OBE是一种以学生学习成果为中心的教育哲学，其核心在于教学设计与实施均围绕学生最终能达成的能 力成果来组织。该理念包含四个相互关联的核心原则。首要原则是清楚聚焦，这意味着教育过程的出发 点必须是定义清晰、可衡量且公开的学习成果，这些成果着重于学生毕业后实际能具备的能力而非仅掌 握的知识内容。第二个原则是反向设计，它要求课程设计与评价必须从预期的最终学习成果出发，逆向 推导出实现这些成果所需的教学活动、资源配置及评价节点，确保教学环节与最终目标高度一致。第三 个原则是高期待，主张为所有学生设定具有挑战性的高标准，并相信通过有效的教学支持，大多数学生 都能达成这些标准，从而激发其潜能。第四个原则是扩大机会，承认个体差异的存在，强调应为学生提 供多元化的学习路径、充足的时间及多次尝试的机会，以支持其最终成功，这体现了教育的包容性与发 展性。 二、 OBE教育理念与过程性评价的契合点 OBE教育理念与过程性评价在内在逻辑上高度契合，共同构成促进学生能力达成的有效框架。首先，二 者在目标上具有一致性，均以实现明确的、高阶的学习成果为根本目的，过程性评价的各个节点如同路 标，共同指向最终学习成果的实现。其次，二者均强调学 ...

Group 1 - Several top universities in China are reforming their GPA systems, with Fudan University introducing a P/NP grading system and Peking University planning to abolish GPA for undergraduates starting from 2025 [1][22] - The shift away from a strict GPA system reflects a broader critique of the "score-centric" approach in education, indicating a move towards more qualitative assessments [1][22] - The historical reliance on grading systems has created a culture of anxiety among students, leading to unhealthy competition and a focus on grades over genuine learning [10][19] Group 2 - The grading system, which has been a staple in education since the late 18th century, is now being questioned for its effectiveness and relevance in modern education [3][4] - Critics argue that the current grading practices do not accurately reflect students' understanding or capabilities, often reducing their educational experience to mere numbers [10][15] - The push for reform is not just about changing grading policies but also about redefining the values of education and what constitutes success [22]

Group 1 - Several top universities in China are reforming their GPA systems, with Fudan University introducing a "P/NP" grading mechanism and Peking University announcing the cancellation of the GPA system for undergraduates starting in 2025 [2][3] - The shift away from traditional grading systems reflects a broader critique of the reliance on scores in education, moving towards a more qualitative assessment of student learning [2][4] - The historical context of grading systems reveals their evolution from local, personalized assessments to standardized measures that serve bureaucratic and organizational purposes in education [6][8] Group 2 - The grading system has been criticized for distorting educational practices, leading to a focus on grades rather than genuine learning, and fostering unhealthy competition among students [9][10] - The current GPA system is seen as inadequate in capturing individual student capabilities and learning styles, often reducing students to a single numerical value [10][18] - There is a growing recognition that the emphasis on grades can negatively impact student motivation and mental health, prompting calls for a reevaluation of assessment methods [13][19] Group 3 - The need for a new assessment system is highlighted, one that emphasizes process-oriented evaluation rather than purely outcome-based grading, incorporating elements like participation and collaboration [20][21] - Some educational institutions are experimenting with alternative grading methods, such as personalized feedback and mastery-based assessments, to better align with contemporary educational needs [20][21] - The reforms at Peking University symbolize a significant shift in educational philosophy, challenging traditional notions of success and the value of learning [21]

Core Insights - The article discusses the transformative impact of artificial intelligence (AI) on higher education, particularly in the realm of ideological and political education in universities, highlighting new opportunities and perspectives brought by digitalization [1] Group 1: Transformation of Educational Models - AI technology will lead to a comprehensive transformation of ideological and political education in universities, shifting from traditional methods to a more intelligent and collaborative educational model [2] - The integration of AI will facilitate a hybrid teaching model that combines online and offline learning, making online micro-classes a significant supplement to traditional ideological education [2] - AI can assist educators by taking over repetitive tasks such as student performance analysis and assignment grading, thereby enhancing teaching efficiency [2] Group 2: Innovation in Teaching Content - AI will enable a dynamic and multi-dimensional presentation of teaching content, moving beyond static textbooks to a more integrated approach [2] - AI systems can automatically gather trending educational materials from the internet, creating an updated case library for ideological education [2] - Virtual reality (VR) technology can simulate various scenarios for students, helping them understand the consequences of different value choices [2] Group 3: Redefining Roles of Educators and Students - The roles of educators and students will undergo significant changes, fostering a collaborative educational community [2] - Educators will transition from mere knowledge transmitters to classroom designers and academic researchers, utilizing AI data to enhance teaching [2] - Students will evolve from passive recipients of knowledge to active learners, using digital tools for independent exploration and collaborative activities [2] Group 4: Reform Pathways for AI Integration - To realize the envisioned transformation, a systematic solution must be developed, focusing on key areas such as technology, policy, and talent [3] - There is a need to establish comprehensive regulations and standards for the application of AI in ideological education, ensuring data security and ethical considerations [3] - Institutions should create a tiered certification system for AI educational platforms, assessing their safety, algorithm transparency, and educational suitability [3] Group 5: Enhancing Value Guidance and Teacher Competence - The application of AI in education must adhere to the principle of serving educational purposes, ensuring that technology supports rather than detracts from the educational experience [4] - A robust review mechanism should be established to filter negative content generated by AI, maintaining ideological safety in educational materials [4] - Developing a composite teacher workforce with both professional and digital literacy is crucial for improving the quality of ideological education [5]