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A Revision of the Literature Concerned with Mobile, Ubiquitous, and Pervasive Learning: A Survey

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Mobile, Ubiquitous, and Pervasive Learning

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 406))

Abstract

This chapter tailors a perspective of the work fulfilled in three learning research lines, which besides holding many common attributes also tend to converge to shape mobile, ubiquitous, and pervasive sceneries. Such a junction pursues to spread the traditional classroom and distance settings to open environments, as well as use the surrounding physical and digital objects as learning content that is available to learners at anytime, anywhere, and in any way. In sum, a complete learning environment is recreated to provide formal and informal learning to support academic studies, professional training, and lifelong learning. Thus, in this chapter a description of the mobile, ubiquitous, and pervasive learning (MUP-Learning) arena is presented through the selection of a sample of recent and transcendent works that offer from a conceptual contribution, such as models and frameworks, even empirical approaches oriented to specific domains of study. The sample of works is characterized according to a proposed pattern, as well as organized according to a suggested taxonomy. A profile to describe each work is also stated and a series of statistics are presented, as well as an analysis of the arena is provided to understand the potential and challenges related to the MUP-Learning field.

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Notes

  1. 1.

    The meaning of this journal as well as others that appears within figures and text in this section are identified in Appendix.

Abbreviations

AR:

Augmented reality

CSCL:

Computer-supported collaborative learning

MUP-Learning:

Mobile, ubiquitous, and pervasive learning

m-learning:

Mobile learning

m-CSCL:

Mobile computer-supported collaborative learning

p-learning:

Pervasive learning

SRL:

Self-regulated learning

SWOT:

Strengths, weaknesses, opportunities, and threats

UNESCO:

United Nations Educational, Scientific, and Cultural Organization

u-learning:

Ubiquitous learning

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Acknowledgments

The first author gives testimony of the strength given by his Father, Brother Jesus and Helper, as part of the research projects of World Outreach Light to the Nations Ministries (WOLNM). Moreover, this work holds a partial support from grants: CONACYT-SNI-36453, IPN-COFAA-SIBE-ID: 9020/2015-2016, IPN-SIP-EDI-848-14, IPN-SIP-20150910, CONACYT 289763, and IPN-SIP-BEIFI-20150910. IPN-SIP-20150910, CONACYT 264215, CONACYT 289763, and IPN-SIP-BEIFI-597.

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Authors and Affiliations

  1. WOLNM: Artificial Intelligence on Education Lab, 31 Julio 1859 No. 1099-B, Leyes Reforma, Iztapalapa, 09310, Mexico City, Mexico

    Alejandro Peña-Ayala

  2. ESIME Zacatenco—Instituto Politécnico Nacional (IPN), Building Z-4, 2nd Floor, Lab 6, Miguel Othón de Mendizábal, S/N, 07320, Mexico City, Mexico

    Alejandro Peña-Ayala & Leonor Cárdenas

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  1. Alejandro Peña-Ayala
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Correspondence to Alejandro Peña-Ayala .

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  1. Artificial Intelligence on Education Lab, WOLNM:, Ciudad de México, Mexico

    Alejandro Peña-Ayala

Appendix

Appendix

The pattern that characterizes the main attributes of the sample of MUP-Learning works, described in Sect. 3.5, is edited in Table A.1, where seven key traits are shown. The series of patterns is presented according to the hierarchy sketched in the Taxonomy to classify MUP-Learning works, illustrated in Table 1, as well as the profile stated for each related work along Sect. 4.

Inclusive, the name of each category, subcategory, and topic as well as their respective count of related works is presented as a header inside of the table body. However, due the lack of space, diverse acronyms are used to facilitate the edition of several common values, according to next definitions:

  • Journal:

    • BJET: British Journal of Educational Technology.

    • C&E: Computers & Education.

    • CHB: Computers in Human Behavior.

    • EC_TEL: European Conference on Technology Enhanced Learning.

    • ESWA: Expert Systems with Applications.

    • ET&S: Educational Technology & Society.

    • ETRD: Education Tech Research Development.

    • ICALT: International Conference on Advanced Learning Technologies.

    • IHE: Internet and Higher Education.

    • KMEL: Knowledge Management & E-Learning: An International Journal.

    • RPTEL: Research and Practice in Technology Enhanced Learning.

    • SET: Journal of Science and Technology.

    • SLE: Smart Learning Environments.

    • TOE: IEEE Transactions on Education.

    • TOLT: IEEE Transactions on Learning Technologies.

    • ULET: Ubiquitous Learning Environments and Technologies.

    • UMUAI: User Modeling and User-Adapted Interaction.

  • Country: UK: United Kingdom; USA: United States of America.

  • Academic level: N/S: not specified.

  • Learning setting: N/S: not specified.

  • Domain: ICT: information–communication technologies.

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Peña-Ayala, A., Cárdenas, L. (2016). A Revision of the Literature Concerned with Mobile, Ubiquitous, and Pervasive Learning: A Survey. In: Peña-Ayala, A. (eds) Mobile, Ubiquitous, and Pervasive Learning. Advances in Intelligent Systems and Computing, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-319-26518-6_3

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