iSchools培养计划知识挖掘下的情报学教育及人才培养

Research on Teaching of Information Science Based on iSchool Training Program Knowledge Mining

[目的/意义]情报学作为信息科学群的一个分支学科,在大数据时代呈现出更高的职责要求,iSchool这一高校信息学院联盟培养符合新时代需求的信息领域人才。[方法/过程]为探索情报学学科的教学模式和特点,文章以iSchool培养计划为研究对象,分别基于Bi-LSTM-CRF和BERT深度学习方法,构建能力和研究领域的自动抽取模型,挖掘其中情报学科教学信息。在模型的基础上,完成iSchool培养计划的知识挖掘,统计iSchool院校对学生的能力要求以及主要的研究领域,并按照iSchool等级进行系统和深入的统计分析。[结果/结论]在上述分析的基础上,发现和总结当前情报学教育的发展态势,为我国情报学教育体系设计提供切实可行的建议。

[Purpose/significance]Information science,as a branch of information science group,shows higher responsibility requirements in the era of big data.ISchool,an information college alliance,cultivates talents in the information field meeting the needs of the new era.[Method/process]In order to explore the teaching mode and characteristics of iSchool,we taking iSchool training scheme as the object of research,based on Bi-LSTM-CRF and BERT model respectively,constructs an automatic extraction model of ability and research field,and mines the teaching information of intelligence discipline.On the basis of the model,we focus on 60 iSchools’training scheme and analyzed the requirements of students’major abilities and the major areas of study statistically.We also did comparative studies according to the iSchool level.[Result/conclusion]On the basis of the above analysis,we provides practical suggestions for the teaching of information subject in China.