Title

Contextual Learning And Memory Retention The Use Of Near Field Communications, Qr Codes, Qbic, And The Spacing Effect In Location Based Learning

Abstract

An important part of multiplatform or blended learning is designing learning environments that take full advantage of the relative strengths and weakness of the various platforms employed to meet learning objectives. The desktop has strengths that are conducive to immersive learning environments, whereas mobile devices excel in contextual learning and performance support roles. Blended learning then, is not merely porting the same content from one platform to another, but recognizing the need for unique implementations. This chapter will examine two general applications in which mobile learning takes advantage of the flexibility afforded by the platform. In the first case we will explore the possibilities presented by physical hyperlinks through the use of Near Field Communications, QR codes, and image recognition software. In addition to providing contextually relevant information, the mobile platform is ideal for providing enhanced conceptual retention. The Spacing Effect demonstrates that memory decays according to a well-defined logarithmic curve. Once this curve has been optimized for an individual, it is possible to determine the most productive times to review learning objectives. Mobile devices are the perfect platform to review material initially mastered on a desktop or in a classroom, and these scheduled sessions can boost retention times dramatically. Contextual Learning and Enhanced Retention are two applications that cater to the strengths of mobile devices, and augment a holistic multiplatform approach to learning. © 2010, IGI Global.

Publication Date

12-1-2009

Publication Title

Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education

Number of Pages

309-320

Document Type

Article; Book Chapter

Personal Identifier

scopus

DOI Link

https://doi.org/10.4018/978-1-60566-703-4.ch019

Socpus ID

84901518064 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84901518064

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