Reading into Writing Source pack: Pre-sessional 2025 阅读写作资源包：2025年学前班
MANCHESTER
1824 曼彻斯特
1824
The University of Manchester 曼彻斯特大学
IMPORTANT: PLEASE READ BEFORE USING THE SOURCE PACK 重要提示：请在使用源包前阅读
Below are THREE sources for your Reading into Writing assessment. 以下是对阅读到写作进行评估的三个来源。
Do NOT translate or use these sources in a way that may result in academic malpractice or copyright infringements. Your reading score is based on how you use this source pack. It is therefore important that all interpretations and use of the source pack are your own. Please see the criteria and marking rubric in the handbook for more information. 请勿以可能导致学术不端或侵犯版权的方式翻译或使用这些资料。您的阅读分数取决于您如何使用此资料包。因此，请务必自行解释和使用资料包。更多信息，请参阅手册中的评分标准和评分细则。
The three sources have been edited under a Creative Commons BY licence for the purpose of the 2025 presessional assessment and should ONLY be used for this purpose. Because these sources have been edited, they do not contain the same details as the original sources. You must therefore only use this source pack and not the original sources to write your essay. 这三个资料已根据知识共享许可协议 (Creative Commons BY) 编辑，用于 2025 年会前评估，仅供此用途使用。由于这些资料经过编辑，因此其包含的信息与原始资料有所不同。因此，您必须仅使用此资料包，而非原始资料来撰写论文。
All sources total approximately 9,500 words. 所有资料总计约 9,500 个单词。
Sources: 资料来源：
Source 1: ‘Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators’ Weng Marc Lim, Asanka Gunasekara, Jessica Leigh Pallant, Jason Ian Pallant, Ekaterina Pechenkina, The International Journal of Management Education, Volume 21, Issue 2, 2023. 来源 1：《生成式人工智能与教育的未来：诸神黄昏还是改革？来自管理教育者的矛盾视角》Weng Marc Lim、Asanka Gunasekara、Jessica Leigh Pallant、Jason Ian Pallant 和 Ekaterina Pechenkina，《国际管理教育杂志》，第 21 卷，第 2 期，2023 年。
Source 2: ‘Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education’ Yun Dai, Ang Liu, Cher Ping Lim, Procedia CIRP, Volume 119, 2023, Pages 84-90, (2023) 来源 2：《将 ChatGPT 和生成式 AI 重新概念化为高等教育中学生驱动的创新》Yun Dai、Ang Liu、Cher Ping Lim，Procedia CIRP，第 119 卷，2023 年，第 84-90 页，(2023 年)
Source 3: ‘Students’ voices on generative AI: perceptions, benefits, and challenges in higher education’ Chan, C.K.Y., Hu, W. International Journal of Educational Technology in Higher Education 20, 43 (2023). 来源 3：《学生对生成性人工智能的声音：高等教育中的看法、好处和挑战》Chan, CKY, Hu, W.《高等教育国际教育技术杂志》20, 43 (2023)。
Please note: the above references are NOT in Manchester Harvard style. You must consult the appropriate style guide for information on how to reference these sources. 请注意：以上参考文献并非采用曼彻斯特哈佛格式。您必须参考相应的格式指南，了解如何引用这些资料。
For direct quotations, please refer to the page numbers in this source pack and NOT the original source. 对于直接引用，请参考此源包中的页码，而不是原始来源。
Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators 生成式人工智能与教育的未来：诸神黄昏还是改革？来自管理教育者的矛盾视角
Weng Marc Lim ^(a,b,c,^(**)){ }^{\mathrm{a}, \mathrm{b}, \mathrm{c},{ }^{*}}, Asanka Gunasekara ^(b){ }^{\mathrm{b}}, Jessica Leigh Pallant ^(b){ }^{\mathrm{b}}, Jason Ian Pallant ^("b "){ }^{\text {b }}, Ekaterina Pechenkina ^("d "){ }^{\text {d }} Weng Marc Lim ^(a,b,c,^(**)){ }^{\mathrm{a}, \mathrm{b}, \mathrm{c},{ }^{*}} 、Asanka Gunasekara ^(b){ }^{\mathrm{b}} 、Jessica Leigh Pallant ^(b){ }^{\mathrm{b}} 、Jason Ian Pallant ^("b "){ }^{\text {b }} 、Ekaterina Pechenkina ^("d "){ }^{\text {d }}^(a){ }^{a} Surnway Business School, Surway University, Sumway City, Selangor, Malaysia ^(a){ }^{a} 马来西亚雪兰莪州萨姆韦市萨姆韦大学萨姆韦商学院^("b "){ }^{\text {b }} School of Business, Law and Entrepreneurship, Swinburne University of Technology, Hawthorn, Vietoria, Australia ^("b "){ }^{\text {b }} 澳大利亚维多利亚州霍索恩市斯威本科技大学商学院、法律学院和创业学院^("c "){ }^{\text {c }} Faculty of Business, Design and Arts, Swinburne University of Technology Sarawak Campus, Kuching, Sarawak, Malaysia ^("c "){ }^{\text {c }} 马来西亚砂拉越州古晋斯威本科技大学砂拉越校区商业、设计与艺术学院^(d){ }^{\mathrm{d}} Learning Transformations Unit, Swinburne University of Technology, Hawthorn, Victoria, Australia ^(d){ }^{\mathrm{d}} 澳大利亚维多利亚州霍索恩市斯威本科技大学学习转型部门
Abstract 抽象的
Generative artificial intelligence (AI) has taken the world by storm, with notable tension transpiring in the field of education. Given that Generative AI is rapidly emerging as a transformative innovation, this article endeavors to offer a seminal rejoinder that aims to (i) reconcile the great debate on Generative AI in order to (ii) lay the foundation for Generative AI to co-exist as a transformative resource in the future of education. Using critical analysis as a method and paradox theory as a theoretical lens (i.e., the “how”), this article (i) defines Generative AI and transformative education (i.e., the “ideas”), (ii) establishes the paradoxes of Generative AI (i.e., the “what”), and (iii) provides implications for the future of education from the perspective of management educators (i.e., the “so what”). Noteworthily, the paradoxes of Generative AI are four-fold: (Paradox #1) Generative AI is a ‘friend’ yet a ‘foe’, (Paradox #2) Generative AI is ‘capable’ yet ‘dependent’, (Paradox #3) Generative AI is ‘accessible’ yet ‘restrictive’, and (Paradox #4) Generative AI gets even more ‘popular’ when ‘banned’ (i.e., the “what”). Through a position that seeks to embrace rather than reject Generative AI, the lessons and implications that emerge from the discussion herein represent a seminal contribution from management educators on this trending topic and should be useful for approaching Generative AI as a game-changer for education reformation in management and the field of education at large, and by extension, mitigating a situation where Generative AI develops into a Ragnarök that dooms the future of education which management education is a part of (i.e., the “so what”) 生成式人工智能 (AI) 席卷全球，教育领域也随之出现了显著的紧张局面。鉴于生成式人工智能正迅速崛起成为一项变革性创新，本文力图提出一项开创性的反驳，旨在 (i) 调和关于生成式人工智能的广泛争论，从而 (ii) 为生成式人工智能在未来教育中作为变革性资源共存奠定基础。本文以批判性分析为方法，以悖论理论为理论视角（即“如何”），(i) 定义生成式人工智能和变革性教育（即“理念”），(ii) 阐明生成式人工智能的悖论（即“是什么”），以及 (iii) 从管理教育者的角度探讨对未来教育的启示（即“那又怎样”）。值得注意的是，生成人工智能的悖论有四个方面：（悖论 1）生成人工智能是“朋友”又是“敌人”，（悖论 2）生成人工智能“有能力”但却“依赖”，（悖论 3）生成人工智能“可访问”但却“受限制”，以及（悖论 4）当生成人工智能被“禁止”（即“什么”）时，它会变得更加“受欢迎”。通过寻求拥抱而不是拒绝生成式人工智能的立场，本文讨论中得出的经验教训和启示代表了管理教育者对这一热门话题的开创性贡献，并有助于将生成式人工智能视为管理教育改革和整个教育领域的游戏规则改变者，进而缓解生成式人工智能发展成为毁灭教育未来的诸神黄昏的局面，而管理教育是教育的一部分（即“那又怎样”）。
1. Introduction and background 1. 简介和背景
