Towards Adaptive Mobile Learning System

Razek, Mohammed Abdel; Bardesi, Hisham Jameel

doi:10.1109/his.2011.6122154

Cited by 8 publications

(7 citation statements)

References 5 publications

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“…The authors produced a design for a prototype tool, labelled Adaptive Mobile Learning System (AMLS), which was tested on 128 participating students. This adaptive mobile learning framework as promoted by [35] is a promising development in the field of M-learning, facilitating personalization of course delivery, learning materials, interaction styles, techniques and assignments, based on analysis of e-profiles of students that typically involves machine learning algorithms and/or questionnaires. Such personalization facilitates a transition from instructor-centred curricula to learner-centred approaches as celebrated by [32] among others.…”

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

“…The AMLS system developed by [35] involves two agents: a Filtering Agent and a Pedagogical Agent. The former program filters and analyses learning styles and preferences by means of questionnaires and long-term assessment of students' web requests for image, audio and textual materials.…”

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

“…The former program filters and analyses learning styles and preferences by means of questionnaires and long-term assessment of students' web requests for image, audio and textual materials. Based on this data, the Pedagogical Agent then assigns and distributes various learning objects compatible with students' learning trajectories [35]. The survey, administered among distance learners at King Abdul-Aziz University, KSA, revealed a number of advantages of AMLS over traditional learning systems in terms of accessibility, usability and overall student satisfaction.…”

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

“…Future research and development of mobile learning systems will benefit from the integration of such technology acceptance frameworks in assessing students' attitudes and customizing systems to improve usability and overall UX. In a follow-up study, [35] extended their initial framework to include new agents and parameters integrating social and adaptive agents. In particular, an effort was made to leverage the vast flow of students' social network data to improve the adaptivity of mobile-based courses.…”

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

“…In particular, an effort was made to leverage the vast flow of students' social network data to improve the adaptivity of mobile-based courses. Social agents (SA) created by [35] were able to tag materials and activities, make wiki entries and share knowledge and learning experiences through Facebook, substantially improving the collaborative knowledge environment for mobile learning courses.…”

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

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Cultural Factors that Influence M-Learning for Female University Students: A Saudi Arabian Case Study

Badwelan¹,

Bahaddad²

2017

IJCA

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Mobile learning (m-learning) is one of the most technological environments used in higher education distance learning programmes. M-learning provides students with widespread access to classroom resources via mobile devices' networks and the possibility to learn regardless of their time and place. Many studies have shown the importance of the relationship between electronic systems and communities' traditions, because their increasing levels of acceptance depend on many moderators that directly affect the acceptance of M-learning communities. This study aims to verify the influence of demographic moderators in the UTAUT model to increase the level of learning perspectives acceptance via mobile in specific higher education communities and institutions. In the present study, the specific community is Saudi Arabia (KSA). The gender separation found in all stages of the Saudi education system is based on religious policies rooted in an Islamic perspective. Using m-learning smartphone applications could be helpful, yet also affected by traditional factors, in supporting women's efforts in higher education institutions in conservative countries such as KSA. The experiences that we uncover in KSA could be applied in other communities. The method used in the study is a quantitative approach based on a questionnaire completed by roughly 400 university students who are studying, at least in part, via their colleges' and universities' m-learning systems. The main objective of the study is to lead to a gradual increase in the number of remote learning students in many Saudi universities over the next five years according to Saudi vision 2030. With the conservative policies pursued in KSA in mind, women face a significant challenge in completing various education paths; thus, providing m-learning through electronic channels, such as mobile applications, could assist them significantly as they face these challenges.

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Section: M-learning Acceptance In Ksamentioning

confidence: 99%

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

Section: M-learning Acceptance In Ksamentioning

confidence: 99%

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