🛰️ 生成式 AI 智能体与高等教育形成性评价论文雷达

智能反馈 · 形成性评价 · 学术诚信 ｜ OpenAlex + DOAJ ｜ AI: glm-5.3
📄 67 篇在库🤖 12 篇 AI 卡片 🔎 检索自 2025-02-21🕒 生成 2026-08-22 07:38
高频技术/主题词 Top 25
📌 高被引论文 Top 10
    研究主题共现知识图谱
    节点=技术/主题词（大小=出现频次，颜色=所属检索方向或语料高频词）；连线=同篇论文共现（越粗越常一起出现）。可拖拽探索。
    近期热度 Top 20
    基于 67 篇样本、最近 180 天窗口统计。

    ⚠️ 趋势预警简报

    **趋势预警**（仅基于本次67篇、180天窗口样本）

    ① 「学习成效、评价、支持」类关键词升温最快，AI反馈对学习成效的客观测量与长期影响可即刻布局。

    ② 空白明显：因果检验设计（如阶梯楔形试验）、开放性任务的人机混合评分分工、未声明AI使用的分级披露与检测框架，样本内均缺实证。

    ③ 医学教育等垂直场景的可操作AI伦理指南与本土化实施路径仍属空档，适合差异化切入。

    ④ 仅凭满意度自评的态度调查与泛化伦理综述已现同质化堆积，不宜再跟风重复。

    基于 67 篇样本、最近 180 天窗口统计。

    🔥 近期热度关键词

    learning outcomes（近期热度 2 篇，相对升温 0.25x）、development（近期热度 3 篇，相对升温 0.18x）、learning（近期热度 5 篇，相对升温 0.17x）、education（近期热度 5 篇，相对升温 0.16x）、support（近期热度 3 篇，相对升温 0.16x）、applications（近期热度 2 篇，相对升温 0.15x）、future（近期热度 2 篇，相对升温 0.14x）、understanding（近期热度 2 篇，相对升温 0.13x）、assessment（近期热度 2 篇，相对升温 0.12x）、design（近期热度 2 篇，相对升温 0.11x）、artificial intelligence（近期热度 3 篇，相对升温 0.1x）

    📈 各方向趋势速览

    形成性评价

    样本显示热点集中在三处：LLM能否替代教师评分与反馈、医学教育中的AI形成性反馈（文献计量与实操指南）、远程高校真实课程的系统部署。方法以综述、文献计量和小规模试点为主，领域仍处在“画地图”阶段。空白清晰：缺跨学科、有对照组、追踪学习效果的严谨实证；评分信度与量规对齐、学生对AI反馈的实际采纳、人机协同工作流几乎无人做，是优先切入点。

    学术诚信

    本批样本热点集中三处：AI生成内容检测与溯源（水印综述）、机构诚信政策与报告框架（74份全球政策比较）、未声明AI写作的不端定性论证，另有医学教育等场景伦理梳理。方法上以综述、范围综述与政策文本分析为主，思辨多、实证少。明显空白：评估设计与形成性反馈如何随GenAI重构尚无实证；智能体（Agentic AI）代写的不端风险无人研究；学生真实使用行为与动机缺乏测量——均为可优先切入的低拥挤方向。