Generative artificial intelligence (AI) is a distinct class of AI and an incredibly powerful technology that has been popularized by ChatGPT.1. Developed by OpenAI, ChatGPT acquired one million users in five days and reached 100 million users two months after it was made public in November 2022, setting the record for the fastest-growing consumer application (Hu, 2023). 2 As a chatbot driven by Generative AI, 3 ChatGPT shocked the world with its ability to understand complex and varied human languages and generate rich and structured human-like responses. DALL-E is another example of Generative AI developed by OpenAl that works in a similar way to ChatGPT albeit with digital images as outputs. Both ChatGPT and DALL-E are products of deep learning (OpenAl, 2023), which is a subset of machine learning that mirrors the human brain in learning and responding to data, information, and prompts (Sahoo et al., 2023). Google has responded rapidly by announcing their own Generative Al, Bard, which is powered by next-generation language and conversation capabilities such as Language Model for Dialogue Applications (LaMDA) (Pichai, 2023). Therefore: 生成式人工智能 (AI) 是人工智能 (AI) 中一个独特的类别，也是一项极其强大的技术，ChatGPT 的出现使其广为人知。ChatGPT 由 OpenAI 开发，在五天内就获得了 100 万用户，并在 2022 年 11 月公开两个月后达到 1 亿用户，创下了增长最快的消费级应用纪录 (Hu, 2023)。ChatGPT 是一款由生成式人工智能驱动的聊天机器人，其能够理解复杂多样的人类语言，并生成丰富且结构化的类人响应，震惊了世界。DALL-E 是 OpenAI 开发的另一个生成式人工智能示例，其工作方式与 ChatGPT 类似，但输出的是数字图像。ChatGPT 和 DALL-E 都是深度学习 (OpenAI, 2023) 的产物。深度学习是机器学习的一个子集，它能够模拟人脑学习和响应数据、信息和提示 (Sahoo et al., 2023)。谷歌迅速做出反应，宣布推出自己的生成式人工智能系统 Bard，该系统基于下一代语言和对话功能，例如对话应用语言模型 (LaMDA) (Pichai, 2023)。因此：
Generative AI can be defined as a technology that (i) leverages deep learning models to (ii) generate human-like content (e.g., images, words) in response to (iii) complex and varied prompts (e.g., languages, instructions, questions). 生成式人工智能可以定义为一种技术，它 (i) 利用深度学习模型 (ii) 根据 (iii) 复杂多样的提示（例如，语言、指令、问题）生成类似人类的内容（例如，图像、文字）。
As a group that is often accused of being conservative and resistant to change (Marks & AI-Ali, 2022), it is unsurprising to see many educators voicing concerns about Generative AI, particularly around assessment and ethical issues such as originality and plagiarism (Chatterjee & Dethlefs, 2023; Stokel-Walker, 2022). At the time of writing, it is noteworthy that many governments and schools have banned Generative AI tools such as ChatGPT amid fears of AI-assisted cheating (ABC News, 2023; Dibble, 2023; Lukpat, 2023) while the same is observed in academic publishing (Nature, 2023). 教育工作者经常被指责为保守且抗拒变革（Marks & AI-Ali, 2022），因此看到许多教育工作者对生成式人工智能表示担忧也就不足为奇了，尤其是在评估和原创性与抄袭等伦理问题上（Chatterjee & Dethlefs, 2023; Stokel-Walker, 2022）。值得注意的是，在撰写本文时，许多政府和学校出于对人工智能辅助作弊的担忧，已经禁止使用 ChatGPT 等生成式人工智能工具（ABC News, 2023; Dibble, 2023; Lukpat, 2023），学术出版领域也出现了同样的情况（Nature, 2023）。
With Generative AI rapidly emerging as a transformative innovation along with the likes of the internet and the smartphone, there is now a golden opportunity to truly reimagine and transform the future of education (i.e., the “importance”), and with the likes of ChatGPT co-authoring and publishing journal articles (e.g., Ali & OpenAI Inc, 2023; O’Connor & ChatGPT, 2023), educators must inevitably transition into a future of education where Generative Al is embraced rather than shunned (i.e., the “urgency”). 随着生成性人工智能与互联网、智能手机等一起迅速崛起成为一项变革性创新，现在有一个黄金机会来真正重新构想和改变教育的未来（即“重要性”），并且随着 ChatGPT 等共同撰写和发表期刊文章（例如 Ali & OpenAI Inc, 2023；O'Connor & ChatGPT, 2023），教育工作者必须不可避免地过渡到接受而不是回避生成性人工智能的教育的未来（即“紧迫性”）。
