DIGITAL LIBRARY
MOBILE LEARNING RESEARCH AT RCAAP: A LITERATURE REVIEW BASED ON THE APPLICATION OF THE MAECC® META-MODEL
1 Fundação Instituto de Administração, Faculdade de Economia, Administração e Contabilidade, USP; LE@D, Universidade Aberta (PORTUGAL)
2 Universidade Aberta - Open University Portugal (PORTUGAL)
About this paper:
Appears in: EDULEARN22 Proceedings
Publication year: 2022
Pages: 3483-3489
ISBN: 978-84-09-42484-9
ISSN: 2340-1117
doi: 10.21125/edulearn.2022.0850
Conference name: 14th International Conference on Education and New Learning Technologies
Dates: 4-6 July, 2022
Location: Palma, Spain
Abstract:
Contemporary society is increasingly using and depending on information and communication technologies in all fields of human action, including teaching and learning. In particular, technologies and devices aimed at mobile learning have been shaping conditions for the creation and development of new pedagogical approaches, expanding the availability of educational and/or learning resources for use in the most diverse formal or non-formal environments, where learning can occur. This study is motivated to continue the literature reviews on mobile learning carried out with the application of the Meta-Model of Analysis and Exploration of Scientific Knowledge (MAECC), published in open repositories, namely that of Universidade Aberta and those consolidated in RCAAP, the Scientific Open Access Repository of Portugal.

The object of analysis is the academic production on mobile learning published and made available, in open access, through the RCAAP portal, until the 2021 year. This research seeks to analyze and systematize the knowledge published in the documents of the corpus, aiming at identifying:
1) Which research questions were expressly stated in the published studies;
2) What research methodologies were used in these studies;
3) What contributions and implications were found in the analyzed studies.

The qualitative methodological approach, predominant in our research study, is complemented by procedures of basic descriptive statistics, in order to better analyze and understand the emerging results.
Keywords:
m-learning, m-learning, Knowledge Systematization, Meta-model of Analysis and Exploration of Scientific Knowledge, Scientific Open Access Repository of Portugal.