    📈 趋势速览

    （本方向未生成趋势速览：样本不足或 AI 提炼未运行）

    学术诚信智能体反馈
    Agentic AI: a comprehensive survey of architectures, applications, and future directions
    Artificial Intelligence Review · 2025-11-14 · 被引 101 · Mohamad Abou Ali、Fadi Dornaika、Jinan Charafeddine
    速览综述智能体AI的符号与神经双范式架构、跨领域应用及治理挑战，提出整合发展路线图。
    方法基于PRISMA系统综述2018-2025年90项研究，构建双范式分类框架分析。
    发现符号范式主导安全关键域，神经范式胜于数据丰富环境；未来在于两类范式的有意整合。
    机会混合神经-符号架构与符号系统治理模型存在研究空白，可延伸至教育智能体的可靠反馈与评价设计。
    智能体反馈
    Dynamic Assessment with AI (Agentic RAG) and Iterative Feedback: A Model for the Digital Transformation of Higher Education in the Global EdTech Ecosystem
    Algorithms · 2025-11-11 · 被引 1 · Rubén Juárez Cádiz、Antonio Hernández Fernández、Cláudia de Barros Camargo、David Molero López-Barajas
    速览构建智能体RAG驱动的六轮动态评价模型，实证迭代反馈显著提升高校课程成绩并重塑AI时代评价范式
    方法智能体RAG（规划、工具调用、自评）嵌入六轮迭代评价，结合更新规则、逻辑收敛与增益回归建模
    发现35人课程六轮内均分58.4升至91.2且离散度下降；高质量证据型反馈带来更大单步增益与更快收敛
    机会单课程观察设计待因果检验（如阶梯楔形试验）与跨学科泛化；可深挖过程痕迹与来源证据作为AI时代学术诚信评价信号
    智能体反馈
    The Rise of Agentic AI: A Review of Definitions, Frameworks, Architectures, Applications, Evaluation Metrics, and Challenges
    Future Internet · 2025-09-04 · 被引 122 · Ajay Bandi、Bhavani Kongari、Roshini Naguru、Sahitya Pasnoor
    摘要原文 Agentic AI systems are a recently emerged and important approach that goes beyond traditional AI, generative AI, and autonomous systems by focusing on autonomy, adaptability, and goal-driven reasoning. This study provides a clear review of agentic AI systems b…
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    智能体反馈
    AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges
    Information Fusion · 2025-08-22 · 被引 161 · Ranjan Sapkota、Konstantinos I. Roumeliotis、Manoj Karkee
    摘要原文 Information fusion, in the context of the Generative AI era, must distinguish AI Agents from Agentic AI. This review critically distinguishes between AI Agents and Agentic AI, offering a structured, conceptual taxonomy, application mapping, and analysis of opp…
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    学术诚信智能体反馈
    AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges
    SuperIntelligence - Robotics - Safety & Alignment · 2025-07-20 · 被引 158 · Ranjan Sapkota、Konstantinos I. Roumeliotis、Manoj Karkee
    摘要原文 This review critically distinguishes between AI Agents and Agentic AI, offering a structured, conceptual taxonomy, application mapping, and analysis of opportunities and challenges to clarify their divergent design philosophies and capabilities. We begin by ou…
    （本篇未生成 AI 卡片）
    智能体反馈
    Breaking human dominance: Investigating learners' preferences for learning feedback from generative AI and human tutors
    British Journal of Educational Technology · 2025-07-04 · 被引 18 · Huixiao Le、Yüan Shen、Zijian Li、Mengyu Xia
    摘要原文 Abstract Understanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' pr…
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    智能体反馈
    AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational setting
    Scientific Reports · 2025-06-03 · 被引 115 · Greg Kestin、Kelly Miller、Anna Klales、Timothy Milbourne
    摘要原文 Advances in generative artificial intelligence show great potential for improving education. Yet little is known about how this new technology should be used and how effective it can be compared to current best practices. Here we report a randomized, controlle…
    （本篇未生成 AI 卡片）
    学术诚信智能体反馈
    AI-Powered Educational Agents: Opportunities, Innovations, and Ethical Challenges
    Information · 2025-05-31 · 被引 68 · Diana‐Margarita Córdova‐Esparza
    摘要原文 Recent advances in large language models (LLMs) have triggered rapid growth in AI-powered educational agents, yet researchers and practitioners still lack a consolidated view of how these systems are engineered and validated. To address this gap, we conducted …
    （本篇未生成 AI 卡片）
    智能体反馈
    The benefits and dangers of anthropomorphic conversational agents
    Proceedings of the National Academy of Sciences · 2025-05-16 · 被引 98 · Sandra Peter、Kai Riemer、Jevin D. West
    摘要原文 A growing body of research suggests that the recent generation of large language model (LLMs) excel, and in many cases outpace humans, at writing persuasively and empathetically, at inferring user traits from text, and at mimicking human-like conversation beli…
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    智能体反馈
    Comparing Generative AI and teacher feedback: student perceptions of usefulness and trustworthiness
    Assessment & Evaluation in Higher Education · 2025-05-13 · 被引 115 · Michael Henderson、Margaret Bearman、Jennifer Chung、Tim Fawns
