Human-computer interaction perspective on mobile learning: Gender and social implications

Al-Hunaiyyan, Ahmed and Alhajri, Rana and Al-Sharhan, Salah and Bimba, Andrew (2021) Human-computer interaction perspective on mobile learning: Gender and social implications. International Journal of Interactive Mobile Technologies, 15 (11). pp. 4-20. ISSN 1865-7923, DOI

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The state of Kuwait has implemented a national e-learning initiative that included the distribution of mobile devices (Tablets) to be used by students and educators. Understanding the obstacles which currently prevent a successful roll-out, implementation, and adoption of mobile learning methods in Kuwait is vital. The opportunities for learners are particularly essential in this respect, and an absence of research remains an issue as far as Kuwait is concerned. This research was carried out within Kuwait Higher Education (HE) facilities to assess students’ opinions and motivations for adopting this form of learning, aiming to analyse its efficacy and explore the social factors and gender issues that might impact extending mobile learning (m-learning) potential throughout Kuwait. A questionnaire has been central to this research, sent out to 620 students in total. Two statistical methods, an analysis of variance (ANOVA), and an independent-sample t-test, have been applied. The latter is essential for assessing if any statistical significance exists between two unrelated groups (male and female being the two independent variables). The results reveal disparities of age and gender while highlighting certain social and cultural factors that might prove to be obstacles that m-learning will need to overcome. A firm analysis of such issues will enable improved approaches to help learners’ access and make the most robust m-learning methods. © 2021

Item Type: Article
Funders: None
Uncontrolled Keywords: e-learning; Gender differences; Higher education; Human-Computer Interaction; Mobile learning
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms Zaharah Ramly
Date Deposited: 27 Nov 2023 04:59
Last Modified: 27 Nov 2023 04:59

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