听众朋友们好，欢迎来到美国教育播客华语节目，我是曼琳。华语节目很自豪能成为美国领先的教育播客网络的一部分。我们用汉英双语为您讲解美国教育的最新动态，以及美国和世界范围内的教育家和企业家们的深刻见解，并为您带来更多的精彩。美国节目先用汉语剥奖，然后用英语重播相同的内容。
大家好，在当天世界，尤其在美国，高等教育正处于快速转型期，他需要以创新的方式应对劳力市场瞬息万变的现实，而在线的专业发展和继续教育正是这一转型的前沿。美国教育播客《在线专业和继续教育》这个节目的主持人、加拿大安大略省伦敦的安大略西部大学继续教育部执行主任Amrit Ahluwalia，在他的第11集里采访了在线专业和继续教育专家、斯坦福大学负责数码教育的副教务长Rascoff（拉斯科夫）先生。他们就各自学校如何积极主动敏捷地发挥在线专业和继续教育的先锋作用，进行了精彩的讨论，并共同探讨了人工智能及AI应用在高等教育中的局限和潜能，以及他未来的希望。很遗憾，我们短小的节目今天只能为大家测众介绍其中的某些重要部分。主持人和受访嘉宾的讨论很精彩。刚开头，当被问及在高等教育领域迎遇到与人工智能相关的最大误解是什么时，Rascoff先生就认为，人工智能似乎并没有达到我们所设想的革命性变化。Amrit Ahluwalia先生也提出了发言身形的问题：生存式人工智能到底是在寻找真正创新的做事方式，还是目前在很大程度上，只是在寻找变结高效的方式，去做人们已经在做的事情？换言之，人工智能本身及其应用是具有局限性的。在Rascoff先生看来，由于互联网资讯的高度发达，今天人们获取知识的方式与过去相比已经发生了很大的变化，但是让一个人获取知识本身，或者这个层级的所谓个性化学习，远非完整的教育过程。目前人们并没有看到，因为AI的出现，完整的教育过程和与之相关联的劳动就业和财富创造体系，发生根本性的革命性的质变和大规模的量变，至少现在没有。当被问及您能否举例说明什么是高等教育领域发生的革命性变化时，来自斯坦福的嘉宾Rascoff先生说，在线学习就是一个革命性的变化。
在过去的25年里，他渗透到了整个高等教育体系。他把最优化的教育资源，向所有各层次各类别的学校开放，向所有人开放，是教育变得前所未有的公平和容易获得，这就是一种根本性的转变。如果我们回想远程教学，从通过电子邮件发送录像带，或者电视讲座到现在，如今他已经实现了真正意义上的远程，他向人们接受了什么是教育上的革命性转变。再加上AI的助力，在线学习的质量可能还会继续提高。在Rascoff先生看来，相比个性化学习，今天更需要的是共同学习，让人们在不同的背景、种族和观点之间架起桥梁，建立社区，及有意义的参与，相互学习，重新思考每个人的假设，并以深思熟虑的方式，让个人接触差异，并制定更好的规则。但很显然，这不是通过人工智能的算法能够实现的，他也不会是消费者驱动的。任志科学有一个概念，叫做理想难度，意思是，我们在学习中面临的一些挑战，并不会自然地让人感觉良好，就像一道菜，他们对身体健康好，但味道不一定好。如果我们只是围绕消费者的偏好去设计学习系统，这样的系统可能不会引导求知者去解决难题，从而化解成长的困境，而是指照顾学习者的情绪和感觉，那他们最终只会得到一种快餐式的学习模式，而非健康饮食式的学习，及以发展人的批判性思维及综合能力为本的完整教育。在我看来，教育过程中需要照顾独立个体的需求，而共同学习，则是更高层子和更广意义上的学习，是培养人的综合能力不可或缺的一步。虽然目前，AI还没有更好的算法，能在这个层面和广度上，为教育带来技术上的革命性变化，但上述两位系统教育、又熟悉生成是AI应用的专家，深入探讨了AI在高等教育领域的巨大潜能。比如，怎样应用AI改革教育评估，推广教学中即时可靠高质高效和更加专业化的形成是评估。
又比如，怎样利用AI创建更好的师身之间积极互动的教学模式。哈佛商学院的创业课程正在出色的进行这方面的研究，而非仅仅只是让学生学会用ChatGPT和生成是AI去为某个或某些已经在进行的原有项目提高效率。受访嘉宾斯坦福大学的Rascoff先生说，他希望将来高校会以校际和社区联盟的形式，以高度协作的方式，在通用的AI平台上，打造一整个专属于教育的运用层面。这样的讨论急剧动查例，他竟然让人看清目前AI的局势，又让人对AI的巨大潜能打开思路。亲爱的听众朋友们，您觉得呢？感谢您的收听，我们下次再聊。
哈喽, welcome to Adult Pink Chinese. I am a man. About Edit Pink Chinese is a very probably to be part of American leading education podcasts, the network. The Adult Experience adopy Chinese talks in both Chinese and English to the audience about latest happening in American education, sharing the deep insights of educators and entrepreneurs in the United States and in the world 和更多更多. Each episode is broadcasted in Mandarin first, then English for the same content.
