AI-assisted Assessment in Higher Education:A Systematic Review

AI tools are increasingly used in education,impacting teaching and learning across various disciplines.However,previous review articles and empirical studies have not systematically discussed the application of AI in higher education assessment,the impact on user acceptance during its application,and the future opportunities and challenges.This systematic review aims to understand the application of AI tools in assessment,factors that influence students'and educators'perceptions,and related challenges and opportunities.Analyzing 81 empirical studies through matrix coding and content analysis,the results show that AI tools are used in intelligent tutoring and personalized learning,giving automated assessment and feedback,virtual classroom and online collaboration,learning analytics and prediction,knowledge management and resource recommendation,and educational chat assistants.AI tools offer high-quality,real-time,personalized feedback,improving cognitive and metacognitive skills and fostering positive emotions.Despite the benefits,challenges such as security and privacy concerns,algorithmic bias,unreliable feedback,negative attitudes,insufficient abilities,academic integrity issues,and lack of proper guidance persist.To advance our understanding of AI as an assessment tool,we call for studies that explore ways to enhance teachers’and students’perceptions and refine guidelines to prevent academic dishonesty and ensure responsible AI use.

Study on the Influence of AI Composition Software on Students'Creative Ability in Music Education

Generative AI technology for human-assisted tools has made great strides in recent years,and studying the impact of this technology on students'compositional abilities plays an important role in promoting changes in music education.Previous studies have focused on the performance of music composition software itself in terms of composition,with less consideration given to the impact of creators'compositional ability after using assistive composition tools.Thus,this paper designs a controlled experiment to investigate the changes in students'compositional ability before and after using AI composition tools.This paper finds that students'compositional abilities in all areas of composition improved to varying degrees after using AI composition tools.This paper compares the differences in compositional abilities of students with and without the education of AI composition tools,which has practical implications for vigorously promoting the adoption of AI composition tools in university music education teaching.

AI赋能军队院校任职教育的方法与策略研究

随着军队院校教育改革的推进,军校教育已逐渐由学历教育为主向以任职教育为主转变。然而,传统教学模式在实际教学实施过程中已经很难取得较好的培训效果。立足军队院校任职教育现状与挑战,针对传统任职教育模式存在的学员背景多样、师资能力发展不均衡以及教学效果提升慢的问题,从学员学习、教员教学和效果评价三个维度研究AI技术赋能军校任职教育的方法策略,通过深入探讨AI赋能军校任职教育可能遇到的挑战,提出相应的应对措施和解决方案。AI赋能教育是未来军校任职教育发展趋势,应积极拥抱技术创新,全面革新任职教育体系模式,满足新时代军官能力快速生成需求,适应未来智能化战争变化。

Integrated environmental education for sustainable forest management: the case of Nandi Hills Forests, Kenya

Environmental education （EE） is a vital dimension of modern day acumen that portends a great promise in solving the myriad environmental resource management challenges at global, regional and local levels. A study was carried out in 18 locations in the Nandi North, Nandi South and Nandi Hills districts of Kenya, which cover the Nandi Hills and Nandi Forests in Nandi County, major water catchments for Lake Victoria. A mixed methodological approach, incorporating both qualitative and quantitative data obtained from focus group discussions, key informant interviews, household survey and observations was embraced in data collection and analysis. The study reveals that there are several strategies that have been adopted by the local population and institutions involved in the management of the Nandi Hills Forests （NHFs） and that these strategies have contributed to an improvement in the perceptions of the local population in terms of the importance of environmental management of the forests. This paper highlights EE as a vehicle for ensur- ing a sustainable management of the Nandi Hills Forests. As such, it illuminates the great potential that lies in sustainably managing the NHFs by integrating formal and informal EE approaches. It further points out the functional gaps in the management of NHFs and proposes best-practices that could be adopted and/or domesticated in NHFs management regimes.

