Harnessing blended learning data to address the education and attainment gap as a result of Covid-19

利用混合学习数据来解决 Covid-19 造成的教育和成绩差距

• 批准号: 79296
• 金额: $ 22.28万
• 依托单位: TOUCH FANTASTIC LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=79296
• 关键词: Harnessing; blended; learning; data; address

One of the most significant impacts of COVID-19 on the long-term future of the UK has been on the education of our young people.Lockdown is understood to have created two significant types of impacts on students. The first is the attainment/progress gap in the sense of lost learning. Contributing factors to the level of impact are likely to include the particular school's quality and quantity of remote education (or face-to-face provision for vulnerable/key workers' children), the quality and quantity of home learning by parents, and a variety of home background factors including socio-economic, physical environment, access to technology and resources etc.The second type of impact is psychological/interpersonal/developmental. Young people, particularly those who have not been in school throughout lockdown may have also lost acclimation to the school learning environment, structures and routines; interactions with peers; and interactions with teachers. This lost acclimatisation, alongside other difficulties of lockdown life, may have affected their ability to recover lost learning, wider psychosocial development, and mental health/wellbeing.These gaps and factors are currently hypothesised but the extent to which they have affected young people over lockdown is not yet well understood or evidenced. Gathering this understanding and evidence is crucial to ensure the current cohort of students do not become a lost generation, with long term detrimental effects on them, wider society, and the national workforce and economy.We have a unique opportunity at this moment in history to analyse learning and development gaps in school children through the use of remote/blended learning data. Never has so much educational activity taken place on digital learning platforms as over the past few months.Sparkjar -- our world-leading UK-based blended learning platform for schools -- saw +700% in usage during lockdown. Throughout lockdown, our two testbed secondary schools using have run full teaching timetables throughout, exchanged 170,000+ messages, set 9,000+ assignments, and 69,000+ pieces of work have been submitted by students.Not only is this quantity of data remarkable, but its quality and completeness are unprecedented because the schools have been using Sparkjar as their primary means of interaction for a number of months. Never before has there been a data set as rich to analyse patterns in learning and behaviour in the context of mainstream education.At the same time, we are at a point where the fields of machine learning and big data permit an unprecedented depth of analysis of large data sets.Our vision is to harness the power and value of this unique data, providing schools with a realtime dashboard of insights into student learning, progress, behaviour and mental wellbeing. We call this Sparkjar Realtime Insights (SRI). We will leverage cutting-edge machine learning, expert systems, statistical analysis and data visualisation in order to spot patterns and anomalies, and provide realtime actionable insights at three levels of granularity: individual student, student groups, and whole-school. This will represent a quantum leap in school data analysis for schools when compared to current best practice of termly manual reporting and spreadsheet analysis.

新冠肺炎对英国长远未来最重大的影响之一就是对我们年轻人的教育。据了解，封锁对学生产生了两种重大影响。第一个是失学意义上的成就/进步差距。影响程度的因素可能包括特定学校远程教育的质量和数量(或为弱势/关键工人的子女提供面对面的教育)、家长在家学习的质量和数量，以及各种家庭背景因素，包括社会经济、物质环境、获得技术和资源的机会等。第二类影响是心理/人际/发展。年轻人，特别是那些在整个封锁期间没有在学校学习的人，也可能对学校的学习环境、结构和惯例、与同龄人的互动以及与老师的互动失去了适应。这种无法适应的生活，加上禁闭生活的其他困难，可能影响了他们恢复失去的学习、更广泛的心理社会发展和心理健康/福祉的能力。这些差距和因素目前是假设的，但它们在禁闭期间对年轻人的影响程度尚未得到很好的理解或证据。收集这种理解和证据至关重要，以确保当前的学生群体不会成为迷失的一代，对他们、更广泛的社会、国家劳动力和经济产生长期有害的影响。在历史的这个时刻，我们有一个独特的机会，可以通过使用远程/混合学习数据来分析学童的学习和发展差距。在过去的几个月里，数字学习平台上从未发生过如此多的教育活动。Sparkjar--我们位于英国的全球领先的学校混合学习平台--在封锁期间的使用率超过了700%。在整个封锁期间，我们使用的两所试验床中学始终运行着完整的教学时间表，交换了17万多条信息，设置了9000多项作业，学生提交了6.9万多项作业。不仅数据数量惊人，而且其质量和完整性是前所未有的，因为几个月来，这两所学校一直将Sparkjar作为他们主要的互动手段。在主流教育的背景下，从来没有如此丰富的数据集来分析学生的学习和行为模式。与此同时，机器学习和大数据领域允许对大数据集进行前所未有的深度分析。我们的愿景是利用这些独特数据的力量和价值，为学校提供一个实时的仪表盘，深入了解学生的学习、进步、行为和心理健康。我们称之为Sparkjar Realtime Insights(SRI)。我们将利用尖端机器学习、专家系统、统计分析和数据可视化来发现模式和异常，并在三个粒度级别提供实时可操作的见解：个人学生、学生群体和整个学校。与目前定期手动报告和电子表格分析的最佳实践相比，这将代表着学校在学校数据分析方面的巨大飞跃。