    摘要原文 The rapid integration of Generative Artificial Intelligence (GenAI) into educational contexts has presented both opportunities and challenges for students seeking and using feedback. While AI-generated feedback can offer increased access, timely responses and …
    （本篇未生成 AI 卡片）
    智能体反馈形成性评价
    The role of generative AI and hybrid feedback in improving L2 writing skills: a comparative study
    Innovation in Language Learning and Teaching · 2025-05-13 · 被引 63 · Zhihui Zhang、Scott Aubrey、Xiaomeng Huang、Thomas K. F. Chiu
    摘要原文 This study examines the impact of Generative AI (GenAI) – generated feedback and hybrid feedback (GenAI and human tutor input) on L2 academic writing skills. Over 12 weeks, 60 Chinese EFL students were divided into two groups: Group 1 received only GenAI feedb…
    （本篇未生成 AI 卡片）
    智能体反馈
    Human-artificial interaction in the age of agentic AI: a system-theoretical approach
    Frontiers in Human Dynamics · 2025-05-09 · 被引 55 · Uwe M. Borghoff、Paolo Bottoni、Remo Pareschi
    摘要原文 This paper presents a novel perspective on human-computer interaction (HCI), framing it as a dynamic interplay between human and computational agents within a networked system. Going beyond traditional interface-based approaches, we emphasize the importance of…
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    智能体反馈
    Mastering knowledge: the impact of generative AI on student learning outcomes
    Studies in Higher Education · 2025-05-06 · 被引 58 · Jessica L. Pallant、Janneke Blijlevens、Alexander Campbell、Ryan Jopp
    摘要原文 Generative AI (GenAI) has had a significant impact across industries since the launch of ChatGPT in late 2022. Much of the focus of existing research in the higher education space has considered the impact GenAI has had on academics and institutions. Conversel…
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    智能体反馈
    The effects of generative AI agents and scaffolding on enhancing students’ comprehension of visual learning analytics
    Computers & Education · 2025-04-26 · 被引 59 · Lixiang Yan、Roberto Martínez‐Maldonado、Yueqiao Jin、Vanessa Echeverría
    摘要原文 Visual learning analytics (VLA) is becoming increasingly adopted in educational technologies and learning analytics dashboards to convey critical insights to students and educators. Yet many students experienced difficulties in comprehending complex VLA due to…
    （本篇未生成 AI 卡片）
    智能体反馈
    Development of a generative AI ‐powered teachable agent for middle school mathematics learning: A design‐based research study
    British Journal of Educational Technology · 2025-04-17 · 被引 35 · Wanli Xing、Yukyeong Song、Chenglu Li、Zifeng Liu
    摘要原文 This paper reports on a design‐based research (DBR) study that aims to devise an artificial intelligence (AI)‐powered teachable agent that supports secondary school students' learning‐by‐teaching practices of mathematics learning content. A long‐standing pedag…
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    智能体反馈
    The cognitive paradox of AI in education: between enhancement and erosion
    Frontiers in Psychology · 2025-04-14 · 被引 134 · Binny Jose、Jaya Cherian、Alie Molly Verghis、Sony Mary Varghise
    摘要原文 problems in student retention and critical thinking in 206 vocational education students in the Akwa Ibom State, Nigeria. The results showed that AI posed significant threats to the male students showing more concern than their female peers. While AI aids voca…
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    智能体反馈
    Generative AI and its Transformative Value for Digital Platforms
    Journal of Management Information Systems · 2025-04-03 · 被引 110 · Michael Wessel、Martin Adam、Alexander Benlian、Ann Majchrzak
    摘要原文 The emergence of generative artificial intelligence (GenAI) represents a watershed moment in the evolution of digital platforms. The capabilities of this AI technology go beyond traditional AI systems, enabling the autonomous generation of novel outcomes with …
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    智能体反馈形成性评价
    Understanding higher education students’ adoption of generative AI technologies: An empirical investigation using UTAUT2
    Contemporary Educational Technology · 2025-02-24 · 被引 71 · Olga V. Sergeeva、Мarina R. Zheltukhina、Tatyana Shoustikova、Leysan R. Tukhvatullina
    摘要原文 Generative artificial intelligence (GAI) technologies are gaining traction in higher education, offering potential benefits such as personalized learning support and enhanced productivity. However, successful integration requires understanding the factors infl…
    （本篇未生成 AI 卡片）
    📈 趋势速览

