Submitted:
22 June 2023
Posted:
23 June 2023
You are already at the latest version
Abstract
Keywords:
1. Introduction
- RQ1: What types of applications (in the context of technology) are the most popular / used? What is the core AR technology? What external devices are used? What senses are stimulated?
- RQ2: In which areas of education does AR technology have the highest demand / is the most popular? Why? Which of them are at the most advanced stage of development / are already in use?
- RQ3: What kind of validation methods are used in testing AR educational applications?
- RQ4: Has the current world situation (COVID-19) influenced in any way AR in education?
2. Background
2.1. Augmented Reality
2.2. AR definitions and concepts
- Combines real and virtual.
- Interactive in real-time.
- Registered in 3-D.
2.3. The precursors of AR
3. Methodology
- the content of the paper should be relevant to preschool, primary, secondary, or higher education;
- the paper must present at least the preliminary version of an AR tool (no sketches, drafts, and paradigms);
- the tool described in the paper should be applied to learning or at least tested among students and/or educators;
- the paper should report the effect of the provided tool;
- the full paper should be freely accessible.
- Simple publication details such as title, authors, year etc.
- What are the most frequently used keywords in the AR articles?
- Which sub-branch of education are the AR studies concentrated on?
- What are the types of AR applications?
- What are the technologies used for AR applications?
- Which senses do the AR applications engage?
- What is the type of AR application validation?
4. General qualitative data
5. Technologies used in AR applications
5.1. Software
5.1.1. Hardware
5.2. Assets used in AR applications
5.3. AR environments, scenarios and limitations
6. Taxonomy of scientific papers
6.1. AR in engineering
6.2. AR in life science
6.3. AR in medicine
6.3.1. AR in medical education
6.3.2. AR in medical treatment
6.4. AR for special needs education
7. Application evaluation methods
8. Educational advantages of AR applications
9. Conclusion and future directions
Author Contributions
Conflicts of Interest
References
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| Device | Characteristics (RES, FOV) | Usage count | E.g. ref. | |
|---|---|---|---|---|
| Tablet / Mobile Phone | ![]() |
like the device used | 478 | [76,77,78] |
| Hololens |
![]()
|
ver.1 1268 x 720 34° ver.2 2048 x 1080 52° |
82 | [79,80,81] |
|
Magic Leap |
![]() |
1280 x 960 50° |
13 | [82,83,84] |
|
Google Glass |
![]() |
640 x 360 83° |
12 | [85,86,87] |
| Devices | Context of use | E.g. ref. |
|---|---|---|
| Kinect | hand movements recognition for learn tooth-brushing technique | [74] |
| Leap Motion | hand and finger tracking device used for visualisation of hand anatomy | [86] |
| Projector | projecting the process mimicking a real production process and displaying additional data | [88] |
| Motion Capture | operator hands tracking for manual assembly task verification | [89] |
| Magic Mirror | a teaching device for anatomy courses | [90] |
| Microscope | microscope-based AR environment successfully implemented for spinal surgery | [91] |
| Scenario type | Usage [%] | E.g. ref. |
|---|---|---|
| Simple visual solutions | 54% | [83,90,105] |
| Learning by doing | 35% | [76,77,106] |
| Evaluation of user’s performance | 9% | [107] |
| Method type | Usage count | E.g. ref. |
|---|---|---|
| UX questionnaire | 376 | [164,165,166,167] |
| Performance Verification | 204 | [76,77,106,168] |
| Hybrid method (UX and PV) | 87 | [169,170,171,172] |
| Method | Content of use | Experimental protocol | Participants | Results | Ref. |
|---|---|---|---|---|---|
| Expert validation | AR application addressing the heart’s anatomic structure for pre-service science teachers’ laboratory learning. |
|
30 pre-service teachers taking the biology laboratory course |
|
[173] |
| Automatic validation | AR application to assist and guide operators involved in manual assembly processes in real-time. |
|
12 inexperienced operators, both female and male with various anthropocentric parameters. | A real industrial case was adopted to evaluate the benefits of the developed technology compared to the traditional approach in terms of the learning rate, which increases by 22% with a reduction in manual process duration up to -51% during the first assembly cycles. | [89] |
| Pre and post-test | Magic Mirror as a system for combined anatomy and radiology teaching. | A non-announced examination with 20 multiple choice questions similar to the anatomy part of the first main German medical examination. | 749 first-year medical students and 72students from follow-up elective course |
|
[90] |
| Observation | Insights into how current mobile AR interfaces affect co-located group collaboration. | Participants performed collaborative tasks with virtual models that have three different levels of complexity. The session was video recorded for further analysis. | 20 participants (11 female, 9 male) in groups of 4 (snowball sampling) |
|
[174] |
| Field of application | Number of projects |
|---|---|
| Medicine | 10 |
| General | 7 |
| Cultural heritage | 7 |
| Manufacturing | 6 |
| Sport and recreation | 2 |
| Transport | 2 |
| Total | 34 |
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