WITS 2020 pp 167-177 | Cite as

A Model of an Integrated Educational Management Information System to Support Educational Planning and Decision Making: A Moroccan Case

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 745)


The planning of education in Morocco represents an essential element in the projects implementation of the educational system, on which rests the various operations of diagnostics, realization and evaluation of the educational strategic choices. The planning profession has benefited very well from technological advance, and the country has been in the process of automating information systems for a long time. But according to our analysis, the education information system will be able to be more effective if it can adopt the techniques proposed, especially with regard to the establishment of an Integrated Information System (IIS) which groups operational systems, then use a Decision Support System (DSS) to help decision makers. As well as an Early Warning System (EWS) to predict problems, and a Recommendation System (RS) to propose realistic and effective measures. The unification of such systems will improve both the quality of the educational data management and the educational administration processes.


Education planning Integrated information system Decision support system Early warning system Recommendation system Educational management information system 


  1. 1.
    UNESCO Multi-Country Office in the Maghreb (2018) Education planner skills guide.
  2. 2.
    InfoDev (2006) Rethinking education management information systems: lessons from and options from less developed countries (Working paper no. 6).
  3. 3.
    Iyengar R, Mahal AR, Liya Aklilu, Sweetland A, Karim A, Shin H, Aliyu B, Park JE, Modi V, Berg M, Pokharel P (2014) The use of technology for large-scale education planning and decision-making, information technology for development.
  4. 4.
    Rajni J, Borah Malaya D (2015) Predictive analytics in a higher education context. IT Prof 17(4, Article number 7160892):4–33.
  5. 5.
    Anoopkumar M, Md Zubair Rahman AMJ (2016) A review on data mining techniques and factors used in educational data mining to predict student amelioration. In: Proceedings of 2016 international conference on data mining and advanced computing, SAPIENCE 2016, art. no. 7684113, pp 122–133.
  6. 6.
    Shahiri AM, Husain W, Rashid NA (2015) A review on predicting student’s performance using data mining techniques. Procedia Comput Sci 72:414–422. Scholar
  7. 7.
    Chu BC, Guarino D, Mele C, O’Connell J, Coto P (2019) Developing an online early detection system for school attendance problems: results from a research-community partnership. Cogn Behav Pract 26(1):35–45. Scholar
  8. 8.
    Márquez-Vera C, Cano A, Romero C, Noaman AYM, MousaFardoun H, Ventura S (2016) Early dropout prediction using data mining: a case study with high school students. Expert Syst 33(1):107–124. Scholar
  9. 9.
    Gitinabard N, Khoshnevisan F, Lynch CF, Wang EY (2018) Your actions or your associates? Predicting certification and dropout in MOOCs with behavioral and social features. In: Proceedings of the 11th international conference on educational data mining, EDM 2018Google Scholar
  10. 10.
    Wang Y, Zhao L (2010) Service-oriented educational management information system construction. In: Proceedings of the international conference on computer application and system modeling (ICCASM 2010), vol 7, Article number 5620647, pp v7554–v7557.
  11. 11.
    Mhon GGW, Kham NSM (2020) ETL preprocessing with multiple data sources for academic data analysis. In: IEEE conference on computer applications, ICCA 2020, Article number 9022824.
  12. 12.
    Zhu Z, Xiao F, Yang G (2011) Research on performance optimization for the web-based university educational management information system. In: International conference on intelligence science and information engineering, ISIE 2011, Article number 5997430, pp 261–264.
  13. 13.
    Hongjian T (2012) Research and implementation of educational management information system. Adv Mater Res 433–440:6702–6707.
  14. 14.
    Rajni J, Malaya DB (2015) Predictive analytics in a higher education context. IEEE Comput Soc 24–33.
  15. 15.
    Lin J, Li Y, Lian J (2020) A novel recommendation system via L0-regularized convex optimization. J Neural Comput Appl 32(6):1649–1663.

Copyright information

© Springer Nature Singapore Pte Ltd. 2022

Authors and Affiliations

  1. 1.Faculty of Sciences and Technics, Laboratory Mathematics, Computer and Engineering Sciences (MISI)Hassan First University of SettatSettatMorocco

Personalised recommendations