    样本显示热点集中在三处：LLM能否替代教师评分与反馈、医学教育中的AI形成性反馈（文献计量与实操指南）、远程高校真实课程的系统部署。方法以综述、文献计量和小规模试点为主，领域仍处在“画地图”阶段。空白清晰：缺跨学科、有对照组、追踪学习效果的严谨实证；评分信度与量规对齐、学生对AI反馈的实际采纳、人机协同工作流几乎无人做，是优先切入点。

    形成性评价
    A Survey of Large Language Models
    Frontiers of Computer Science · 2026-05-09 · 被引 1488 · Wayne Xin Zhao、Kun Zhou、Junyi Li、Tianyi Tang
    速览系统综述大语言模型在预训练、后训练、使用策略与评测四维度的进展与开放挑战。
    方法系统性文献综述，涵盖架构创新、SFT与RLHF、上下文学习、智能体推理及评测基准。
    发现LLM能力快速跃升，但理论根基、高效扩展、对齐与智能体能力仍是关键开放问题。
    机会可将该综述的评测框架与智能体推理技术迁移至教育场景，探索LLM作为学习反馈智能体支持形成性评价的路径。
    形成性评价
    Mapping the landscape of AI-assisted formative feedback in medical education: A bibliometric analysis
    Medicine · 2026-01-30 · 被引 6 · Sha Yu、Jin Liu
    速览对2021-2025年医学教育中AI辅助形成性反馈研究做文献计量分析，绘制领域知识图谱与发展趋势。
    方法基于Web of Science的116篇文献，用VOSviewer、CiteSpace与R-bibliometrix进行计量分析。
    发现该领域呈指数增长，美国主导；反馈、大语言模型、医学教育为2024-25热点，需理论与伦理导向的AI整合。
    机会缺少验证AI反馈能否真正提升学习者能力的实证与理论框架；跨国跨学科协作与伦理规约是待填补的研究空白。
    形成性评价
    Can ChatGPT Replace the Teacher in Assessment? A Review of Research on the Use of Large Language Models in Grading and Providing Feedback
    Applied Sciences · 2026-01-08 · 被引 7 · Marcin Jukiewicz、Michał Wyrwa
    速览系统综述42项实证研究，检验ChatGPT等LLM能否替代教师完成评分与反馈。
    方法PRISMA系统综述，纳入42项LLM自动评分与反馈的实证研究。
    发现LLM在封闭题与简答接近人类水平，开放性任务欠佳；提示词与评分量规质量关键，人机混合模式最优。
    机会LLM对开放性、创造性任务评分可靠性不足，人机混合评价中教师监督的最优分工机制值得深入探索。
    形成性评价
    Integration of an AI-Powered Feedback System for Formative Assessment at the Open University Malaysia
    Journal of Learning for Development · 2025-11-18 · 被引 1 · Nantha Kumar Subramanıam、Santhi Raghavan
    速览马来西亚开放大学在12门首学期课程中部署AI反馈系统，提升远程教育形成性评价。
    方法AI驱动作业反馈系统覆盖12门课程，结合学生问卷调查评估使用体验。
    发现学生满意度高并愿持续使用；系统支持自主学习，显著减轻教师批改负担。
    机会研究仅依赖满意度自评，可延伸至AI反馈对学习成效的客观测量、长期影响及跨学科泛化验证。
    形成性评价
    Formative assessment and feedback in medical education: A practical guide: AMEE Guide No. 189
    Medical Teacher · 2025-10-24 · 被引 25 · Anastasiya A. Lipnevich、Krista D. Mattern、C. A. Feddock
    速览提出医学教育中系统整合形成性评价与反馈的循证实用指南框架。
    方法综合医学与教育学文献综述，构建含持续性、及时性、同伴自评与技术反馈的框架
    发现形成性实践常碎片化且依赖终结性结构，系统整合可培养反思型、适应型终身学习者。
    机会可探索生成式AI智能体如何实现及时、个性化、规模化的形成性反馈并提升评价素养。
    形成性评价
    Using AI to generate formative feedback in doctoral education
    Assessment & Evaluation in Higher Education · 2025-08-03 · 被引 9 · David Tensen、Peter Grainger、Wayne Graham
    摘要原文 This paper examines how artificial intelligence (AI) tools enhance feedback practices in doctoral education by providing a supplementary source of formative assessment. It explores the use of Generative AI alongside Grainger’s Formative Assessment Criteria-Bas…
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    形成性评价
    Large Language Models in Healthcare and Medical Applications: A Review
    Bioengineering · 2025-06-10 · 被引 187 · Subhankar Maity、Manob Jyoti Saikia
    摘要原文 This paper provides a systematic and in-depth examination of large language models (LLMs) in the healthcare domain, addressing their significant potential to transform medical practice through advanced natural language processing capabilities. Current implemen…
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    学术诚信形成性评价
    A Framework for Generative AI-Driven Assessment in Higher Education
    Information · 2025-06-03 · 被引 44 · Galina Ilieva、Tania Yankova、Margarita Ruseva、Stanimir Kabaivanov
    摘要原文 The rapid integration of generative artificial intelligence (AI) into educational environments raises both opportunities and concerns regarding assessment design, academic integrity, and quality assurance. While new generation AI tools offer new modes of inter…
    （本篇未生成 AI 卡片）
    形成性评价
    Large Language Models in Medicine: Applications, Challenges, and Future Directions
    International Journal of Medical Sciences · 2025-05-31 · 被引 118 · Erlan Yu、Xuehong Chu、Wanwan Zhang、Xiangbin Meng
    摘要原文 In recent years, large language models (LLMs) represented by GPT-4 have developed rapidly and performed well in various natural language processing tasks, showing great potential and transformative impact. The medical field, due to its vast data information as…
    （本篇未生成 AI 卡片）
    形成性评价
    Exploring How AI Literacy and Self-Regulated Learning Relate to Student Writing Performance and Well-Being in Generative AI-Supported Higher Education
    Behavioral Sciences · 2025-05-20 · 被引 50 · Jiajia Shi、Weitong Liu、Ke Hu
    摘要原文 The integration of generative artificial intelligence (GAI) into higher education is transforming students' learning processes, academic performance, and psychological well-being. Despite the increasing adoption of GAI tools, the mechanisms through which stude…
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    智能体反馈形成性评价
    The role of generative AI and hybrid feedback in improving L2 writing skills: a comparative study
    Innovation in Language Learning and Teaching · 2025-05-13 · 被引 63 · Zhihui Zhang、Scott Aubrey、Xiaomeng Huang、Thomas K. F. Chiu
    摘要原文 This study examines the impact of Generative AI (GenAI) – generated feedback and hybrid feedback (GenAI and human tutor input) on L2 academic writing skills. Over 12 weeks, 60 Chinese EFL students were divided into two groups: Group 1 received only GenAI feedb…
    （本篇未生成 AI 卡片）