A Review of Artificial Intelligence in K-12 Education

Artificial intelligence (AI) has garnered significant interest within the educational domain over the past decade, promising to revolutionise teaching and learning. This paper provides a comprehensive overview of systematic reviews conducted from 2010 to 2023 on the implementation of AI in K-12 education. By synthesising findings from ten selected systematic reviews, this study explores the multifaceted opportunities and challenges posed by AI in education. The analysis reveals several key findings: AI’s potential to personalise learning, enhance student motivation, and improve teaching efficiency are highlighted as major strengths. However, the study also identifies critical concerns, including teacher resistance, high implementation costs, ethical considerations, and the need for extensive teacher training. These findings represent the most significant insights from the analysis, while additional findings further underscore the complexity and scope of AI integration in educational settings. The study employs a SWOT analysis to summarise these insights, identifying key areas for future research and policy development. This review aims to guide educators, policymakers, and researchers in effectively leveraging AI to enhance educational outcomes while addressing its inherent challenges.

A Discussion of Artificial Intelligence in Visual Art Education

Since ChatGPT emerged on November 30, 2022, Artificial Intelligence (AI) has been increasingly discussed as a radical force that will change our world. People have become used to AI in which such ubiquitous technologies as Siri, Google, and Netflix deploy AI algorithms to answer questions, impart information, and provide recommendations. However, many individuals including originators and backers of AI have recently expressed grave concerns. In this paper, the authors will assess what is occurring with AI in Visual Arts Education, outline positives and negatives, and provide recommendations addressed specifically for teachers working in the field regarding emerging AI usage from kindergarten to grade twelve levels as well as in higher education.

ChatGPT: Application in Chemistry Education and Challenges

The paper discusses the advancements and applications of neural networks, specifically ChatGPT, in various fields, including chemistry education and research. It examines the benefits of AI and ChatGPT, such as their ability to process and analyze large amounts of data, create personalized training systems, and offer problem-solving recommendations. The paper delves into practical applications, showcasing how ChatGPT can be utilised to augment chemistry learning. It provides examples of using ChatGPT for creating tests, generating multiple-choice questions, and studying chemistry in general. Concerns are voiced about the ethical and societal impact of AI development. In conclusion, it explores the exciting potential of AI to tackle challenges that may exceed human capabilities alone, paving the way for further exploration and collaboration between humans and intelligent machines.

Complementary Functions and Potential of Generative AI in Algorithm Education

In today’s digital era,algorithms have become an indispensable part of our daily lives and work.Algorithm education plays a crucial role in computer science and software engineering,aiming to cultivate students’problem-solving skills and computational thinking.However,traditional algorithm education often requires significant time and efforts from teachers,lacks interactivity,and provides limited examples.The rapid advancement of AI technology,particularly generative models,and large language models(LLMs),has the potential to revolutionize computer education.Models like OpenAI’s GPT-4 and ChatGPT have conversational capabilities and contribute to various aspects of computer education.GPT-3.5,as an assistant in algorithm education,assists teachers in automatically generating explanations and algorithmic examples to enhance students’understanding of algorithms.While existing research has certain limitations,such as focusing on specific scenarios and lacking comprehensive benchmark testing,this paper explores the role of ChatGPT(GPT-3.5)in algorithm education.By refining prompts and evaluating generative capabilities,the study demonstrates that GPT-3.5 holds significant potential as a teaching aid.With an average accuracy of 0.81.GPT-3.5 can generate explanations,code examples,and visualizations of the corresponding algorithms.Other tests including algorithm problem-solving and examples giving also prove the practicability of GPT-3.5 in algorithm education.

什么因素影响人们对AI的接受:EST和TAM视角

人工智能(AI)技术以前所未有的速度迅猛发展,人机交互领域迈入了崭新的历史阶段。然而个体对AI的接受程度并未如预期般高涨,这在一定程度上限制了AI技术的广泛应用及其带来的潜在增效。在深入回顾以往技术接受理论的基础上,融合生态系统理论和技术接受模型,系统性地从三个维度探讨影响AI接受度的关键因素:微观层面(个体与AI的互动)、中观层面(涉及任务要素与组织结构)以及宏观层面(文化背景、社会环境及政策导向)。本研究旨在构建一个全面的理论框架,以深入理解影响人们对AI接受度的复杂多元因素。本文特别强调了在人与AI交互过程中,层次结构的明确划分和动态互动的重要性,为人工智能与人类互动的研究领域提供了全新的理论视角。未来研究应当关注AI接受度的动态变化轨迹,深入探讨AI的情感价值及其伦理问题,从而推动社会各界更加广泛地接受和应用人工智能技术。

