Augmented Reality for Education
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Reimagining our future engagement with learners through an augmented reality (AR) lens offers a range of possibilities, on a continuum from rigid materials, created with generic learning outcomes, to learner-centered, personalized, and emancipatory practice. Educational paradigms are shifting to include alternatives to physical classrooms and the controlled virtual learning spaces that support traditional content delivery. Augmented reality is part of a broader mixed reality where varying degrees of virtual enhancement to the real world can be integrated into traditional delivery practice but also allow learning spaces to be explored more imaginatively and collaboratively.
For educators, there are significant challenges to utilize the potential of technology to meet the increasing demands of students, institutions, industry, and the expectations of society. By carefully scaffolding educators into reframing their curricula to encourage, inspire, and motivate a diverse student body, technology can act as a mediator – a proxy for what Vygotsky termed the “more capable peer” (Cook 2010). AR applications in education, training, marketing, medicine, and other industries demonstrate both the capability of the technology and the need for designers to be aware of the possibilities. Karakus et al. (2019), in their bibliometric study of augmented reality in education, identify the work by Wu et al. (2013) as the most influential across the sector. This entry suggests that AR not only bridges virtual and real worlds but also creates an enhanced reality through a creative process. They argue that the educational values of AR are not solely based on the use of technologies but are closely related to how AR is designed, implemented, and integrated into formal and informal learning settings.
The recent McKinsey report (Bughin et al. 2018) modelled skills shifts in automation and artificial intelligence going forward to 2020 and found a sharp acceleration in demand for these technologies that will transform the workplace, as humans work with ever smarter machines. Transferring technology for educational use, reuse and repurpose are key emergent themes in research as employers demand ever more technology enabled graduates, with high-level cognitive skills.
AR Definition and General Mechanisms
There is no reason the objects displayed by a computer have to follow the ordinary rules we are familiar with …the user of a visual display could easily make solid objects transparent. He can ‘see through matter’ [with] augmented reality urbanware
The term was first used to describe technology by Tom Caudell in 1990 while working on ways to visualize component information in aircraft construction at Boeing. In common with other virtual technologies, experimental prototypes were developed during the 1990s, with the first AR system developed by Louis Rosenberg at the US Air Force Research Laboratory in 1992.
Today there are a variety of devices and technologies, but most users experience AR as an application on their smartphone to display media combined with the image of the real world on their screen. Typically, the media is triggered by scanning objects or images that match a previously captured image of the scene. Other triggers include dedicated logos, QR codes, location sensors, or system-generated events such as responses to user queries, display of data streams, or timed events. It is with these broader considerations in mind we move to the affordances of AR and the benefits and barriers to adoption in a range of learning contexts.
Affordances and Application Areas
The defining feature of AR is that it is context-sensitive, aware of its temporal, spatial, physical, and virtual environment, operating at a specific time (temporal) and place (spatial), and in response to particular/predetermined real-time triggers (physical) or data input (virtual). In common with other virtual environments, it can respond to user interaction and direction so that the experience can be unique to the user. There are many applications of AR, but these can be usefully categorized into three broad and overlapping areas – content delivery, user content creation, and data integration.
Many applications use AR to allow the visualization and 3D exploration of remote or difficult to see structures or components, which make it ideal for content delivery and experiential learning in engineering, science, medicine, environment, and architectural and historical education.
In common with previously innovative, disruptive technologies, AR is extending from specialized developers and professional publishers to include hobbyists and casual creators within social media. Ranging from basic image filters to more sophisticated AR, shopping experiences and development studios, Snapchat, Facebook, and Instagram are providing users with AR creation and sharing facilities. This provides considerable opportunity for educationalists to develop collaborative projects that allow students to create and share their own artifacts in many different learning contexts.
A more technically advanced use combines image recognition with data analysis, enabling prototype systems to automatically identify triggers and associate overlay information and enabling large-scale integration of AR with existing information resources. Using AR as part of data analysis and visualization can help illustrate and interpret results. For example, blood circulation data can be projected onto a patient’s body to show blood flow issues from diseases such as diabetes; the inside of a nuclear reactor comes to life; teams working at critical incidents such as fire crews can “see” how flames proliferate inside a building.
Although the original Google Glass was seen as a breakthrough, it has not been a commercial success. However, there are a wide range of heads-up display glasses that project media onto the surface of the lens and provide different levels of interaction – from simple audio to sophisticated interactive media and dedicated controllers for remote devices such as drones. Processing power is often provided by mobile phone to provide an intermediate platform between a handheld device and a full headset.
Headsets designed for VR and gaming (such as Oculus, HTC Vive, Samsung Gear, and Sony PlayStation VR) have been adapted for AR but need to provide a camera facility to capture the real world to enable augmentation. Many of these require a high-speed data link to a sufficiently powerful computer or game console, which provides good quality graphics but limits their mobility. More sophisticated versions come with their own image processing capability.
An indication of the direction of technological development is shown by the Magic Leap, which has been designed for AR with lenses embedded in a wraparound headset. This has a pocket-sized processing pack and uses sensors for gesture control, object location, and accurate image overlay. The Microsoft HoloLens uses an onboard computer for gesture control sensors and to project images onto a transparent screen to combine the virtual with the real-world view. It has shown potential for AR-based collaboration allowing participants from different locations to interact with 3D models for engineering and medical projects.
