The rapid emergence of Generative AI, particularly ChatGPT, has sparked a global debate on the future of education, often characterized by alarmism and speculation. Moving beyond this, this study investigates the structured, grounded perspectives of a key stakeholder group: university educators. It proposes a novel theoretical model that conceptualizes the educational environment as a "Learning Space" composed of seven subspaces to systematically identify the impact of AI integration. This framework was operationalized through a quantitative survey of 140 Russian university educators, with responses analyzed using a binary flagging system to measure acceptance across key indicators. The results reveal a strong but conditional consensus: a majority of educators support ChatGPT's integration, contingent upon crucial factors such as the transformation of assessment methods and the availability of plagiarism detection tools. However, significant concerns persist regarding its impact on critical thinking. Educators largely reject the notion that AI diminishes their importance, viewing their role as evolving from information-deliverer to facilitator of critical engagement. The study concludes that ChatGPT acts less as a destroyer of education and more as a catalyst for its necessary evolution, and proposes the PIPE Model (Pedagogy, Infrastructure, Policy, Education) as a strategic framework for its responsible integration. This research provides a data-driven, model-based analysis of educator attitudes, offering a nuanced alternative to the polarized discourse surrounding AI in education.
翻译:生成式人工智能(特别是ChatGPT)的迅速兴起,已在全球范围内引发了一场关于教育未来的辩论,这一辩论常被危言耸听和猜测所主导。本研究超越这一层面,探究了一个关键利益相关者群体——大学教育工作者——的结构化、基于现实的视角。它提出了一个新颖的理论模型,将教育环境概念化为由七个子空间构成的“学习空间”,以系统性地识别人工智能整合的影响。该框架通过对140名俄罗斯大学教育工作者的定量调查得以实施,并使用二元标记系统分析回应,以衡量关键指标上的接受度。结果显示了一种强烈但有条件的共识:大多数教育工作者支持ChatGPT的整合,但这取决于关键因素,如评估方法的转变和抄袭检测工具的可用性。然而,对其批判性思维影响的重大担忧依然存在。教育工作者大多反对人工智能削弱其重要性的观点,认为自己的角色正从信息传递者演变为批判性参与的促进者。研究得出结论:ChatGPT与其说是教育的破坏者,不如说是其必要变革的催化剂,并提出了PIPE模型(教学法、基础设施、政策、教育)作为其负责任整合的战略框架。本研究提供了基于数据和模型的教育工作者态度分析,为围绕教育中人工智能的两极化讨论提供了一个细致入微的替代视角。