    形成性评价
    Peer and AI Review + Reflection (PAIRR): A human-centered approach to formative assessment
    Computers & composition/Computers and composition · 2025-04-23 · 被引 17 · Lisa Sperber、Marit MacArthur、Sophia Minnillo、Nicholas Stillman
    摘要原文 • AI can offer useful writing feedback when used combined with peer review. • AI and peer responses were often similar and mutually reinforcing. • When AI and peer responses differed, the perspectives were often complementary. • Evaluating AI feedback fostered…
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    形成性评价
    Cognitive Computing with Large Language Models for Student Assessment Feedback
    Big Data and Cognitive Computing · 2025-04-23 · 被引 8 · Noorhan Abbas、Eric Atwell
    摘要原文 Effective student feedback is fundamental to enhancing learning outcomes in higher education. While traditional assessment methods emphasise both achievements and development areas, the process remains time-intensive for educators. This research explores the a…
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    形成性评价
    Industrial applications of large language models
    Scientific Reports · 2025-04-21 · 被引 134 · Mubashar Raza、Zarmina Jahangir、Muhammad Bilal Riaz、Muhammad Jasim Saeed
    摘要原文 Large language models (LLMs) are artificial intelligence (AI) based computational models designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate language patterns, enabling remarkable perfo…
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    形成性评价
    Perceptions of Generative AI Tools in Higher Education: Insights from Students and Academics at Sultan Qaboos University
    Education Sciences · 2025-04-16 · 被引 38 · Alsaeed Alshamy、Aisha Salim Ali Al-Harthi、Shubair Abdulla
    摘要原文 This study investigates the perceptions of generative artificial intelligence (GenAI) tools, such as ChatGPT, among students and academics at Sultan Qaboos University (SQU) within the context of higher education in Oman. Using the Technology Acceptance Model (…
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    形成性评价
    Benchmarking large language models for biomedical natural language processing applications and recommendations
    Nature Communications · 2025-04-05 · 被引 156 · Qingyu Chen、Yan Hu、Xueqing Peng、Qianqian Xie
    摘要原文 The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While Large Language Models (LLMs) have shown promise in general domains, their effec…
    （本篇未生成 AI 卡片）
    学术诚信形成性评价
    The impact of generative AI on academic integrity of authentic assessments within a higher education context
    British Journal of Educational Technology · 2025-03-31 · 被引 110 · Alexander Kofinas、Crystal Han‐Huei Tsay、David A. Pike
    摘要原文 Generative AI (hereinafter GenAI) technology, such as ChatGPT, is already influencing the higher education sector. In this work, we focused on the impact of GenAI on the academic integrity of assessments within higher education institutions, as GenAI can be us…
    （本篇未生成 AI 卡片）
    形成性评价
    Integrating generative AI into STEM education: enhancing conceptual understanding, addressing misconceptions, and assessing student acceptance
    Disciplinary and Interdisciplinary Science Education Research · 2025-03-31 · 被引 60 · Tarik El Fathi、Aouatif Saad、Hayat Larhzil、Driss Lamri
    摘要原文 Abstract Advancements in artificial intelligence (AI), particularly generative AI models such as ChatGPT, offer transformative opportunities to enhance educational practices in STEM disciplines. Thermodynamics, a fundamental subject in engineering education, p…
    （本篇未生成 AI 卡片）
    形成性评价
    PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
    BMJ · 2025-03-24 · 被引 594 · Karel G.M. Moons、Johanna AAG Damen、T. K. Kaul、Lotty Hooft
    摘要原文 The Prediction model Risk Of Bias ASsessment Tool (PROBAST) is used to assess the quality, risk of bias, and applicability of prediction models or algorithms and of prediction model/algorithm studies. Since PROBAST’s introduction in 2019, much progress has bee…
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    形成性评价
    Teachers and AI: Understanding the factors influencing AI integration in K-12 education
    Education and Information Technologies · 2025-03-20 · 被引 85 · Ozan FİLİZ、Mehmet Haldun Kaya、Tufan Adıgüzel
    摘要原文 Abstract This study investigates the psychological and pedagogical factors influencing K-12 teachers' readiness to integrate artificial intelligence (AI) into educational settings. An exploratory qualitative approach was employed, involving 66 teachers from 11…
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    智能体反馈形成性评价
    Understanding higher education students’ adoption of generative AI technologies: An empirical investigation using UTAUT2
    Contemporary Educational Technology · 2025-02-24 · 被引 71 · Olga V. Sergeeva、Мarina R. Zheltukhina、Tatyana Shoustikova、Leysan R. Tukhvatullina
    摘要原文 Generative artificial intelligence (GAI) technologies are gaining traction in higher education, offering potential benefits such as personalized learning support and enhanced productivity. However, successful integration requires understanding the factors infl…
    （本篇未生成 AI 卡片）
    📈 趋势速览

