This study investigated the relationship between parental cognitive ability and child logical reasoning ability,and the role of academic expectation and family environment in that relationship.Based on the 2020 China ...This study investigated the relationship between parental cognitive ability and child logical reasoning ability,and the role of academic expectation and family environment in that relationship.Based on the 2020 China Family Panel Studies(CFPS)data,1491 children(girls ratio=53.78%;average grade=6.023 years,school grade standard deviation=1.825 years).Results following multiple regression model(OLS)show that the higher the parental cognitive ability,the higher the children’s logical reasoning ability.Secondly,parental academic expectation serves as a mediator between their cognitive ability and children’s logical reasoning ability for higher logical reasoning by children.Third,a possible family environment acts as a mediator in the relationship between parents’cognitive ability and children’s logical reasoning ability to be higher.We conclude from thesefindings that parents with high cognitive abilities can enhance their children’s logical reasoning skills not only by setting higher academic expectations,but also by cultivating a supportive family environment.Thesefindings imply a need for intervention to improve family quality of life to enhance children’s thinking abilities to optimize their academic learning.展开更多
Purpose To evaluate the accuracy and reasoning ability of DeepSeek-R1 and three recently released large language models(LLMs)in bilingual complex ophthalmology cases.Methods A total of 130 multiple-choice questions(MC...Purpose To evaluate the accuracy and reasoning ability of DeepSeek-R1 and three recently released large language models(LLMs)in bilingual complex ophthalmology cases.Methods A total of 130 multiple-choice questions(MCQs)related to diagnosis(n=39)and management(n=91)were collected from the Chinese ophthalmology senior professional title examination and categorized into six topics.These MCQs were translated into English.Responses from DeepSeek-R1,Gemini 2.0 Pro,OpenAI o1 and o3-mini were generated under default configurations between February 15 and February 20,2025.Accuracy was calculated as the proportion of correctly answered questions,with omissions and extra answers considered incorrect.Reasoning ability was evaluated through analyzing reasoning logic and the causes of reasoning errors.Results DeepSeek-R1 demonstrated the highest overall accuracy,achieving 0.862 in Chinese MCQs and 0.808 in English MCQs.Gemini 2.0 Pro,OpenAI o1,and OpenAI o3-mini attained accuracies of 0.715,0.685,and 0.692 in Chinese MCQs(all P<0.001 compared with DeepSeek-R1),and 0.746(P=0.115),0.723(P=0.027),and 0.577(P<0.001)in English MCQs,respectively.DeepSeek-R1 achieved the highest accuracy across five topics in both Chinese and English MCQs.It also excelled in management questions conducted in Chinese(all P<0.05).Reasoning ability analysis showed that the four LLMs shared similar reasoning logic.Ignoring key positive history,ignoring key positive signs,misinterpretation of medical data,and overuse of non–first-line interventions were the most common causes of reasoning errors.Conclusions DeepSeek-R1 demonstrated superior performance in bilingual complex ophthalmology reasoning tasks than three state-of-the-art LLMs.These findings highlight the potential of advanced LLMs to assist in clinical decision-making and suggest a framework for evaluating reasoning capabilities.展开更多
基金supported by scientific research fund of Jiangxi Provincial Social Sciences“14th Five-Year Plan”(No.23SH05).
文摘This study investigated the relationship between parental cognitive ability and child logical reasoning ability,and the role of academic expectation and family environment in that relationship.Based on the 2020 China Family Panel Studies(CFPS)data,1491 children(girls ratio=53.78%;average grade=6.023 years,school grade standard deviation=1.825 years).Results following multiple regression model(OLS)show that the higher the parental cognitive ability,the higher the children’s logical reasoning ability.Secondly,parental academic expectation serves as a mediator between their cognitive ability and children’s logical reasoning ability for higher logical reasoning by children.Third,a possible family environment acts as a mediator in the relationship between parents’cognitive ability and children’s logical reasoning ability to be higher.We conclude from thesefindings that parents with high cognitive abilities can enhance their children’s logical reasoning skills not only by setting higher academic expectations,but also by cultivating a supportive family environment.Thesefindings imply a need for intervention to improve family quality of life to enhance children’s thinking abilities to optimize their academic learning.
基金supported by the Global STEM Professorship Scheme(P0046113)the Start-up Fund for RAPs under the Strategic Hiring Scheme(P0048623)from HKSAR.
文摘Purpose To evaluate the accuracy and reasoning ability of DeepSeek-R1 and three recently released large language models(LLMs)in bilingual complex ophthalmology cases.Methods A total of 130 multiple-choice questions(MCQs)related to diagnosis(n=39)and management(n=91)were collected from the Chinese ophthalmology senior professional title examination and categorized into six topics.These MCQs were translated into English.Responses from DeepSeek-R1,Gemini 2.0 Pro,OpenAI o1 and o3-mini were generated under default configurations between February 15 and February 20,2025.Accuracy was calculated as the proportion of correctly answered questions,with omissions and extra answers considered incorrect.Reasoning ability was evaluated through analyzing reasoning logic and the causes of reasoning errors.Results DeepSeek-R1 demonstrated the highest overall accuracy,achieving 0.862 in Chinese MCQs and 0.808 in English MCQs.Gemini 2.0 Pro,OpenAI o1,and OpenAI o3-mini attained accuracies of 0.715,0.685,and 0.692 in Chinese MCQs(all P<0.001 compared with DeepSeek-R1),and 0.746(P=0.115),0.723(P=0.027),and 0.577(P<0.001)in English MCQs,respectively.DeepSeek-R1 achieved the highest accuracy across five topics in both Chinese and English MCQs.It also excelled in management questions conducted in Chinese(all P<0.05).Reasoning ability analysis showed that the four LLMs shared similar reasoning logic.Ignoring key positive history,ignoring key positive signs,misinterpretation of medical data,and overuse of non–first-line interventions were the most common causes of reasoning errors.Conclusions DeepSeek-R1 demonstrated superior performance in bilingual complex ophthalmology reasoning tasks than three state-of-the-art LLMs.These findings highlight the potential of advanced LLMs to assist in clinical decision-making and suggest a framework for evaluating reasoning capabilities.
