Digital EducationOutlook 2021（Ⅲ）

Frontiers of smart education technology： opportunities and challenges

Smart data and digital technology in education

Digitalisation opens new possibilities for education. However， most uses of innovative technology have been to conserve existing educational practice and sometime enrich it， but rarely transform it. Might digital technology， and， notably， smart technologies based on artificial intelligence， learning analytics， robotics， and others， transform education in the same ways they are transforming the rest of society？ If so， how might this look like？

Key opportunities

Smart technologies can improve education systems and education delivery in different ways. They can enhance access to education， improve its quality for learners， and enhance its cost-efficiency for societies.

Effectiveness

In the classroom， applications that directly support student learning show early promise. Personalised learning aims to provide all students with the appropriate curriculum or task， and scaffold them within a task， based on a diagnosis of their knowledge and knowledge gaps. This is not only done at the academic level， focusing on the “what”， but increasingly takes into account how students learn and factors such as self-regulation， motivation or effort.

A second promise of learning effectiveness comes from classroom analytics that support teachers in providing more effective teaching. Many applications already show how a variety of solutions could support teachers in better using their time in class， for example， by suggesting when it is a good time to shift to the next teaching or learning activity， who would require their attention the most， how they could engage the whole class in collaborative learning activities.

At the organisational and system levels， smart technologies also hold promise in making education more effective. While this remains relatively rare， smart technologies can be integrated in most dimensions of school activities， providing administrators， teachers and learners with feedback to manage school resources as well as improve the effectiveness of teaching and learning.

Equity

Smart technologies can help education systems provide more equitable learning opportunities. In this respect， smart technologies are more ambivalent. On the one hand， they clearly do or could help reduce inequity both by increasing access to learning opportunities for all and improving learning effectiveness for those who need it the most. On the other hand， without a widespread and equitable availability of smart technologies， inequity could also rise.

There are at least two reasons why technology may have a negative effect on equity. The first， obvious reason lies in the difference in access to devices and connectivity by students from different groups， notably students from lower socio-economic backgrounds. These students may not have the devices， the connectivity or the resources that allow accessing and using smart technologies either at the school they attend or at home. A second reason is that， if technology （e.g. personalised learning） works the same for everyone， those who start with stronger prior knowledge can maintain their advantage or even make faster progress than those with less prior knowledge. This would widen rather than reduce the achievement gap.

There are also many reasons to believe that smart technologies can advance the equity agenda.

First， learning technology can expand access to learning opportunities. Educational platforms proposing open educational resources or massive open online course （MOOC） platforms are good examples. They allow learners to access learning materials with a quality that may be superior to what they can access locally.

As importantly， smart technologies can reduce inequity by facilitating the inclusion of students with special needs and by adapting learning to different learning styles. Technology has， for example， made it much easier to support the diagnosis of learning difficulties such as dysgraphia， and remedial digital responses have also been developed.

Second， solutions such as early warning systems are entirely focused on reducing inequity by helping students at risk of dropping out from high school （or university） to graduate - students who drop out typically come from disadvantaged and minority backgrounds. Some use of learning analytics within institutions， for example， to monitor student engagement or redesign study programmes， could also have the same effects， should the educational institution pay particular attention to inequity.

Third， the use of learning analytics as exemplifed by personalisation at the individual level， be it using intelligent tutoring systems or learning analytics to keep students engaged in learning， all hold promise in reducing inequity， notably by supporting students with less prior knowledge to learn at the right pace.

譯文

智能教育技术前沿：机遇与挑战

教育中的智能数据和数字技术

数字化为教育带来了新的可能性。然而，创新技术的大多数用途是为了保护现有的教育实践，或是丰富现有的教育实践，很少有技术改变现有的教育实践。数字技术，尤其是基于人工智能、学习分析、机器人和其他技术的智能技术，是否会像改变社会其他部分一样改变教育？如果是这样，将会是什么样子？

关键机会

智能技术能以不同的方式改善教育系统和教育服务。它们可以增加接受教育的机会，提高学习者的教育质量，提高社会的成本效益。

有效性

在课堂上，直接支持学生学习的应用程序率先显示出前景。个性化学习旨在为所有学生提供适当的課程或任务，并根据对学生知识水平和知识差距的诊断，在任务中为他们提供支持。这不仅要在学术层面进行应用，重点是应用“什么”，而且要越来越多地考虑学生的学习方式以及自我调节、动机或努力等因素。

学习效率的第二个前景是课堂分析，提供更有效的教学以支持教师。许多应用程序已经表明，多种解决方案可以帮助教师更好地利用课堂时间，例如，给出转移到下一个教学或学习活动好时机的建议，谁最需要他们的注意力，他们如何让全班参与协作学习活动。

在组织和系统层面，智能技术也有望使教育更加有效。虽然这仍然相对少见，但智能技术可以整合学校活动的大多数方面，为管理者、教师和学习者提供反馈，管理学校资源，提高教学和学习的效率。

公平性

智能技术可以帮助教育系统提供更公平的学习机会。但在这方面，智能技术更加矛盾。一方面，它们增加了所有人获得学习机会的途径，提高了有强烈需求的人的学习效率，或多或少地减少了不平等。另一方面，如果智能技术得不到广泛和公平的使用，不平等问题也可能加剧。

技术可能对公平性产生负面影响的原因至少有两个。第一个明显的原因在于不同群体的学生，尤其是社会经济背景较差的学生，在使用设备和网络连接方面存在差异。这些学生可能没有设备、网络连接或资源，无法在他们就读的学校或家中访问和使用智能技术。第二个原因是，如果技术（如个性化学习）对每个人都适用，那些事先具备较强知识的人可以保持优势，甚至比那些具备较少知识的人进步更快。这将扩大而不是缩小成就差距。

但还有很多理由相信智能技术可以推进公平事项。

第一，学习技术能扩大获得学习机会的途径。开放教育资源的教育平台或大规模开放在线课程（MOOC）平台就是很好的例子。它们允许学习者访问学习材料，其质量可能优于他们在当地可以获得的资源。

同样重要的是，智能技术能促进有特殊需要的学生的参与，学习适应不同的学习风格，从而减少不平等。例如，技术使得诊断书写困难等学习障碍变得更加容易，并且还开发了补救性数字响应。

第二，早期预警系统等解决方案完全着眼于通过帮助高中（或大学）到研究生阶段辍学的学生减少不平等现象（辍学学生通常来自弱势群体或有少数民族背景）。如果教育机构特别关注不平等问题，那么在机构内部使用学习分析技术来监控学生参与度或重新设计学习计划，也可能产生同样的效果。

第三，学习分析的使用，如个人层面的个性化，无论是使用智能辅导系统还是学习分析来让学生参与学习，都有助于减少不平等，特别是支持先前知识较少的学生以正确的速度学习。