Context aware mobile learning application development: A systematic literature review

Kumar, Bimal Aklesh; Sharma, Bibhya N.

doi:10.1007/s10639-019-10045-x

Cited by 23 publications

(13 citation statements)

References 36 publications

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“…Most of the contextual data in learning applications are captured using the sensors available in the mobile device. The mobile sensors can be classified into three main categories, namely environmental sensors, biosensors, and activity sensors (Kumar and Sharma, 2019). The use of environmental sensors in the development of mobile applications is mainly to capture the surrounding context information.…”

Section: Sensorsmentioning

confidence: 99%

“…The context sensing layer is an essential part of the implementation of mobile learning applications. The raw context data acquired from the sensors available on the mobile devices are processed and represented as relational or ontology data that is convenient to be computerized by the system (Kumar and Sharma, 2019). Hasanov et al (2019) derived the context sensing layer into three fundamental steps to attain context acquisition.…”

Section: Context Sensing Layermentioning

confidence: 99%

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Personalized and Adaptive Context-Aware Mobile Learning: Review, challenges and future directions

Gumbheer

Khedo

Bungaleea³

2022

Educ Inf Technol

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Due to the outbreak of COVID 19, digital learning has become the most efficient learning and teaching technique adopted across the world. The pervasiveness of Personalized and Adaptive Context-Aware Mobile Learning (PACAML) technologies is improving the academic performances of learners by providing an efficient learning platform that supports social interactivity, context sensitivity, connectivity, and individuality in a ubiquitous manner. Several studies have demonstrated the efficacy of PACAML in a modern and innovative educational environment. Based on the recent studies and development of mobile learning technologies, there is clearly a gap in the research that provides a comprehensive body of knowledge on PACAML. In this paper, a review has been conducted on the existing PACAML, analyzing the recent research and development progress using Kitchenham et al. (2009) for systematic reviews. The review was conducted on 25 papers which were selected using the PRISMA technique to put forward the quality criteria that are based on the research aims, objectives and knowledge relevant to the study of PACAML. The results identified the contextual information used in the PACAML studies, the infrastructural requirements of PACAML, the application of PACAML in functional educational settings and the major methodological approaches applied in the studies of PACAML. Finally, the paper presents challenges and future directions that will be of interest to researchers in the educational technologies in the context of PACAML.

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Section: Sensorsmentioning

confidence: 99%

Section: Context Sensing Layermentioning

confidence: 99%

Personalized and Adaptive Context-Aware Mobile Learning: Review, challenges and future directions

Gumbheer

Khedo

Bungaleea³

2022

Educ Inf Technol

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“…Context-aware analysis in teaching-learning processes has evolved significantly in several emerging fields such as Context-Aware Mobile Learning Applications (CAMLA). The systematic literature review presented by Kumar and Sharma (2019) describes the key components of CAMLA through the extraction and representation of context information, context adaptation, and different types of applications developed. The review identifies different context types of which the student, location, and time are the most frequently used types in CAMLA development.…”

Section: Context-awarenessmentioning

confidence: 99%

Omnichannel for Learning

Tabares¹,

Vallejo²

2020

Education 4.0: A View From Different Digital Proposals

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“…This study's overarching goal is to comprehend the current state of m-learning use in order to ensure its successful implementation in the future. While [11] mentioned the context-aware mobile learning application employed during development in their study. The research reveals eight context factors, including the learner's cognitive state, time, learning style, place, technology, and people.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Mobile Learning for Adult Learners: State-of-the-Art, Taxonomy, and Challenges

et al. 2022

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Adult learner performance has become a significant challenge in the field of education. Adult learners are identified as being of productive age in engaging with multiple commitments, including studying. The multiple engagements make it difficult for them to manage their time and focus, which contributes to a high institutional dropout rate. This situation has led to a reduced number of highly skilled and professional workers in the country because of the failure to meet academic requirements. In the current digital world, every aspect of education includes some elements of technology. However, most adult learners are reluctant to utilise mobile technology for the purpose of learning. Therefore, this review paper aims to provide a state of art regarding mobile learning for adult learners. Considering a set of inclusion and exclusion criteria, 135 related articles from IEEE, Google Scholar, Springer Link, Science Direct, Taylor and Francis, and Wiley digital databases were extracted and reviewed. The state of the art of M-learning were discussed in terms of functions of m-learning, effectiveness, and m-learning as a tool. Keywords from articles were extracted and the taxonomy of M-learning was discussed under five classifications (Behavioural Intention, Technological Support, Educational Content, Learner Coordination, and Instructional Design) were created based on these keywords, which represented the same meaning and features that were discussed in the articles. The findings can raise awareness among mobile learning practitioners to provide more effective services for adult learners. Meanwhile, higher education institutions can be better redesigned in terms of pedagogy to fit the needs of adult learners with mobile learning.

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Context aware mobile learning application development: A systematic literature review

Cited by 23 publications

References 36 publications

Personalized and Adaptive Context-Aware Mobile Learning: Review, challenges and future directions

Personalized and Adaptive Context-Aware Mobile Learning: Review, challenges and future directions

Omnichannel for Learning

A Survey on Mobile Learning for Adult Learners: State-of-the-Art, Taxonomy, and Challenges

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