Intelligent System for Generation and Evaluation of e-Learning Tests Using Integer Programming

  • Daniela BorissovaEmail author
  • Delyan Keremedchiev
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1126)


The major challenge in e-learning is the assessment as a tool to measure students’ knowledge. In this regard an intelligent system for generation and evaluation of e-learning tests using integer programming is proposed. The described system aims to determine a number of questions with different degree of difficulty from a predefined set of questions that will compose the test. It allows also generating tests with different level of complexity. To realize the selection of the questions for different levels of tests two optimization models are proposed. Both of these models are of linear integer programming. The first of them determines the minimum number of questions by selecting among more difficult questions, while the second one aims to maximize the number of questions by selecting among less difficult questions. The proposed intelligent system for generating and evaluating e-learning tests with different levels of complexity is implemented as web-based application. The numerical testing of the developed prototype of the intelligent system for generation of tests for e-learning purposes is demonstrated in a web programming course.


Intelligent system E-tests Algorithm Integer programming Mathematical models 


  1. 1.
    Borissova, D., Keremedchiev, D.: Group decision making in evaluation and ranking of students by extended simple multi-attribute rating technique. Cybern. Inf. Technol. 18(3), 45–56 (2019)Google Scholar
  2. 2.
    Mustakerov, I., Borissova, D.: A framework for development of e-learning system for computer programming: application in the C programming language. J. e-Learn. Knowl. Soc. 13(2), 89–101 (2017)Google Scholar
  3. 3.
    Mustakerov, I., Borissova, D.: A conceptual approach for development of educational web-based e-testing system. Expert Syst. Appl. 38(11), 14060–14064 (2011)Google Scholar
  4. 4.
    Marinova, G., Guliashki, V., Chikov, O.: Concept of online assisted platform for technologies and management in communications OPTIMEK. Int. J. Bus. Technol. 3(1) (2014). Scholar
  5. 5.
    Hennig, S., Staatz, C., Bond, J.A., Leung, D., Singleton, J.: Quizzing for success: evaluation of the impact of feedback quizzes on the experiences and academic performance of undergraduate students in two clinical pharmacokinetics courses. Curr. Pharm. Teach. Learn. 11, 742–749 (2019). Scholar
  6. 6.
    ClassMarker. Accessed 30 Aug 2019
  7. 7.
    Marsh, E.J., Cantor, A.D.: Learning from the test: dos and don’ts for using multiple-choice tests. In: McDaniel, M., Frey, R., Fitzpatrick, S., Roediger, H.L. (eds.) Integrating Cognitive Science with Innovative Teaching in STEM Disciplines (2014).
  8. 8.
    Tuparov, G., Keremedchiev, D., Tuparova, D., Stoyanova, M.: Gamification and educational computer games in open source learning management systems as a part of assessment. In: 17th International Conference Information Technology Based Higher Education and Training (ITHET), pp. 1–5. IEEE (2018)Google Scholar
  9. 9.
    Paunova-Hubenova, E., Terzieva, V., Dimitrov, S., Boneva, Y.: Integration of game-based teaching in Bulgarian schools state of art. In: Ciussi, M. (ed.) 12th European Conference on Game-Based Learning, ECGBL 2018, pp. 516–525 (2018)Google Scholar
  10. 10.
    Balabanov, T., Keremedchiev, D., Goranov, I.: Web distributed computing for evolutionary training of artificial neural networks. In: International Conference InfoTech-2016, pp. 210–216 (2016)Google Scholar
  11. 11.
    Ma, J., Liu, Q.: The design and development of web-based examination system. In: Wang, Y. (ed.) Education Management, Education Theory and Education Application. Advances in Intelligent and Soft Computing, vol. 109, pp. 117–121. Springer, Heidelberg (2011). Scholar
  12. 12.
    Tashu, T.M., Esclamado, J.P., Horvath, T.: Intelligent on-line exam management and evaluation system. In: Coy, A., Hayashi, Y., Chang, M. (eds.) ITS 2019. LNCS, vol. 11528, pp. 105–111. Springer, Cham (2019). Scholar
  13. 13.
    Stancheva, N., Stoyanova-Doycheva, A., Stoyanov, S., Popchev, I., Ivanova, V.: A model for generation of test questions. Comptes rendus de l’Academie bulgare des Sciences 70(5), 619–630 (2017)Google Scholar
  14. 14.
    Veldkamp, B.P.: Computerized test construction. In: Wright, J.D. (ed.) The International Encyclopedia of Social and Behavioral Sciences, 2nd edn, pp. 510–514. Elsevier, Amsterdam (2015)CrossRefGoogle Scholar
  15. 15.
    Veldkamp, B.P.: Multiple objective test assembly problems. J. Educ. Meas. 36(3), 253–266 (1999)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Kubiszyn, T., Borich, G.D.: Educational Testing and Measurement: Classroom Application and Practise. Harper Collins Publishers, New York (1990)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Information and Communication Technologies at Bulgarian Academy of SciencesSofiaBulgaria
  2. 2.University of Library Studies and Information TechnologiesSofiaBulgaria
  3. 3.New Bulgarian UniversitySofiaBulgaria

Personalised recommendations