面向发展中国家的大规模学习:来自全球学习XPRIZE实地研究的经验教训

Andrew A. Mcreynolds, Sheba P. Naderzad, Mononito Goswami, Jack Mostow
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引用次数: 6

摘要

教育技术的进步使大规模学习取得了巨大进步。然而,他们通常会使用发达国家认为理所当然的资源,包括可靠的电力、高带宽的互联网接入、快速的WiFi、功能强大的计算机、复杂的传感器和专业的技术支持,以保持一切正常运行。本文在一个发展中国家大规模学习测试的背景下检验了这些假设。我们研究了每个假设,它是如何被打破的,以及一些变通方法,并对坦桑尼亚168个村庄的2000多名儿童进行了为期15个月的测试前后学习和社交情感收益的独立对照评估。我们使用考试成绩数据、社交情绪测量和RoboTutor的详细日志来分析这些收益,以确定谁获得了多少收益。我们量化了考试前分数、识字愿望、治疗和使用对学习收益的相对影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward Learning at Scale in Developing Countries: Lessons from the Global Learning XPRIZE Field Study
Advances in education technology are enabling tremendous advances in learning at scale. However, they typically assume resources taken for granted in developed countries, including reliable electricity, high-bandwidth Internet access, fast WiFi, powerful computers, sophisticated sensors, and expert technical support to keep it all working. This paper examines these assumptions in the context of a massive test of learning at scale in a developing country. We examine each assumption, how it was broken, and some workarounds used in a 15-month-long independent controlled evaluation of pre- to posttest learning and social-emotional gains by over 2,000 children in 168 villages in Tanzania. We analyze those gains to characterize who gained how much, using test score data, social-emotional measures, and detailed logs from RoboTutor. We quantify the relative impact of pretest scores, literate aspirations, treatment, and usage on learning gains.
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