Enhancing Multi-Body Mechanisms With Learning-Aided Cues in an Augmented Reality Environment

Enhancing Multi-Body Mechanisms With Learning-Aided Cues in an Augmented Reality Environment

DOI: 10.4018/978-1-7998-0465-9.ch006


Augmented reality (AR) is a potential area of research for education, covering issues such as tracking and calibration, and realistic rendering of virtual objects. The ability to augment real world with virtual information has opened the possibility of using AR technology in areas such as education and training as well. In the domain of computer-aided learning (CAL), researchers have long been looking into enhancing the effectiveness of the teaching and learning process by providing cues that could assist learners to better comprehend the materials presented. Although a number of works were done looking into the effectiveness of learning-aided cues, none has really addressed this issue for AR-based learning solutions. This chapter discusses the design and model of an AR based software that uses visual cues to enhance the learning process and the outcome perception results of the cues.
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According to Bonnie Meyer in her book published in 1975, cueing means the addition of a non-content aspect of prose, which gives emphasis to certain aspects of the semantic content or points out aspects of the structure of the content (de Koning et al., 2010a). Hence, researchers have been identifying and looking at various important cues to aid learners in computer mediated learning environments. The use of multimedia elements in instructional design have also contributed to the importance of using suitable cues to aid in the delivery of multimedia enhanced contents (de Koning et al., 2010b); (Lijia et al., 2011). Appropriate cues in multimedia enhanced learning environment will reduce students cognitive load (Mayer & Moreno, 2003); Brianna et al., 2007). The advancements in the area of computer graphics and AR have resulted in the use of complex 2D and 3D synthetic computer generated objects in AR-based computer aided learning (CAL) applications. A number of researches have been done incorporating AR technology in various domains of educational and training scenarios (Zagoranski & Divjak, 2003); (Augmented Reality in Education, 2012). This project in particular, is looking into, not only using AR technology to assist in the delivery of mechanical engineering education, but also enhancing the learning process with suitable learning-aided cues.

Key Terms in this Chapter

Markers: Are normal images or small objects which are trained beforehand so that they can be recognized later in the camera stream.

Multi-Body Mechanisms: A multibody dynamic (MBD) system is one that consists of solid bodies, or links, that are connected to each other by joints that restrict their relative motion. The study of MBD is the analysis of how mechanism systems move under the influence of forces, also known as forward dynamics.

Slider Crank: Linkage is a four-link mechanism with three revolute joints and one prismatic, or sliding, joint. The rotation of the crank drives the linear movement the slider, or the expansion of gases against a sliding piston in a cylinder can drive the rotation of the crank.

Visual Cues: Is a signal and reminder of something; aiming to be self–explanatory and pre-attentive, it brings to mind knowledge from previous experiences providing a framework for its own interpretation.

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