    本批样本热点集中三处：AI生成内容检测与溯源（水印综述）、机构诚信政策与报告框架（74份全球政策比较）、未声明AI写作的不端定性论证，另有医学教育等场景伦理梳理。方法上以综述、范围综述与政策文本分析为主，思辨多、实证少。明显空白：评估设计与形成性反馈如何随GenAI重构尚无实证；智能体（Agentic AI）代写的不端风险无人研究；学生真实使用行为与动机缺乏测量——均为可优先切入的低拥挤方向。

    学术诚信
    Watermarking techniques for large language models: a survey
    Artificial Intelligence Review · 2026-01-05 · 被引 8 · Yuqing Liang、Jiancheng Xiao、Wensheng Gan、Philip S. Yu
    速览首个系统综述大语言模型水印技术，梳理传统数字水印的传承关联，并展望多模态水印与未来挑战。
    方法文献综述法：梳理传统水印与LLM水印继承关系，分析多模态水印优劣。
    发现首个LLM水印全面综述：传统水印可迁移至LLM，多模态水印是重要发展方向。
    机会现有综述少涉教育场景，可研究水印在学业评价中识别AI生成内容、保障学术诚信的落地效果。
    学术诚信智能体反馈
    Agentic AI: a comprehensive survey of architectures, applications, and future directions
    Artificial Intelligence Review · 2025-11-14 · 被引 101 · Mohamad Abou Ali、Fadi Dornaika、Jinan Charafeddine
    速览综述智能体AI的符号与神经双范式架构、跨领域应用及治理挑战，提出整合发展路线图。
    方法基于PRISMA系统综述2018-2025年90项研究，构建双范式分类框架分析。
    发现符号范式主导安全关键域，神经范式胜于数据丰富环境；未来在于两类范式的有意整合。
    机会混合神经-符号架构与符号系统治理模型存在研究空白，可延伸至教育智能体的可靠反馈与评价设计。
    学术诚信
    Addressing student use of generative AI in schools and universities through academic integrity reporting
    Frontiers in Education · 2025-11-07 · 被引 13 · Steven A. Peterson
    速览理论文章：探讨AI与GenAI的合理定义框架，并提出应对学生不当使用GenAI的高效透明可扩展学术诚信报告框架。
    方法理论建构与政策文献分析（引用Luo用WPR方法对20所顶尖大学GenAI政策的批判分析）。
    发现主流政策将GenAI视为诚信威胁，风险污名化正当使用者，并使教师沦为惩罚性守门人而非赋能学习。
    机会现有研究缺少政策实际效果的实证数据与学生视角，可延伸开展人机协作'原创性'重定义及诚信政策的实证影响评估。
    学术诚信
    The ethical challenges in the integration of artificial intelligence and large language models in medical education: A scoping review
    PLoS ONE · 2025-10-22 · 被引 25 · Xinrui Li、Xiaodan Yan、Hsiang-Wai Lai
    速览通过范围综述系统梳理AI与大语言模型融入医学教育带来的伦理挑战、机遇及缓解策略。
    方法范围综述法，检索PubMed/Embase/WoS（2010–2024.8），纳入50篇，用Kimi AI辅助筛选并双人交叉验证。
    发现识别七大核心伦理维度：隐私安全、算法偏见、问责归属、公平性、技术可靠性、应用依赖与患者自主性，并逐一提出缓解策略。
    机会医学教育专用AI伦理框架与实施指南仍缺失，可研究构建可操作的伦理治理框架、本土化指南及AI应用的长期伦理影响追踪。
    学术诚信
    Utilizing Generative AI Responsibly and Ethically for Research Purposes in Higher Education: A Policy Analysis
    Serials Review · 2025-10-02 · 被引 25 · Ahmed Alduais、Saba Qadhi、Youmen Chaaban、Majeda Khraisheh
    速览分析全球74份政策文件，比较高等教育研究中生成式AI的伦理规范与政策响应。
    方法归纳式定性内容分析，覆盖政府、高校、出版商与出版手册四类74份政策文件。
    发现透明与披露是跨域核心共识，AI不可署名；公平包容与政策执行机制仍存明显缺口。
    机会政策执行与公平包容指导薄弱，可研究AI素养培训框架设计及其对研究者负责任使用行为的干预效果。
    学术诚信
    Undeclared AI-Assisted Academic Writing as a Form of Research Misconduct
    Science Editor · 2025-09-08 · 被引 5 · Bor Luen Tang
    速览论证未声明使用生成式AI辅助学术写作本质上属于研究不端行为。
    方法概念论证结合文献案例，将未声明AI使用归入'伪造研究'范畴。
    发现未声明AI写作可能操纵研究过程、产生不可靠知识，属'研究造假'类不端。
    机会缺乏可操作的未声明AI使用检测方法与分级披露监管框架，亟待实证研究。
    学术诚信
    LLM-D12: A Dual-Dimensional Scale of Instrumental and Relational Dependencies on Large Language Models
    ACM Transactions on the Web · 2025-09-03 · 被引 24 · Ala Yankouskaya、Areej Babiker、Syeda Rizvi、Sameha Alshakhsi
    摘要原文 There is growing interest in understanding how people interact with large language models (LLMs) and whether such models elicit dependency or even addictive behaviour. Validated tools to assess the extent to which individuals may become dependent on LLMs are s…
    （本篇未生成 AI 卡片）
    学术诚信
    Student Perceptions of AI-Assisted Writing and Academic Integrity: Ethical Concerns, Academic Misconduct, and Use of Generative AI in Higher Education
    AI in Education · 2025-09-02 · 被引 26 · Brady Lund、Nishith Reddy Mannuru、Zoë Abbie Teel、Tae Hee Lee
    摘要原文 The rise of generative AI in higher education has disrupted our traditional understandings of academic integrity, moving our focus from clear-cut infractions to evolving ethical judgment. In this study, a survey of 401 students from major U.S. universities pro…
