Improving user cognitive processes in mobile learning platforms through context-awareness

Curum, Brita; Khedo, Kavi Kumar

doi:10.1109/cccs.2015.7374137

Cited by 5 publications

(4 citation statements)

References 46 publications

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“…With the assistance and support of modern infrastructures such as cloud computing, storage technology, networks, and big data, further mobility access can be gained first-hand, thus expanding the concept by using a variety of learning activities. [46] and [47] highlighted the limitations of using m-Learning technology (such as device battery life, screen, data entry methods, network connectivity, memory, and bandwidth) concerning the mobility of technology. This can be addressed by matching only the related functions of m-Learning that match with the needs of adult learners to reduce physical and wastage of using mobile devices.…”

Section: Understanding Of the M-learning Conceptmentioning

confidence: 99%

“…Likewise, the quality of education can be evaluated by several dimensions that consist of information, systems, and services [89]. Studies have shown that lessons delivered simultaneously may lead to cognitive overload [47], while the over-delivery text could distract the learning process by reducing lesson content and focus [90]. Accordingly, only related and useful information is allowed to be employed during learning sessions.…”

Section: E Instructional Designmentioning

confidence: 99%

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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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Section: Understanding Of the M-learning Conceptmentioning

confidence: 99%

Section: E Instructional Designmentioning

confidence: 99%

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

et al. 2022

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“…Brita Curum and Kavi Kumar Khedo (Curum & Khedo, 2015) pointed out the cognitive load to the users in mobile learning platform is the central for instruction design for course material and course material adaptation for personalized learning.…”

Section: Personalized Mobile Learning and Recommender Systemmentioning

confidence: 99%

Personalized Mobile Learning and Course Recommendation System

Madhubala

Akila

2021

International Journal of Mobile and Blended Learning

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Mobile-based learning provides new experience to the learners to learn anything from anywhere and anytime by using their portable or mobile device. Vast educational contents and also different media formats can be supported by the mobile devices. Access speed of those materials has also improved a lot. With this advancement, providing required content or materials in the desired format to the learner is essential to the learning management system. Also, it is very important to guide the learner based on their interest in learning. With this outset, the proposed mobile learning system helps the learners to access different courses under different levels and different specializations. The course contents are in different formats called learning objects (LO). In order to provide personalized learning experience to the learner, the system finds the learner's preferences and selects the desired learning objects. It also recommends some specializations with level to the learners to achieve higher grades.

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“…In spite of this, m-learning in Malaysia is still in an emerging stage [10]. Most projects or studies continue to emphasize the notion of establishing foundational understanding of m-learning, and activities sustained by mobile technology [11,12].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Personality Traits Towards the Intention to Adopt Mobile Learning

Sanjebad

Shrestha

Shahid

2020

Re-Imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation

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Mobile devices have become increasingly more common in the digitally connected world. Mobile learning as a model of e-learning refers to the acquisition of knowledge & skills utilizing mobile technologies. The aim of this study is to identify the extrinsic influential factors for the adoption of mobile learning. This study proposes the use of an extended technology acceptance model (TAM) theory that includes variables of personality traits such as perceived enjoyment and computer self-efficiency. The participants of this study were 351 students at University Technology Malaysia who had experiences in elearning. The study found that perceived usefulness as an extrinsic factor has the highest influence on students' intention to adopt mobile learning through an investigation of technology acceptance toward mobile learning. Personality traits such as perceived enjoyment and self-efficacy have impact on behavior intention to adopt mobile learning.

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Improving user cognitive processes in mobile learning platforms through context-awareness

Cited by 5 publications

References 46 publications

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

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

Personalized Mobile Learning and Course Recommendation System

The Impact of Personality Traits Towards the Intention to Adopt Mobile Learning

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