This article offers a seminal contribution from the perspective of management educators and highlights the potential for Generative AI to co-exist as a transformative resource in education, thereby supporting endeavors that approach Generative AI as a game-changer for education reformation, and by extension, mitigating a situation where Generative AI develops into a Ragnarök " that dooms the future of education which management education is a part of (i.e., the “so what”). 本文从管理教育者的角度提供了开创性的贡献，并强调了生成性人工智能作为教育变革资源共存的潜力，从而支持将生成性人工智能作为教育改革游戏规则改变者的努力，并进而缓解生成性人工智能发展成为“诸神黄昏”的局面，这种局面注定会毁掉管理教育所属的教育的未来（即“那又怎样”）。
2. The paradoxes of generative Al and the future of education 2. 生成性人工智能的悖论与教育的未来
Current discourse surrounding Generative AI and its impact on education tends to focus on the challenges it creates for educators (e. g., Stokel-Walker, 2022; Terwiesch, 2023) or the opportunities it presents for educators and students alike (e.g., Pavlik, 2023; Zhai, 2022). At their extremes, the former position views Generative AI as a form of Ragnarök, bringing about the destruction of the education system, while the latter sees it as a reformation, bringing a new dawn of accessible information and automation to enhance the footprint and quality of education. These two views highlight the inherently paradoxical nature of Generative AI and its role in education; it could destroy some education practices while at the same time supporting them. To explore these conflicting ideologies, we present four key paradoxes of Generative AI in education, including some hands-on practical examples, which, in turn, offer useful lessons and implications for the future of education. 2.1. 当前围绕生成人工智能及其对教育影响的讨论往往集中在它给教育者带来的挑战（例如，Stokel-Walker，2022 年；Terwiesch，2023 年）或它为教育者和学生带来的机遇（例如，Pavlik，2023 年；Zhai，2022 年）。前一种观点认为生成人工智能是“诸神黄昏”的预兆，会摧毁教育体系；而后一种观点则认为生成人工智能是一场改革，带来了可访问信息和自动化的新曙光，以扩大教育覆盖面并提升教育质量。这两种观点凸显了生成人工智能及其在教育中作用的内在矛盾性；它既可以摧毁某些教育实践，也可以支持它们。为了探讨这些相互冲突的意识形态，我们提出了生成人工智能在教育中的四个关键悖论，包括一些实际案例，这些案例反过来又为教育的未来提供了有益的经验教训和启示。2.1.
2.1 Paradox #1: Generative AI is a 'friend' yet a 'foe' 2.1 悖论1：生成式人工智能是“朋友”，也是“敌人”
Early research suggests that ChatGPT, as a specific example of Generative AI, can be used as a tool to facilitate knowledge acquisition and support writing tasks such as codes, essays, poems, and scripts (Chatterjee & Dethlefs, 2023; Terwiesch, 2023; Zhai, 2022). Within a short period, ChatGPT has demonstrated its remarkable ability to generate human-like responses in almost all disciplines. Feedback from early users suggests that many are surprised and impressed by how fast the tool learns from and responds to human interactions (Terwiesch, 2023). Yet, where elevation of knowledge is concerned, Generative AI tools may pose challenges for educators, especially those in research-intensive higher education institutions, in ascertaining whether knowledge presented by students, and even peers, is truly novel (e.g., new insight emerging from a critical analysis of information) or, in fact, recycled (e.g., basic copying and pasting to advanced paraphrasing of AI-generated answers). Critics such as Noam Chomsky (Open Culture, 2023) have suggested that Generative AI tools such as ChatGPT are essentially ‘high-tech plagiarism’ and ‘a way of avoiding learning’, but is this truly the case, or should we be viewing this an opportunity to rethink how we learn and evaluate information? 