    （本篇未生成 AI 卡片）
    学术诚信
    AI for scientific integrity: detecting ethical breaches, errors, and misconduct in manuscripts
    Frontiers in Artificial Intelligence · 2025-09-02 · 被引 25 · Diogo Pellegrina、Mohamed Helmy
    摘要原文 The use of Generative AI (GenAI) in scientific writing has grown rapidly, offering tools for manuscript drafting, literature summarization, and data analysis. However, these benefits are accompanied by risks, including undisclosed AI authorship, manipulated co…
    （本篇未生成 AI 卡片）
    学术诚信智能体反馈
    AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges
    SuperIntelligence - Robotics - Safety & Alignment · 2025-07-20 · 被引 158 · Ranjan Sapkota、Konstantinos I. Roumeliotis、Manoj Karkee
    摘要原文 This review critically distinguishes between AI Agents and Agentic AI, offering a structured, conceptual taxonomy, application mapping, and analysis of opportunities and challenges to clarify their divergent design philosophies and capabilities. We begin by ou…
    （本篇未生成 AI 卡片）
    学术诚信
    Generative AI in Higher Education: Demographic Differences in Student Perceived Readiness, Benefits, and Challenges
    TechTrends · 2025-06-10 · 被引 32 · Daniel Maxwell、Beth Oyarzun、Stella Kim、Ji Yae Bong
    摘要原文 Abstract With the rapid evolution and widespread adoption of Generative AI (GenAI), there has been a recent surge in research on students’ perceptions and usage of these tools for learning. However, a critical need remains to understand how students from vario…
    （本篇未生成 AI 卡片）
    学术诚信
    GLAT: The generative AI literacy assessment test
    Computers and Education Artificial Intelligence · 2025-06-09 · 被引 56 · Yueqiao Jin、Roberto Martínez‐Maldonado、Dragan Gašević、Lixiang Yan
    摘要原文 The rapid integration of generative artificial intelligence (GenAI) technology into education requires precise measurement of GenAI literacy to ensure that learners and educators possess the skills to engage with and critically evaluate this transformative tec…
    （本篇未生成 AI 卡片）
    学术诚信
    Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology
    Nature Cancer · 2025-06-06 · 被引 139 · Dyke Ferber、Omar S. M. El Nahhas、Georg Wölflein、Isabella C. Wiest
    摘要原文 Clinical decision-making in oncology is complex, requiring the integration of multimodal data and multidomain expertise. We developed and evaluated an autonomous clinical artificial intelligence (AI) agent leveraging GPT-4 with multimodal precision oncology to…
    （本篇未生成 AI 卡片）
    学术诚信
    From institutional climate to moral attitudes: examining theoretical models of academic misconduct
    Ethics & Behavior · 2025-06-05 · 被引 7 · Andrew H. Perry、David A. Rettinger、Jason M. Stephens、Eric M. Anderman
    摘要原文 The study of academic misconduct in higher education spans generations. Reducing the problem among college students remains a top priority among university stakeholders. There are several theoretical explanations for why students cheat, including the instituti…
    （本篇未生成 AI 卡片）
    学术诚信形成性评价
    A Framework for Generative AI-Driven Assessment in Higher Education
    Information · 2025-06-03 · 被引 44 · Galina Ilieva、Tania Yankova、Margarita Ruseva、Stanimir Kabaivanov
    摘要原文 The rapid integration of generative artificial intelligence (AI) into educational environments raises both opportunities and concerns regarding assessment design, academic integrity, and quality assurance. While new generation AI tools offer new modes of inter…
    （本篇未生成 AI 卡片）
    学术诚信
    The potential impact of generative AI on the future of higher education: a game-changer or a danger to academic integrity
