摘要
以中国知网(CNKI)2013―2020年间收录的1132篇国内卓越农林人才培养研究文献为对象,借助Cite Space软件绘制知识图谱,从发文量与时间、学者合作网络、发文机构及关键词等方面,对国内卓越农林人才培养的研究现状与进展进行了可视化分析。研究结果表明,近年来国内相关研究的热点主要聚焦于卓越农林人才的内涵与素质、培养模式与机制、培养路径与方法3个方面。结合高频关键词的变化、科学技术的进步及教育教学改革的深入,预测今后的研究热点为借鉴国外经验、创新卓越农林人才培养模式,与互联网技术相结合、丰富卓越农林人才培养路径,以学生为中心,激发卓越农林人才培养主体的主观能动性3个方面。
This research takes 1132 domestic literatures from 2013 to 2020 retrieved and screened from CNKI as the research objects.With the help of CiteSpace,this paper conducts a quantitative visualization analysis from the number and time of literatures,scholars'cooperation network,publishing institutions and keywords.It sorts out the current research status and progress in the cultivation of outstanding agricultural and forestry talents in China.The research results show that in recent years,domestic related research has mainly focused on three aspects,including the connotation and quality,the training model and mechanism,and the training path and methods of outstanding agricultural and forestry talents.Combining the changes in high-frequency keywords,the advancement of science and technology,and the in-depth research of education and teaching reform,the author predicts that future research hotspots will foncous on the following three aspects:learning from foreign experience to innovate the training model of outstanding agricultural and forestry talents;combining with Internet technology to enrich the training path of outstanding agricultural and forestry talents;taking students as the center to stimulate the subjective initiative of the training subjects of outstanding agricultural and forestry talents.
作者
张绿水
刘纯青
喻雪晴
李宝勇
张云
ZHANG Lvshui;LIU Chunqing;YU Xueqing;LI Baoyong;ZHANG Yun(College of Landscape Architecture and Arts,Jiangxi Agricultural University,330045,Nanchang,PRC)
出处
《江西科学》
2021年第5期970-977,共8页
Jiangxi Science
基金
江西省高等学校教学改革研究省级课题(JXJG-19-3-16)
江西省学位与研究生教育教学改革研究项目(JXYJG-2016-056)
江西省学位与研究生教育教学改革研究项目(JXYJG-2020-067)。
关键词
Cite
Space
卓越农林人才
人才培育
知识图谱
国内
CiteSpace
outstanding agricultural and forestry talent
talent training
knowledge graph
domestic