Hello everyone, in today's world is badly in the United States, higher education is in a period of rapid transformation that requires innovative ways to respond to changing reality of the labor market, while online professional and continuing education is at the forefront of this transformation. Mr. Amrit Ahluwalia, the host of the ad of online professional and continuing education and executive director of professional continuing online education at Western University in London, Ontario, Canada, in his 11th episode interviewed Mr. Matthew Rascoff, Vice Provost of Digital Education of Stanford University. They had a wonderful discussion on how their respective schools can actively and actually play a pioneering role in PCO.
They jointly discussed the limitations and the potential of AI. They also talked about the applications of AI in higher education and also look forward the future development of AI. Unfortunately, our short program can only focus on some of them today. The discussion between the host and the guest was wonderful. At the very beginning, when asked what is the biggest misconception you encounter about AI in higher education, Mr. Rascoff felt that AI does not seem to be the revolutionary change we thought it would be. Mr. Ahluwalia also raised a thought-provoking question: is generative AI looking for truly innovative ways to do things, or is it currently just looking for a better, more efficient way to do things that people are already doing?
In other words, AI itself and its applications have limits. According to Mr. Rascoff, the way people acquired knowledge today has changed a lot compared to the past because of the highly developed information on the internet, but allowing a person to acquire knowledge by himself, or so-called personalized learning, is far from a true and complete education. At present, people have not seen that the real complete education and related labor employment and the whole social wealth creation system have undergone qualitative and large scale quantitative, fundamental and revolutionary changes due to the emergence of AI, at least not yet. When asked, can you give an example of what is a revolutionary change in higher education?
Mr. Rascoff, the guest from Stanford, said online learning is a revolutionary change. Over the past 25 years, it has permeated the entire higher education system. It opens optimized educational resources to schools of all levels and kinds, and to everyone. This has been making education more equitable and accessible than ever before, so it is a fundamental change. If we think back to distance teaching, from sending video tapes via email or television lectures to now, it has become truly remote. It reveals to people what is a revolutionary change in education is. And with the help of AI, the quality of online learning may continue to be improved. And Mr. Rascoff's view, what is needed today is not personalized learning,
but rather is co-learning, which allows people to build bridges between different backgrounds, races and perspectives, and to build community, which means engaging meaningfully, learning from each other and rethinking different opinions, to hypothesize, to explore people to differences in a thoughtful way, and to create better rules. But of course, this will not be achieved by AI algorithms, nor will it be the choice of the consumers. In cognitive science, there is a concept called desirable difficulty. It means that people don't naturally feel good when they face some challenges in learning, like some foods, they are good for your health but they don't necessarily taste good. If we only design a learning system based on consumer preferences,
such a system may not lead learners to find a better way to solve difficulty in a self-growth process, but only take care of learner's feelings. In the end, they will not only get a fast food learning model instead of a healthy food learning model, which is a complete education based on developing people's critical thinking and comprehensive ability.
Although in education we need to meet every individual needs, co-learning is at a higher level and has broader sense. It is an indispensable part in calculating people's comprehensive abilities. Even though there is currently no better algorithm of AI that can bring technologically revolutionary changes to education at this level and the breadth, these two experts who know both education and a generated AI applications discussed in depth the huge potential of AI in higher education. For example, the application of AI to reform assessment system and promote timely, reliable, high quality and more professional formative assessment in teaching. Also, how to use AI to create a better teaching model of active interaction between teachers and students.
Harvard Business School's entrepreneurship course is very well-conducted research in this area, rather than just letting students learn to use ChatGPT and generative AI to improve efficiency for some projects that are already on the way. Interviewed guest, Mr. Rascoff of Stanford University, said that he hopes that in the future universities will use inter-school and community alliance to create an entire dedicated education application layer on a common AI platform in a highly collaborative manner. Yes, I think today's discussion is very enlightening. It not only allows people to clearly see the limitations of current AI and its application, but also opens people's minds to the huge potential of AI in the future.
Dear listeners, what do you think? Thanks for tuning in, and I'll see you next time.