Architectural Support for Context-Aware Mobile Learning Applications

2021 ◽  
Author(s):  
Bimal Aklesh Kumar ◽  
Bibhya Sharma ◽  
Elisa Yumi Nakagawa
Keyword(s):  
Mobile Learning ◽  
Context Aware ◽  
Architectural Support

Context-aware ubiquitous and mobile learning systems: research gaps and challenges

2021 ◽  
Vol 13 (3) ◽  
pp. 309
Author(s):  
Jovani Alberto Jiménez Builes ◽  
Jorge Muñoz ◽  
David Santiago Garcia Chicangana ◽  
Oscar Santiago López Erazo ◽  
Carolina González
Keyword(s):  
Mobile Learning ◽  
Learning Systems ◽  
Context Aware ◽  
Research Gaps ◽  
Systems Research

M-Learning Generations and Interview Study Results of a Mobile Context-Aware Learning Schedule Framework

2011 ◽  
pp. 28-55 ◽  
Author(s):  
Jane Yin-Kim Yau ◽  
Mike Joy
Keyword(s):  
Mobile Learning ◽  
Adaptive Learning ◽  
Interview Study ◽  
Learning Preferences ◽  
Context Aware ◽  
Postgraduate Students ◽  
Learning Contexts ◽  
Proposed Model ◽  
Study Results ◽  
Mobile Context

Mobile learning applications can be categorized into four generations – ‘non-adaptive’, ‘learning-preferences’-based adaptive, ‘learning-contexts’-based adaptive and ‘learning-contexts’-aware adaptive. The research on our Mobile Context-aware and Adaptive Learning Schedule framework is motivated by some of the challenges within the context-aware mobile learning field. These include being able to create and enhance students’ learning opportunities in different locations by considering different learning contexts and using these as the basis for selecting appropriate learning materials for students. The authors have adopted a pedagogical approach for evaluating this framework – an exploratory interview study with potential users consisting of 37 university students. The authors targeted primarily undergraduate computing students, as well as students within other departments and postgraduate students, so that a deep analysis of a wider variety of users’ thoughts regarding the framework can be gained. The observed interview feedback gives us insights into the use of a pedagogical m-learning suggestion framework deploying a learning schedule subject to the five proposed learning contexts. Their data analysis is described and interpreted leading to a personalized suggestion mechanism for each learner and each scenario, and a proposed model for describing mobile learning preferences dimensions.

Towards a Flipped Classroom Based on a Context-Aware Mobile Learning System (FC-CAMLS)

2020 ◽  
pp. 43-56
Author(s):  
Mahnane Lamia ◽  
Hafidi Mohamed
Keyword(s):  
Mobile Learning ◽  
Structural Equation ◽  
Flipped Classroom ◽  
Learning System ◽  
Equation Modeling ◽  
Context Aware ◽  
Course Content ◽  
Positive Effects ◽  
Mobile Learning System ◽  
Students Satisfaction

The approach proposed in this chapter called flipped classroom based on context-aware mobile learning system (FC-CAMLS) aims to provide learners with an adapted course content format based on their feedback and context. The latter has a significant influence on multimedia content in adaptive mobile learning. The contribution was applied in the context of the flipped learning in order to manage the heterogeneity of context imposed by this approach. Firstly, the authors present a quantitative analysis by means of structural equation modeling to analyze the causal relationships of knowledge, skills, and motivation with students' satisfaction. Secondly, they confirm that the proposed flipped classroom has positive effects on students' knowledge, skills, and motivation. Finally, the research provides useful results that the use of the context dimensions and learner feedback in adaptive mobile learning is more beneficial for learners especially in the flipped classroom.

scholarly journals UBISOUND: DESIGN A USER GENERATED MODEL IN UBIQUITOUS GEOSPATIAL INFORMATION ENVIRONMENT FOR SOUND MAPPING

2014 ◽  
Vol XL-2/W3 ◽  
pp. 243-247 ◽  
Author(s):  
S. Soleimani ◽  
E. Keshtehgar ◽  
M. R. Malek
Keyword(s):  
Mobile Computing ◽  
Data Acquisition ◽  
Ubiquitous Computing ◽  
Information Environment ◽  
Context Aware ◽  
Geospatial Information ◽  
Noise Mapping ◽  
Mobile Wireless ◽  
Architectural Support ◽  
Gis Applications

In this paper, we study how mobile computing and wireless technologies can be explored to provide effective ubiquitous GIS services. Instead of reinventing the wheels, we make use of smartphones, off-the-shelf components, and existing technologies in ubiquitous computing (i.e. wireless and mobile positioning technologies, and data acquisition techniques and processing via sensors) to develop a middleware, and tools for the development of systems and applications to provide effective ubiquitous GIS services. Two main tasks to be studied are: 1) Developing a framework, called UbiSound, to provide the infrastructure and architectural support for realizing ubiquitous GIS services; and 2) Designing and developing ubiquitous GIS applications by utilizing the UbiSound framework to let users experience and benefit from the context aware services. We use scenario to illustrate how mobile/wireless and sensor technologies can enable ubiquitous GIS services in UbiSound. Some of the examples included in UbiSound are: Noise mapping, soundscape mapping and wellbeing data acquisition and analysis.

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