as supplement to standard curriculum.(a) Android tablets.
(b) Custom AR activities (name not specified).
(c) Marker-based, 3D objects over real images.		[10]
ecosystems, environmental changesProblem-Based Learning (PBL); development research following Lee and Owen model [63](a)/(b) Electronic module with embedded AR (details not specified).[64]
cytology, genetics, ecologyConceptual analysis of blended learning and immersive technology integration; proposes a strategy for implementing AR in a mixed online/offline model.(a)/(b) No specifics named.
(c) Describes immersive AR technologies as part of national digitalisation trends.		[65]
Legend: PS *—primary education; LS **—lower secondary; US ***—upper secondary; UN °—tertiary/university; ND •—not defined; Mol* Viewer is developed as an open-source project and hosted on GitHub [33].
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Stanič, K.; Špernjak, A. Augmented Reality in Biology Education: A Literature Review. Multimodal Technol. Interact. 2025, 9, 117. https://doi.org/10.3390/mti9120117

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Stanič K, Špernjak A. Augmented Reality in Biology Education: A Literature Review. Multimodal Technologies and Interaction. 2025; 9(12):117. https://doi.org/10.3390/mti9120117

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Stanič, Katja, and Andreja Špernjak. 2025. "Augmented Reality in Biology Education: A Literature Review" Multimodal Technologies and Interaction 9, no. 12: 117. https://doi.org/10.3390/mti9120117

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Stanič, K., & Špernjak, A. (2025). Augmented Reality in Biology Education: A Literature Review. Multimodal Technologies and Interaction, 9(12), 117. https://doi.org/10.3390/mti9120117

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