Skip to main content
Log in

Applying lean six sigma incorporated with big data analysis to curriculum system improvement in higher education institutions

  • Original article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

The purpose of this paper is to propose a method to improve the curriculum system in higher education institutions by taking use of the Lean Six Sigma (LSS) framework incorporated with big data analysis. The Lean Six Sigma Define-Measure-Analyze-Improve-Control methodology combined with text analysis, knowledge graph analysis and topology graph analysis are used. The proposed method can improve the curriculum system and better meet the talent market requirements, the technical requirements, and the social requirements. Little study uses the LSS framework and big data analysis to improvement the curriculum system. However, big data is an effective and efficient tool and is the trend to be used to help to make decision. This paper proposed the detailed improvement process using both LSS framework and big data analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

Download references

Funding

The study is funded by National Natural Science Foundation of China (72004139), the Science and Technology Commission of Shanghai Municipality (20ZR1454500).

Author information

Authors and Affiliations

Authors

Contributions

SS conceptualized and designed research, interpreted data, supervised the research team, WF and LJ collected and analyzed data, drafted the manuscript, SS reviewed and edited the manuscript. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Luo Lijuan.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Availability of data and material

The datasets generated and/or analyzed during the current study are not publicly available due confidential issues but are available from the corresponding author on reasonable request.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix A

Appendix A

Please rate the following statements, 1–5 (strongly disagree to strongly agree).

Questionnaire for students.

 

1–5

The coherence between the curriculum and your level

 

The appropriateness of the content of the curriculum to your needs

 

The meaningfulness of the content of the curriculum to you

 

The curriculum’s reflecting recent developments

 

The appreciation of your ideas and suggestions regarding the curriculum used

 

Overall, your satisfaction to the curriculum system

 

Please state any additional ideas or suggestions

Questionnaire for teachers

 

1–5

The coherence between your job and your personal traits

 

The coherence between the curriculum and the level of your students

 

The appropriateness of the content of the curriculum to the needs of your students

 

The meaningfulness of the content of the curriculum to you

 

The curriculum’s reflecting recent developments

 

The appreciation of your ideas and suggestions regarding the curriculum used

 

Overall, your satisfaction to the curriculum system

 

Please state any additional ideas or suggestions

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shanshan, S., Wenfei, L. & Lijuan, L. Applying lean six sigma incorporated with big data analysis to curriculum system improvement in higher education institutions. Int J Syst Assur Eng Manag 13, 641–656 (2022). https://doi.org/10.1007/s13198-021-01316-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-021-01316-3

Keywords

Navigation