生成式人工智能背景下高校AI素养教育实施方案研究

生成式人工智能技术的兴起,为高等教育和图书馆带来了新的机遇和挑战。文章在提出高校AI素养教育实施目标、保障措施和具体方案的基础上,进一步从知识、技能和应用、伦理和道德以及未来发展四个维度构建AI素养框架。同时,在实施方案方面提出并强调了构建AI素养知识体系、促进AI应用与创作、加强AI伦理与安全教育、探索未来职业发展四个方面的具体措施,以帮助学生应对当前AI发展环境并培养适应未来社会发展需求的人才。

产教融合视域下AI赋能环境设计专业教学实践与探索

随着人工智能技术(AI)在教育领域的全面应用,环境设计专业的教学模式面临着新的契机。专业现有的教学体系存在诸多挑战,如理论知识与实践脱节、师资队伍建设滞后、校企合作不稳定、缺乏技术设备与场地、教学评价体系的局限性等问题。本文探讨了利用人工智能(AI)如何为环境设计专业实施产教融合提供新的实践路径,包括搭建智慧协同平台、联合开发课程内容、建设数字化评价系统、设立智创空间、加强师资队伍建设,建立“双导师制”队伍等,为环境设计专业的培养应用型人才提供新的思路和实践路径。

AI-TPACK理论视角下幼儿教师智能教育素养提升的现实挑战与应对路径

数智时代,智能技术正迅速融入幼儿教育领域,这对教师的智能教育素养提出了新的要求。本研究通过文献梳理,基于AI-TPACK理论构建了幼儿教师智能教育素养的概念框架,该框架包括智能教育意识、智能教育知识、智能教育技能、智能教育思维、智能教育伦理。同时,通过问卷调查剖析了幼儿教师智能教育素养的现状与挑战。最后从政策引领、理念更新、教学创新、道德教育、教学科研等方面着手,探寻幼儿教师智能教育素养发展的突破路径,以期为幼儿教师智能教育素养的提升提供借鉴与参考。

AI赋能教育教学数字化改革的智慧教学新模式

本文主要研究了在高职院校智慧校园建设过程中构建的AI赋能教育教学数字化改革的智慧教学新模式,包含课堂内和课堂外的教学行为,同时兼顾师生的信息化能力的培养,并覆盖教、学、管全过程。AI赋能教育教学数字化改革,推动了AI与教育教学的系统性融合,实现了教师与学生的同步发展,解决了高职院校教、学、管各环节存在的问题。

基于知识图谱的中职《数控技术》新形态AI课程研究与实践

针对中职《数控技术》科目教学中存在的理论与实际脱节、传统教学方法与学生需求不匹配等问题,提出了基于知识图谱技术构建的新形态AI课程教学模式,并在此框架下设计并实施了相关的教学实践。通过构建知识图谱,让学生在学习《数控技术》时得以形成完整的知识结构,同时运用知识图谱嵌入技术将复杂的数控知识体系转换为低维度、高效率的知识表示形式。在教学实施方面,采取混合式教学方法,利用虚拟仿真实验室和实体实训基地相结合的方式,提高学生的实操能力。对比实验结果显示,应用该新形态AI教学模式的学生在知识理解程度、技能掌握水平以及创新思维能力等方面均有显著提高。

AI产业化与产业AI化:AI大模型产业生态的行动实践、变革趋势与前沿议题

以ChatGPT、Sora等为代表的AI大模型产业生态雏形正加速显现,但对其产业行动实践概况及其影响变革趋势的研究仍不够深入。文章创新性地提出AI大模型产业生态理念,从AI产业化与产业AI化两个维度并结合多个视角深入探究AI大模型产业生态体系。结果发现AI大模型产业生态呈现AI产业化与产业AI化共生、AI原生应用与“X+AI应用”并进、通用与专用模型共存、大模型与小模型协同、开源与闭源并行、多模态融合、端云AI混合的演化态势,且AI大模型正成为产业新型基础设施,促进手工作坊、分布式智能服务生产走向工业规模化、集中式智能服务生产,重塑人机关系、颠覆产业知识模型建构与调用范式并助推AI平民化、AIGS、具身智能、物理AI、超级AI应用等加速到来。在此基础上,从AI大模型产业生态体系构建及其分工协作机制、产业生态的不同路线选择及协同共生机制、AI大模型对传统产业赋能机制、产业生态治理体系等方面提出前沿议题展望。

