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A Framework for Designing Gender Inclusive Mobile Learning Experiences

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Smart Mobile Communication & Artificial Intelligence (IMCL 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 936))

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Context: Mobile learning (m-learning) is education via portable devices like laptops and smartphones. Current guidelines for creating mobile learning environments cover technological, pedagogical, and social aspects but frequently neglect to include gender-specific considerations. This oversight can worsen the gender disparity in education, potentially leading to unequal opportunities and outcomes for learners of different genders.

Purpose: This research aims to establish an action-oriented framework to enhance gender inclusivity in mobile learning.

Approach: A survey involved 24 instructors from various disciplines. The survey examined course content, teaching methodologies, and assessment proce-dures for gender inclusivity. Statistical analysis utilized Bayesian credible inter-vals and Mann-Whitney U-tests.

Outcomes: The study reveals the current state of gender inclusivity in mobile learning among the surveyed instructors. Distribution histograms for each ques-tion are also presented, offering a more nuanced understanding of the data. This informed the creation of the actionable framework with eight key components.

Recommendations: The framework recommends focused educator training, development of inclusive materials and examples, the use of gender-neutral lan-guage and visuals, the inclusion of diverse references, equitable assessment pro-cedures, and a commitment to continuous improvement in inclusivity practices. It serves as a guide for educators and curriculum developers to consciously integrate gender inclusivity into their mobile learning programs.

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This work was supported by Nazarbayev University under Grant 021220FD0751 (FDCRG).

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Correspondence to Mariza Tsakalerou .

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Lukhmanov, Y., Perveen, A., Tsakalerou, M. (2024). A Framework for Designing Gender Inclusive Mobile Learning Experiences. In: Auer, M.E., Tsiatsos, T. (eds) Smart Mobile Communication & Artificial Intelligence. IMCL 2023. Lecture Notes in Networks and Systems, vol 936. Springer, Cham.

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