    International Journal of Evaluation and Research in Education (IJERE) · 2025-06-01 · 被引 4 · Pritam Kumar、Amarjeet Singh Mastana、Chainarong Rungruengarporn、Donyawan Chantokul
    摘要原文 Artificial intelligence (AI) has the potential to improve education by substantially modifying knowledge acquisition. While the research on AI’s incorporation into higher education is growing, significant gaps exist in understanding its responsibilities, poten…
    （本篇未生成 AI 卡片）
    学术诚信智能体反馈
    AI-Powered Educational Agents: Opportunities, Innovations, and Ethical Challenges
    Information · 2025-05-31 · 被引 68 · Diana‐Margarita Córdova‐Esparza
    摘要原文 Recent advances in large language models (LLMs) have triggered rapid growth in AI-powered educational agents, yet researchers and practitioners still lack a consolidated view of how these systems are engineered and validated. To address this gap, we conducted …
    （本篇未生成 AI 卡片）
    学术诚信
    Students’ Perceptions of Generative Artificial Intelligence (GenAI) Use in Academic Writing in English as a Foreign Language
    Education Sciences · 2025-05-16 · 被引 54 · Anderson Nelson、Paola V. Santamaría、Josephine S. Javens、Marvin Ricaurte
    摘要原文 While research articles on students’ perceptions of large language models such as ChatGPT in language learning have proliferated since ChatGPT’s release, few studies have focused on these perceptions among English as a foreign language (EFL) university student…
    （本篇未生成 AI 卡片）
    学术诚信
    Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities
    Science China Information Sciences · 2025-04-02 · 被引 177 · Qimei Cui、Xiaohu You、Wei Ni、Guoshun Nan
    摘要原文 Abstract With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks has emerged as a transformative paradigm. By embedding AI capabilities ac…
    （本篇未生成 AI 卡片）
    学术诚信形成性评价
    The impact of generative AI on academic integrity of authentic assessments within a higher education context
    British Journal of Educational Technology · 2025-03-31 · 被引 110 · Alexander Kofinas、Crystal Han‐Huei Tsay、David A. Pike
    摘要原文 Generative AI (hereinafter GenAI) technology, such as ChatGPT, is already influencing the higher education sector. In this work, we focused on the impact of GenAI on the academic integrity of assessments within higher education institutions, as GenAI can be us…
    （本篇未生成 AI 卡片）
    学术诚信
    AI and Academic Integrity: Exploring Student Perceptions and Implications for Higher Education
    Journal of Academic Ethics · 2025-03-19 · 被引 66 · Brady Lund、Tae Hee Lee、Nishith Reddy Mannuru、Nikhila Arutla
    （该来源无摘要，仅元数据）
    学术诚信
    The use of generative AI by students with disabilities in higher education
    The Internet and Higher Education · 2025-03-13 · 被引 50 · Xin Zhao、Andrew Cox、Xuanning Chen
    摘要原文 The use of generative AI is controversial in education largely because of its potential impact on academic integrity. Yet some scholars have suggested it could be particularly beneficial for students with disabilities. To date there has been no empirical resea…
    （本篇未生成 AI 卡片）
    学术诚信
    Exploring the Ethical Challenges of Conversational AI in Mental Health Care: Scoping Review
    JMIR Mental Health · 2025-02-21 · 被引 144 · Mehrdad Rahsepar Meadi、Tomas Sillekens、Suzanne Metselaar、Anton J.L.M. van Balkom
    摘要原文 BACKGROUND: Conversational artificial intelligence (CAI) is emerging as a promising digital technology for mental health care. CAI apps, such as psychotherapeutic chatbots, are available in app stores, but their use raises ethical concerns. OBJECTIVE: We aimed…
    （本篇未生成 AI 卡片）
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