Proceedings of the 4th International Conference on Education, Knowledge and Information Management, ICEKIM 2023, May 26–28, 2023, Nanjing, China

Research Article

Support of Data Literacy for Cultivation of Graduate Students' Innovative Ability: a Study Based on Empirical data

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  • @INPROCEEDINGS{10.4108/eai.26-5-2023.2337284,
        author={Junping  Yao and Chengrong  Dong and Xiaojun  Li and Yi  Su},
        title={Support of Data Literacy for Cultivation of Graduate Students' Innovative Ability: a Study Based on Empirical data},
        proceedings={Proceedings of the 4th International Conference on Education, Knowledge and Information Management, ICEKIM 2023, May 26--28, 2023, Nanjing, China},
        publisher={EAI},
        proceedings_a={ICEKIM},
        year={2023},
        month={9},
        keywords={data literacy; innovation ability; supporting mechanism; graduate training; empirical data},
        doi={10.4108/eai.26-5-2023.2337284}
    }
    
  • Junping Yao
    Chengrong Dong
    Xiaojun Li
    Yi Su
    Year: 2023
    Support of Data Literacy for Cultivation of Graduate Students' Innovative Ability: a Study Based on Empirical data
    ICEKIM
    EAI
    DOI: 10.4108/eai.26-5-2023.2337284
Junping Yao1,*, Chengrong Dong1, Xiaojun Li1, Yi Su1
  • 1: Xi’an Research Inst
*Contact email: junpingy200225@163.com

Abstract

In view of the problems of unclear supporting mechanism of different dimensions of data literacy for the cultivation of graduate students' innovation ability in existing studies, which leads to an untargeted graduate students' data literacy training practice, this paper analyzes the supporting role of data literacy for the cultivation of graduate students' innovation ability based on empirical data. This paper conducts analytical modeling of data literacy from four dimensions: data attitude, data awareness, data knowledge and data skills, and designs a data literacy cultivation questionnaire. Based on the cultivation results of science and engineering graduate students in a university, the Apriori algorithm is used to conduct association analysis on literacy dimension items and innovation ability scores, and extract effective strong association rules with the thresholds of support, confidence and lift set to 0.1, 0.7 and 1 respectively. The results show that the supporting effect of data awareness on the cultivation of innovation ability is significantly higher than that of other dimensions, followed by data skills.