With the rapid popularization of artificial intelligence technology in the field of higher education,college students are increasingly dependent on AI tools such as ChatGPT,automatic writing assistants,and intelligent...With the rapid popularization of artificial intelligence technology in the field of higher education,college students are increasingly dependent on AI tools such as ChatGPT,automatic writing assistants,and intelligent translators.Behind the convenience and efficiency,a decline trend in students’core learning abilities such as autonomous learning ability,critical thinking ability,and knowledge construction ability has gradually emerged.This study aims to explore the interactive logical mechanism between college students’reliance on AI tools and the weakening of their learning abilities,and on this basis,propose practical and feasible educational intervention strategies.Research has found that while AI tools lower the learning threshold,they also weaken students’cognitive investment and independent thinking abilities,further intensifying their reliance on technology.In this regard,this paper proposes a three-dimensional intervention path based on guided usage,ability compensation,and value reconstruction to achieve the collaborative improvement of students’technical usage ability and learning ability.This research has certain theoretical value and practical enlightenment significance for solving the structural predicament of higher education in the intelligent era.展开更多
This paper investigates the potential of AI tools,particularly AI pens such as the Caterpillar pen,to enhance children's intrinsic motivation for English language learning in China.Compared to traditional exam-ori...This paper investigates the potential of AI tools,particularly AI pens such as the Caterpillar pen,to enhance children's intrinsic motivation for English language learning in China.Compared to traditional exam-oriented English education in China,the AI pens offer a more engaging and natural language environment through features like audio readings with native pronunciation,graded difficulty levels for various reading abilities,and repetitive exposure to vocabulary and sentence structures.These features can significantly increase children's intrinsic motivation by making learning enjoyable and effective.However,challenges such as limited research on AI's impact on intrinsic motivation and the ongoing need for parental supervision exist.To maximize the benefits of AI tools,they should be integrated into daily learning activities and used in conjunction with traditional teaching methods as opposed to replacing these methods.In this way,AI technology can become a valuable asset in fostering a love of language learning and in turn improving children's overall language proficiency.展开更多
The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number...The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number,sophistication,and quality,and the profession of human translator needs to adapt to work within this new environment–and avoid being replaced by it.This paper examines the major changes that have taken place,and which could take place in the near future,and suggests ways of revising translator-training curricula to adapt to these challenges.This is essential at a time when the profession is undergoing profound changes and when all translators and future translators need to be prepared for new skills in the field of post-editing,machine-reading,machine-cultures and multidisciplinarity.After outlining the challenges that AI is causing to the profession and to the norms and values of the translation sector in its current state,the author suggests that translator training should adapt to the new reality of the profession and not to what it used to be.The profession is undergoing profound changes,and all translators and future translators need to find new skills and knowledge in order to continue to work with AI.The article concludes with recommendations on how to design AI-friendly translation programmes that can train students for the post-AI era.展开更多
AI tools have never been more accessible, and we are witnessing the transformative effects firsthand. In China’s classrooms, both educators and students are facing an unprecedented technological leap that promises to...AI tools have never been more accessible, and we are witnessing the transformative effects firsthand. In China’s classrooms, both educators and students are facing an unprecedented technological leap that promises to revolutionize how knowledge is acquired. AI is also helping rural China address challenges like an aging population and pest control, while easing the paperwork burdens of grassroots officials. Meanwhile, China’s savvy merchants are leveraging AI abroad to boost sales. Dive in to explore the latest strides of AI in China.展开更多
To the Editor,We read with great interest the recent study by Islam et al [1]. The article offers a timely and robust exploration into hypertension prediction using machine learning (ML) and explainable AI tools. The ...To the Editor,We read with great interest the recent study by Islam et al [1]. The article offers a timely and robust exploration into hypertension prediction using machine learning (ML) and explainable AI tools. The combination of XGBoost and Recursive Feature Elimination (RFE), supported by interpretability methods such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), resulted in a 91.5% accuracy and an area under the curve of 0.95, while also uncovering key predictors such as genetic pedigree coefficients and hemoglobin levels [1].展开更多
The authors discovered that Fig.4H and Fig.S3H in the published article contained incorrect images during the process of using AI tools to check published images.After carefully checking the original data,this was due...The authors discovered that Fig.4H and Fig.S3H in the published article contained incorrect images during the process of using AI tools to check published images.After carefully checking the original data,this was due to their unintended negligence during the extraction and handling of a large volume of experimental data in the process of assembling figures.The authors have replaced the incorrect images with the correct representative images.The updated Fig.4H and Fig.S3H are provided below.The original data of the figures have been provided to the Editorial Office,and the corresponding authors or the Editorial Office can be contacted for original data access.展开更多
