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Towards a Model Driven eLearning Framework to Improve Quality of Teaching

机译:建立模型驱动的电子学习框架以提高教学质量

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There is a significant dearth of time and qualified teachers to make 200 million adult illiterates of India spread across 22 Indian Languages literate and it would take massive effort to address the scale and variety challenges. In this paper, we summarize four and half years of our experience of analyzing and improving a decade-long technology to adult literacy problem. Based on this experience and extensive interviews with teachers/learners and with the goal of devising quality instruction at attractive productivity rates through technology, we propose GAMBLE as a unified modelling framework and technical platform to organize instructional material in the form of data (facts, cases, rules and models). Essentially GAMBLE allows learners to perform well at all levels (remember, understand, apply, analyze, evaluate and create) of Bloom'sTaxonomy. We briefly present the case of applying GAMBLE framework to adult literacy and discuss its broad applications for school education as well.
机译:要使2亿印度文盲跨22种印度语文盲传播,需要大量的时间和合格的教师,因此需要大量的精力来应对规模和种类的挑战。在本文中,我们总结了四年半的经验,这些经验用于分析和改进长达十年的技术以解决成人识字问题。基于这一经验和对教师/学习者的广泛访谈,并以通过技术设计出具有吸引力的生产率提高质量指导为目标,我们建议GAMBLE作为统一的建模框架和技术平台,以数据形式(事实,案例)来组织指导材料,规则和模型)。本质上,GAMBLE允许学习者在Bloom的分类法的各个级别(记住,理解,应用,分析,评估和创建)上都表现出色。我们简要介绍了将GAMBLE框架应用于成人扫盲的案例,并讨论了其在学校教育中的广泛应用。

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