早期研究表明，作为生成式人工智能的一个具体例子，ChatGPT 可用作促进知识获取和支持代码、散文、诗歌和脚本等写作任务的工具（Chatterjee & Dethlefs，2023；Terwiesch，2023；Zhai，2022）。在短时间内，ChatGPT 已展示出其在几乎所有学科中生成类似人类反应的卓越能力。早期用户的反馈表明，许多人对该工具从人机交互中学习和响应的速度感到惊讶和印象深刻（Terwiesch，2023）。然而，就知识提升而言，生成式人工智能工具可能会给教育工作者，尤其是研究密集型高等教育机构的教育工作者带来挑战，他们需要确定学生甚至同学所呈现的知识是真正新颖的（例如，从批判性分析信息中获得的新见解），还是实际上只是回收利用的（例如，从基本的复制粘贴到对人工智能生成的答案的高级释义）。诺姆·乔姆斯基（Noam Chomsky）（《开放文化》，2023 年）等批评家认为，ChatGPT 等生成式人工智能工具本质上是“高科技抄袭”和“一种逃避学习的方式”，但事实真的如此吗？或者我们应该将此视为重新思考我们如何学习和评估信息的机会？
Moreover, the diffusion of Generative AI at scale could potentially spell the end of some assessment types such as essays (Zhai, 2022). After all, if a Generative AI tool like ChatGPT can offer detailed and human-like responses to advanced essay questions, then what is the role of human learning and insight in responding to these types of assessments? As an example of this challenge, ChatGPT successfully passed graduate-level business and law exams (Kelly, 2023), and even parts of medical licensing assessments (Hammer, 2023), which has led to suggestions for educators to remove these types of assessments from their curriculum in exchange for those that require more critical thinking (Zhai, 2022). In this regard, the advancement of technology through the rise and proliferation of Generative AI tools could elevate the rigor in the assessment of knowledge, though it could also threaten to make such assessment redundant in at least three instances: (i) when no suitable solution can be found, (ii) when a solution is found but unavailable, or (iii) when a solution assesses only the process (e.g., questioning) but not the product (e.g., answer). 此外，生成式人工智能的大规模普及，或许意味着某些评估类型（例如论文）的终结（Zhai，2022）。毕竟，如果像 ChatGPT 这样的生成式人工智能工具能够对高级论文题目提供详细且类似人类的答案，那么人类的学习和洞察力在应对这类评估中又扮演着怎样的角色呢？作为这一挑战的一个例子，ChatGPT 成功通过了研究生水平的商科和法律考试（Kelly，2023），甚至部分医师执照考试（Hammer，2023），这促使有人建议教育工作者将这些类型的评估从课程中移除，转而采用更需要批判性思维的评估（Zhai，2022）。在这方面，通过生成式人工智能工具的兴起和普及而实现的技术进步可以提高知识评估的严谨性，尽管它也可能在至少三种情况下使这种评估变得多余：（i）当找不到合适的解决方案时，（ii）当找到解决方案但不可用时，或（iii）当解决方案仅评估过程（例如，提问）而不评估产品（例如，答案）时。
Nonetheless, it is important to note that Generative AI has its flaws despite its ability to inform and generate human-like responses. Generative AI tools such as ChatGPT may be (i) limited to non-current data, which, in turn, can cause its users to suffer from (ii) knowledge gaps, or worse, (iii) false information when the tool misinterprets prompts, or (iv) turns dishonest, if any how possible. Further scrutiny of the capability of Generative AI to paraphrase also indicates that the output returned or work performed could appear decent at a glance but may be, in reality, unable to fully meet requirements and pass detailed 尽管如此，值得注意的是，尽管生成式人工智能能够提供信息并生成类似人类的响应，但它也存在缺陷。诸如 ChatGPT 之类的生成式人工智能工具可能 (i) 受限于非当前数据，这反过来会导致用户遭受 (ii) 知识缺口，或更糟的是 (iii) 当工具误解提示时，会提供虚假信息，或 (iv) 变得不诚实（如果可能的话）。进一步审查生成式人工智能的释义能力还表明，返回的输出或执行的工作乍一看可能不错，但实际上可能无法完全满足要求并通过详细的