基金The 2024 Higher Education Teaching Reform Project of Guangdong University of Science and Technology,“Teaching Practice of Human Resource Management Course Based on SPOC+FC Hybrid Teaching Mode”(GKZLGC2024024)。
文摘With the rapid popularization of artificial intelligence technology in the field of higher education,college students are increasingly dependent on AI tools such as ChatGPT,automatic writing assistants,and intelligent translators.Behind the convenience and efficiency,a decline trend in students’core learning abilities such as autonomous learning ability,critical thinking ability,and knowledge construction ability has gradually emerged.This study aims to explore the interactive logical mechanism between college students’reliance on AI tools and the weakening of their learning abilities,and on this basis,propose practical and feasible educational intervention strategies.Research has found that while AI tools lower the learning threshold,they also weaken students’cognitive investment and independent thinking abilities,further intensifying their reliance on technology.In this regard,this paper proposes a three-dimensional intervention path based on guided usage,ability compensation,and value reconstruction to achieve the collaborative improvement of students’technical usage ability and learning ability.This research has certain theoretical value and practical enlightenment significance for solving the structural predicament of higher education in the intelligent era.
文摘This paper investigates the potential of AI tools,particularly AI pens such as the Caterpillar pen,to enhance children's intrinsic motivation for English language learning in China.Compared to traditional exam-oriented English education in China,the AI pens offer a more engaging and natural language environment through features like audio readings with native pronunciation,graded difficulty levels for various reading abilities,and repetitive exposure to vocabulary and sentence structures.These features can significantly increase children's intrinsic motivation by making learning enjoyable and effective.However,challenges such as limited research on AI's impact on intrinsic motivation and the ongoing need for parental supervision exist.To maximize the benefits of AI tools,they should be integrated into daily learning activities and used in conjunction with traditional teaching methods as opposed to replacing these methods.In this way,AI technology can become a valuable asset in fostering a love of language learning and in turn improving children's overall language proficiency.
文摘The recent ability of machines to generate text and images that are fluent,coherent,and culturally nuanced is already causing major upheavals in the translation sector.Machine translation tools have exploded in number,sophistication,and quality,and the profession of human translator needs to adapt to work within this new environment–and avoid being replaced by it.This paper examines the major changes that have taken place,and which could take place in the near future,and suggests ways of revising translator-training curricula to adapt to these challenges.This is essential at a time when the profession is undergoing profound changes and when all translators and future translators need to be prepared for new skills in the field of post-editing,machine-reading,machine-cultures and multidisciplinarity.After outlining the challenges that AI is causing to the profession and to the norms and values of the translation sector in its current state,the author suggests that translator training should adapt to the new reality of the profession and not to what it used to be.The profession is undergoing profound changes,and all translators and future translators need to find new skills and knowledge in order to continue to work with AI.The article concludes with recommendations on how to design AI-friendly translation programmes that can train students for the post-AI era.
文摘AI tools have never been more accessible, and we are witnessing the transformative effects firsthand. In China’s classrooms, both educators and students are facing an unprecedented technological leap that promises to revolutionize how knowledge is acquired. AI is also helping rural China address challenges like an aging population and pest control, while easing the paperwork burdens of grassroots officials. Meanwhile, China’s savvy merchants are leveraging AI abroad to boost sales. Dive in to explore the latest strides of AI in China.
文摘To the Editor,We read with great interest the recent study by Islam et al [1]. The article offers a timely and robust exploration into hypertension prediction using machine learning (ML) and explainable AI tools. The combination of XGBoost and Recursive Feature Elimination (RFE), supported by interpretability methods such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), resulted in a 91.5% accuracy and an area under the curve of 0.95, while also uncovering key predictors such as genetic pedigree coefficients and hemoglobin levels [1].
文摘The authors discovered that Fig.4H and Fig.S3H in the published article contained incorrect images during the process of using AI tools to check published images.After carefully checking the original data,this was due to their unintended negligence during the extraction and handling of a large volume of experimental data in the process of assembling figures.The authors have replaced the incorrect images with the correct representative images.The updated Fig.4H and Fig.S3H are provided below.The original data of the figures have been provided to the Editorial Office,and the corresponding authors or the Editorial Office can be contacted for original data access.
