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Designing Educational Mobile Augmented Reality Games Using Motivators and Disturbance Factors
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0001-5966-992x
Ajou University.
2019 (Engelska)Ingår i: Augmented Reality Games II: The Gamification of Education, Medicine and Art / [ed] Vladimir Geroimenko, Springer, 2019, s. 33-56Kapitel i bok, del av antologi (Refereegranskat)
Abstract [en]

Mobile augmented reality (MAR) has emerged as a mainstream technology to provide novel visualization and interaction opportunities across application domains. The primary forte of MAR is its ability to bridge the real world with virtual worlds by bringing virtual elements onto a real-world view, and by adapting the experience according to the user’s location and other context parameters. Research has shown that MAR possesses a multitude of affordances in the field of education. These affordances can be amplified in educational MAR games (EMARGs) due to the motivational value and the fun factor provided by intriguing game elements. However, there is a gap in research on design guidelines for EMARGs, especially regarding the connection to motivators and disturbance factors that may have positive and negative effects respectively on the learning experience. In this chapter, we first describe related background, and then present two MAR case studies—a treasure hunt and a story-driven adventure game—to illustrate our experiences in designing EMARGs. We conduct a qualitative analysis of the case studies based on questionnaire answers and interviews of 29 and 112 participants respectively, to identify motivators (16, 20) and disturbance factors (11, 25) in the participants’ gameplay experiences. Through an analysis of the motivators, disturbance factors and our design experiences, we proposed 24 design guidelines in six categories that can potentially strengthen motivators and diminish disturbance factors in MAR applications.

Ort, förlag, år, upplaga, sidor
Springer, 2019. s. 33-56
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Distribuerade datorsystem
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URN: urn:nbn:se:ltu:diva-74373DOI: 10.1007/978-3-030-15620-6_2ISBN: 978-3-030-15620-6 (digital)ISBN: 978-3-030-15619-0 (tryckt)OAI: oai:DiVA.org:ltu-74373DiVA, id: diva2:1322955
Tillgänglig från: 2019-06-11 Skapad: 2019-06-11 Senast uppdaterad: 2021-05-07Bibliografiskt granskad

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Laine, Teemu H.

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Totalt: 320 träffar
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