Computer Science

Computer Science ›› 2026, Vol. 53 ›› Issue (8): 9-19.doi: 10.11896/jsjkx.250600231

• Database & Big Data & Data Science • Previous Articles     Next Articles

Construction and Generation of SOR Label System for Learner Personalized Portrait

LAI Yingxu, ZHANG Yuwei, ZHUANG Junxi   

  1. School of Computer Science, Beijing University of Technology, Beijing 100124, China
  • Received:2025-06-30 Revised:2025-10-13 Online:2026-08-15 Published:2026-08-17
  • About author:LAI Yingxu,born in 1973,Ph.D,professor,is a member of CCF(No.F3875M).Her main research interests include network security and trusted computing.
    ZHUANG Junxi,born in 1981,Ph.D,lecturer.Her main research interests include network security and trusted computing.
  • Supported by:
    Key Project of Beijing Education Science “14th Five Year Plan” for 2023(CGAA23034).

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Abstract: With the development of online education and personalized education,how to utilize massive online learner data to construct accurate and personalized learner portrait has become a current research hotspot.Addressing the issues in existing learner portrait research,such as neglecting individual differences and lacking systematic theoretical guidance,a method for constructing and generating a SOR label system for learner personalized portrait is proposed.Firstly,this method combines SOR theory to construct a personalized label system,extracts personalized labels,and explores individual differences among learners.Secondly,based on a multi-label classification model,it learns the complex relationship between features and personalized labels,achieving accurate prediction of personalized labels and dynamic generation of portrait labels.Finally,it constructs learner portrait based on SOR theory,revealing the relationship between environmental stimuli,individual cognition,and learning behavior.Experiment is conducted based on a public MOOC dataset,validating the effectiveness of the proposed label system through predicting the dropout rate in real teaching scenarios,achieving a 0.91% improvement in prediction accuracy over the second-best label system.The results verify the effectiveness of this method in mining learner personalized labels and constructing label systems.

Key words: Learner portrait, SOR theory, Personalized label, Label construction, Multi label classification

CLC Number: 

  • TP391
[1] HAN X Q,YI J,ZHOU W,et al.Personalized Online Course Recommendation Model Based on Hypergraph Enhanement[J].Computer Engineering and Applications,2026,62(2):257-265.
[2] HAO X J,GU X Q.AI reshapes the concept of knowledge:Knowledge creation and educational development under the influence of data science[J].China Distance Education,2023,43(5):13-23.
[3] XU F,YING J R.Literature review of persona at home andabroad[J].Research on Library Science,2020(12):7-16.
[4] WU F,LYU F,REN J,et al.Characterizing Internet card user portraits for efficient churn prediction model design[J].IEEE Trans on Mobile Computing,2023,23(2):1735-1752.
[5] LI G,CHEN W,YAN X,et al.Modeling and analysis of group user portrait through WeChat mini program[J].Wireless Communications and Mobile Computing,2022,2022(1):2515962.
[6] SHAO Y B,QIN Y H,CUI Y J,et al.A method for generating user portraits by integrating multi-granularity information[J].Application Research of Computers,2024,41(2):401-407.
[7] FAN H D.Research on the construction method of learner digit-al portraits based on learning analytics technology[D].Harbin:Harbin Institute of Technology,2023.
[8] WANG S Q,LIU Z F,WANG J M,et al.A Review of Scholar Profiling Research[J].Library and Information Service,2022,66(20):73-81.
[9] YUAN S,TANG J,GU X T.A survey on scholar profiling techniques in the open Internet[J].Journal of Computer Research and Development,2018,55(9):1903-1919.
[10] CHEN Q,LIU R D.Contemporary Educational Psychology[M].Beijing:Beijing Normal University Press,2007.
[11] LI Z H,SHI J C,WANG Y C.The impact of AI technologyadoption on the innovation performance of researchers[J].Research in Science and Technology.2025,43(10):2056-2065.
[12] ZHAI M Y,CHENG J,WANG S T,et al.Analysis of student educational portraits based on K-prototype clustering[J].Journal of Dalian University of Technology(Social Sciences Edition),2021,42(6):22-31.
[13] ALVAREZ-GARCIA M,ARENAS-PARRA M,IBAR-ALON-SO R.Uncovering student profiles.An explainable cluster analysis approach to PISA 2022[J].Computers & Education,2024,223:105166.
[14] LING Y L,ZHANG X,LI X,et al.Application of improved k-means algorithm in student consumption portrait[J].Computer Technology and Development,2021,31(10):122-127.
[15] LIAO S T.Construction and application of blended universityEnglish learner portraits[D].Chengdu:University of Electronic Science and Technology of China,2024.
[16] ZHAO C,LI X.Research on the construction of tag models for learning portraits in online learning spaces[J].Computer Technology and Development.2023,33(10):176-182.
[17] ZHAI M Y,WANG S T,WANG Y Z,et al.An interpretable prediction method for university student academic crisis warning[J].Complex & Intelligent Systems,2022,8(1):323-336.
[18] RICO-JUAN J R,SÁNCHEZ-CARTAGENA V M,VALERO-MAS J J,et al.Identifying Student Profiles Within Online Judge Systems Using Explainable Artificial Intelligence[J].IEEE Trans on Learning Technologies,2023,16(6):955-969.
[19] TIAN Y H.Research on MOOC learning situation early warning based on learner portraits[D].Shanghai:East China Normal University,2020.
[20] HUANG S J,XU M.Research on the impact mechanism of mobile e-commerce live broadcasting on users’ online purchase intention based on SOR theory[J].Statistics and Management,2021,7(7):122-128.
[21] MA J W,ZHANG Y F,PENG L H,et al.Empirical study on user portraits of FoMO in mobile social media in the new media environment[J].Library and Information Work,2024,68(6):60-71.
[22] CHARTE F,RIVERA A J,DEL JESUS M J,et al.MLS-MOTE:Approaching imbalanced multilabel learning through synthetic instance generation[J].Knowledge-Based Systems,2015,89:385-397.
[23] VANDENHENDE S,GEORGOULIS S,VAN GANSBEKE W,et al.Multi-task learning for dense prediction tasks:A survey[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2021,44(7):3614-3633.
[24] VASWANI A,SHAZEER N,PARMAR N,et al.Attention isall you need[C]//Proceedings of the 31st International Confe-rence on Neural Information Processing Systems.2017:5998-6008.
[25] YANG M H,REN C,XIE B L,et al.Employment profiling of students based on campus behavioral characteristics[J].Library Tribune,2024,44(1):62-70.
[26] LI R.Research on behavioral label system of college English online learner profile[D].Chengdu:University of Electronic Science and Technology of China,2021.
[27] GE D,WU Y W,LIU S N Y.Research on low-cost self-evolving learner profile model[J].Computer Engineering and Applications,2023,59(11):141-150.
[28] HUANG Y M,ZHAO C C.Research on third-level short video user profiling based on improved topic modeling method[J].Computer Science,2024,51(S1):698-704.
[29] WAN J S,CHEN L,WU J H,et al.Social user profile modeling based on KD-Tree clustering[J].Computer Science,2019,46(S1):442-445,467.
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