Using Artmaking Generative AIs to Support Augmented Reality Learning Designs With Adobe Aero App

Using Artmaking Generative AIs to Support Augmented Reality Learning Designs With Adobe Aero App

DOI: 10.4018/979-8-3693-1078-6.ch006
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Abstract

The making of augmented reality for mobile learning is a complex endeavor. The visual materials needed for such builds may be time-consuming to create given technological requirements. The emergence of artmaking generative AI (GAI) tools provides opportunities for to fast-track some of the work, in all phases: the design (research, brainstorming, color palette selection, visual elements, drafting, compositing, pilot testing, and others), the development (the creation of the various elements, alpha and beta testing), and the deployment (the release of the works into production). This chapter explores the work needed to co-create artworks with generative AIs, the visual editing required (right-sizing, color changes, outlining, formatting, and others), the accessibility design, the usability design, and other efforts to ensure effective augmented reality work for teaching and learning. Advances in GAI are also considered.
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Review Of Literature

The concept of virtual reality was introduced into human consciousness early in the 20th century. In 1901, writer L. Frank Baum (author of The Wonderful Wizard of Oz) introduced “special glasses capable to display the nature of characters through a letter shown on their head” called the “Character Marker” in his novel The Master Key. Here, tech can identify the quality of someone’s character, such as those who are “good,” “evil,” “wise,” “foolish,” “kind,” or “cruel” (Vertucci, et al., 2023, p. 40). The first experiments in AR technologies and techniques occurred in 1957. The first commercial AR tools “appeared in the late 1980s” (p. 35), with applications in industry and manufacturing. AR has been defined in various ways:

AR can also be described as the representation of an altered reality, in which artificial sensory information is superimposed on the normal reality perceived through the senses. The user of AR applications will then see three-dimensional virtual objects, videos, sounds, and perceive tactile or even olfactory sensations superimposed on the real world, which have been added by means of a computer. (Vertucci, et al., 2023, p. 35)

AR in “industry and consumer contexts includes the following: “design, operations, training/education, entertainment, translation, measurement, creation, navigation, automotive, accessibility, service, manufacturing, (and) sales” (Marshall, 2023, p. 336). It is instantiated in social media platforms and has been experienced by many throughout the world.

Key Terms in this Chapter

Remote Learning: Distance learning; interactive, high-tech high-touch learning methods often using learning management systems, social media, content management systems, data repositories, online libraries, and other connective technologies.

XR: Extended reality (including a mix of virtual, augmented, and mixed reality experiences).

Augmented Reality: The overlay of 2d and 3d and 4d digital contents over a physical space through the camera of various mobile, head-mounted, and other devices (and which may include sound, touch, taste, smell, and interactivity).

Interactivity: The engagement of a person with digital and physical objects (including automated agents) in an augmented reality space; the engagement of a person with others, who are co-present and / or telepresent…to enable particular outcomes from that interactivity.

Mobile Learning: The use of smartphones, pads, tablets, and other portable computers for learning, often in a “ubiquitous” or “anytime/anywhere” way.

Extended Reality (XR): The application of digital and other overlays (across a range of human senses) to extend the physical reality of a particular context.

M-Learning: Mobile Learning, the use of smartphones and laptops and other mobile computational devices for learning (including wearables).

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