Using and Creating AR
Representative selection of AR systems and tools
Systems with free app for viewing, suitable for user created content from nonexperts, with mobile app and web-based studio
HP Reveal (Aurasma)
Easy install and link to content from QR or URL
PR, marketing, casual users
Monthly hosting fee, educational discount
Print, magazines, and catalogues
ZapBox – cardboard headset, controllers and trigger cards
Retail, packaging, publishing, and education
Campaign management user tracking
Marketing, higher education
Systems for technically able students or support staff, code-based application development and professional system development
Google API integrates input from many sources, targets different systems
Independent AR application developers
Multiple users, persistent sessions, object tracking
Independent AR application developers
Accurate and persistent AR artifact location
E-commerce, sales, education
Geo-location, 3D scene recognition, object tracking, browser interface
Bespoke and commercial AR creation
Integration with 3D systems, trigger AR with location, card, image, or object
Independent AR application development
Augmented Reality for Learners: Examples of the Learner Experience
The affordances of AR support a range of pedagogical approaches when designing a learning experience. Place-based learning, encouraging learners to make their thinking more visible, and team-based approaches to professional development help engage the learner in an active learning context (Ferguson et al. 2019).
AR is particularly suited for use within a scaffolded program. It gives an element of novelty, encourages exploration, and focuses on the individual experience, developing a deeper understanding of the concepts while providing a stimulating, collaborative, problem-solving environment. It provides a platform to engage students with learning at a place and time of their choosing, moving outside the confines of the formal lecture theater and changing our practices in supporting their learning. These principles can be seen in the Hobbs and Holley (2016) case study; this describes the re-energizing of a cohort of computer science students who were struggling with the personal development planning (PDP) assessed component of a core unit. By undertaking a radical curricula review, the weekly didactic lecture was transformed to a co-created, dynamic, student-led space. Students in small groups were required to create a team name with a logo and an augmented reality artifact (an Aurasma “aura”) to engage with the University Library. They then planned, scripted, and storyboarded a short video overlay for their aura, which echoed and linked to core themes from software and game design. Over a 3-year period, the progression rate moved from 66% to 91%, working with 345 students; the biggest single factor was that the authentic aspects of the AR tasks aligned with student expectations for the context of the soft skills they were practicing. Thus learner-centered and personalized approaches to learning were supported by the affordances of AR. Feedback showed that the learners were motivated, inspired, and challenged by this different model of learning.
AR offers educators and their learners opportunities to personalize pedagogical practices through the use of content specific apps, an early example was “The 3D Interactive Augmented Reality Coloring Book,” introduced at the IEEE 3D symposium by Clark and Dünser in 2012. This exploited the affordances of AR and offered ways for educators to work with groups who struggle to access a school-based curriculum. Originally trialed with primary school classes in mind, the principles can be applied to agile design and 3D modelling for nonexperts. Another way of using AR is to embed it into learning/play activities, using objects or cards as triggers in an otherwise relatively unstructured play environment to create “educational magic toys.”
At California State University, AR was used with GPS sensors to simulate geology expeditions for students at five institutions who were able to engage with a meaningful geological learning experience, without having to travel hundreds of miles to the Grand Canyon. This is an example of AR facilitating experiential learning outside the normal environment of the classroom.
Bespoke systems use specialized equipment or combine existing systems in novel ways. For example, the “Starry Sky” exploration system created by Shanghai University demonstrates AR used within a complete learning system built with the aim of teaching primary school students about the solar system; this includes video and interactive gaming as well as mobile devices to scan ID cards that support instructor-based learning in the classroom. This illustrates how AR can be integrated with other teaching methods such as gamification.
Creative AR systems aimed specifically at education, enabled the creation and sharing of AR materials, and provided more support than generic systems, which are mostly developed for marketing and promotional uses. For example, “Augment” provides a platform for building and presenting 3D models in a range of topics. These systems provide a more problem-based approach involving design and construction of artifacts.
In industry, AR is used to provide support when/where needed by augmenting tools and infrastructure to demonstrate emergency procedures and how to use and maintain equipment. It can be used to supplement traditional training by using AR activities and context-sensitive materials. The British Safety Council uses AR in its training courses as it provides a safe environment for realistic, complex problems, and they say it has increased retention of information and the enjoyment of the learning experience.
Medicine has pioneered the use of AR for medical training (Barsom et al. 2016) and is also using it to support medical procedures such as finding veins for IV insertion and overlays to project scanning information and tissue identification during surgery. The Microsoft HoloLens has been used to locate bones and blood vessels during lower limb surgery at Imperial College. Examples such as these demonstrate how AR is not just an educational tool but is also relevant to industry and career skills, which can help to motivate students and provide more authentic learning experiences.
Sophisticated applications of AR are not confined to high-tech industry. At the North Western University Knight Lab, journalism students create AR visualization within projects designed to incorporate 3D AR visualization within their work to explain complex concepts and provide a different perspective on narrative creation.
The development of AR as a meaningful educational technology aligns with the pedagogic and economic imperatives to personalize the student experience. Responding to the changing landscape of Higher Education (HE) requires the development of imaginative approaches to support staff in delivering quality learning experiences with their students. AR and its affordances can make a significant impact, as part of a mixed-media strategy, to the holistic student experience. Wang et al. (2018) and Akçayır and Akçayır (2017) provide reviews of current educational practice with AR, showing that it is being used in both technical and more general educational contexts. Clearer proof of efficacy, such as these, should improve scalability of these technologies and convince academics that investing their time and faculty money in these technologies is appropriate in bridging the passive/active learning continuum, as well as offering a conduit for the industry/academic crossovers. AR offers spaces for digital making, creating, sharing, and curating and thus can disrupt traditional pedagogic frameworks. AR has huge potential in terms of disrupting existing pedagogical frameworks and offering shared and co-created spaces for digital making, creating, sharing, and curating.
- Bughin, J., Hazen, E., Lund, S., Dahlstrom, P., Wiesinger, A., & Subramaniam, A. (2018). Skill Shift Automation and the future of the workforce. McKinsey Global Institute Discussion Paper. https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce. Accessed 22 Mar 2019.
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