生成式AI热潮给高等教育带来的挑战和思考

随着生成式AI技术,特别是以ChatGPT为代表的大语言模型的快速发展,高等教育领域正面临着前所未有的机遇和挑战。文章通过系统梳理生成式AI技术的发展过程,分析了其在教育和科研情景中的应用现状。经文献对比和案例分析后发现,生成式AI技术在提升教学质量、促进个性化学习和提高科研效率方面具有显著优势,但同时也引发了数据隐私与安全、学术诚信以及责任归属等伦理和法律问题。文章进一步探讨了各国政府和国内外高校针对生成式AI技术采取的策略和具体实践,并从顶层设计、课程体系、教学模式以及潜在风险方面提出了借助生成式AI技术提升化工高等教育水平的建议,为AI时代化工卓越人才培养提供参考。

以ChatGPT为代表的AI技术与高等教育的深度融合

随着人工智能技术飞速发展,以ChatGPT为代表的人工智能技术已经逐渐成为人们关注的焦点。旨在探讨ChatGPT技术与高等教育的深度融合研究,分析其对高等教育的影响和挑战,并提出相应的解决方案。首先,介绍了ChatGPT技术的基本原理和特点,包括其语言生成模型的构建、预训练和优化等;然后,通过分析ChatGPT技术在高等教育中的应用场景,如智能教育、在线教学、个性化推荐等,探讨了其对高等教育的影响和挑战;最后,提出了一些解决方案,比如加强ChatGPT技术与高等教育的深度融合、建立完善的教育监管机制等,以应对ChatGPT技术在高等教育中面临的挑战。

AI时代的教育与评价

以ChatGPT为代表的AI技术发展对现有教育与评价体系提出挑战,并引发对教育模式与教育理念根本性变革的思考。在AI时代,对知识的了解与掌握已不再是学习的主要目的。以创新、创造、创业为内核的“三创教育”为面向未来的教育提供了一条新路径,其三个基本特征包括可个性化的学习、发现并解决真实问题/产品导向的学习、全球化的学习环境。AI为“三创教育”提供了切实可用的工具与实现方式。人机共生与共同演化(co-evolution)的时代已开启,教育工作者需要深入思考人与AI的关系,以及如何在AI时代实现教育公平和个人成长。

AI教育革命加快拔尖创新人才培养与评价

AI大爆发对社会各个方面产生巨大冲击,并在教育领域引发AI教育革命,在人类历史上可能首次实现精英教育普惠化,这为我国加快拔尖创新人才培养、早日实现教育强国目标提供了新的机遇。本文围绕如何通过AI教育革命加快拔尖创新人才培养与评价展开探讨:一是明确学习者向一流教师学习,从以教师为中心向以学习者为中心转变;二是建立客观化的AI测评系统,推动学历教育向能力教育转变;三是建立组织保障体系,从集中式学校形态转变为分布式“主题名师+AI助教”网络形态与集中式学校形态并存,让学习者有更多选择,让一流教师充分发挥作用。甄选主题名师,研发AI助教,让一流学者主导拔尖创新人才自主培养,有助于早日建成教育强国。

“人工智能+高等教育”应用场景下的AI素养框架研究

[目的/意义]AI技术已经全面融入教学的全过程中,AI素养决定了“人工智能+高等教育”的效果和质量,对教学工作中各角色的AI素养进行细分和明晰,有助于提升高等教育的数字化和智慧化。[方法/过程]以“人工智能+高等教育”的案例为研究基础,总结“人工智能+高等教育”的发展特征,深入剖析人工智能对教师、学生、管理者和教辅工作人员的能力要求,并进一步归纳AI素养核心要素,构建4种角色的AI素养框架。[结果/结论]“人工智能+高等教育”场景下其对教师的能力要求是创新教学、技术融合,对学生的能力要求是主动学习、技能多元,对管理者的能力要求是前瞻引领、数据决策,对教辅工作者的能力要求是智慧服务、资源集成;AI素养的核心要素可以归纳为思维、知识、技能和态度四大核心要素,在具体教学场景中,教师、学生、管理者和教辅人员的AI素养既有相同项,也有差异。