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Evaluating sustainability of mobile learning framework for higher education: a machine learning approach

机译：评估高等教育移动学习框架的可持续性：机器学习方法

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Purpose The purpose of this study is to evaluate the sustainability of the proposed mobile learning framework for higher education. Most sustainability evaluation studies use quantitative and qualitative methods with statistical approaches. Sometimes, in previous studies, machine learning models were utilized conventionally.Design/methodology/approach In the proposed method, the authors use a novel machine learning-based ensemble approach with severity indexes to evaluate the sustainability of the proposed mobile learning system. In this severity indexes, consider the cause-and-effect relationship to identify the hidden correlation among sustainability factors. Also, the proposed novel sustainability evaluation algorithm helps to evaluate and improve sustainability iteratively to have an optimal sustainable mobile learning system. In total, 150 learners and 150 teachers in the university community engaged in the study by taking the sustainability questionnaire. The questionnaire consists of 20 questions that represent 20 sustainable factors in five sustainability dimensions, i.e. economic, social, political, technological and pedagogical.Findings The results reveal that the proposed system has achieved its economic and pedagogical sustainability. However, the results further reveal that the proposed system needs to be improved on technological, social and political sustainability.Originality/value The study focused novel machine learning approach and technique for evaluating sustainability of the proposed mobile learning framework.
机译：目的本研究的目的是评估的可持续性提出移动高等教育的学习框架。可持续发展评价研究使用定量和定性的方法统计方法。研究,利用机器学习模型传统。作者提出的方法,利用一种新型机器上优于整体方法与严重性索引来评估的可持续性提出了移动学习系统。索引,考虑因果关系来识别隐藏的相关性可持续发展的因素之一。小说有助于可持续发展评价算法评估和提高可持续性迭代最优的可持续的移动学习系统。教师在大学社区的参与研究了可持续性问卷调查。代表20可持续因素的问题在五个维度可持续性,即经济、社会、政治、技术和教学。提出系统已经实现了它的经济教学的可持续性。提出了系统需要进一步的揭示改进了技术,社会和政治上的可持续性。机器学习方法和研究小说技术评估的可持续性提出了移动学习框架。

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