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Integrated Models-Driven Framework to Generate Various Online and Print Tests

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Book cover Computer Information Systems and Industrial Management (CISIM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13293))

Abstract

The ongoing digital transformation influence all fields from education to economics. That is why many efforts are taken to develop different business models to reflect the new reality. The e-tests are the core of contemporary e-learning and are suitable to conduct proper checks about the level of competency for different occupations. In this regard the current article describes an integrated framework based on different optimization models to select a set of questions to compose e-tests or print tests. The basic workflow algorithm of this framework is described. The framework’ distinguish feature is the possibility to generate different levels of tests’ complexity thanks to the specifics of formulated single criterion mixed-integer and multi-criteria models. The applicability of the integrated models-driven framework is demonstrated by using a test bank with predefined questions with different difficulties. The obtained results prove the possibility to generate tests with different degrees of complexity accordingly to the formulated models.

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References

  1. Saeed, K.: Limits to growth concepts in classical economics. In: Cavana, R.Y., Dangerfield, B.C., Pavlov, O.V., Radzicki, M.J., Wheat, I.D. (eds.) Feedback Economics. CST, pp. 217–246. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-67190-7_9

    Chapter  Google Scholar 

  2. Petrova, P., Kostadinova, I., Alsulami, M.H.: Embedded intelligence in a system for automatic test generation for smoothly digital transformation in higher education. In: Sgurev, V., Jotsov, V., Kacprzyk, J. (eds.) Advances in Intelligent Systems Research and Innovation. SSDC, vol. 379, pp. 441–461. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-78124-8_20

    Chapter  Google Scholar 

  3. Kostadinova, I., Rasheva-Yordanova, K., Ivanov, I., Petrova, P.: Automated system for generating and validation a learning tests. In: ICERI2017 Proceedings, pp. 414–424 (2017). http://dx.doi.org/10.21125/iceri.2017.0160

  4. Borissova, D., Mustakerov, I.: E-learning tool for visualization of shortest paths algorithms. Trends J. Sci. Res. 2(3), 84–89 (2015)

    Article  Google Scholar 

  5. Meng, W., Qu, R.: Automated design of search algorithms: learning on algorithmic components. Expert Syst. Appl. 185, 115493 (2021). https://doi.org/10.1016/j.eswa.2021.115493

    Article  Google Scholar 

  6. 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). https://doi.org/10.20368/1971-8829/142

  7. Yoshinov, R., Iliev, O.: How to learn computer science, using computer science. Int. J. Comput. 2, 223–228 (2017)

    Google Scholar 

  8. Aldiab, A., Chowdhury, H., Kootsookos, A., Alam, F., Allhibi, H.: Utilization of learning management systems (LMSs) in higher education system: A case review for Saudi Arabia. Energy Proc. 160, 731–737 (2019)

    Article  Google Scholar 

  9. 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). https://doi.org/10.1016/j.cptl.2019.03.014

    Article  Google Scholar 

  10. 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). http://dx.doi.org/10.7936/K7Z60KZK

  11. 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 (2018). https://doi.org/10.1109/ITHET.2018.8424768

  12. Borissova, D., Keremedchiev, D., Tuparov, G.: Multi-criteria model for questions selection in generating e-education tests involving gamification. TEM J. – Technol. Educ. Manag. Inform. 9(2), 779–785 (2020). https://doi.org/10.18421/TEM92-47

  13. Kostadinova, I., Rasheva-Yordanova, K., Garvanova, M.: Analysis of algorithms for generating test questions in e-testing systems. In: 11th International Conference on Education and New Learning Technologies, EDULEARN 2019, pp. 1714–1719 (2019). http://dx.doi.org/10.21125/edulearn.2019.0498

  14. Borissova, D.: A group decision making model considering experts competency: an application in personnel selections. Compt. Rendus l’Acad. Bulgare Sci. 71(11), 1520–1527 (2018)

    Google Scholar 

  15. Yoshinov, R., Chehlarova, T., Kotseva, M.: The e-facilitator as a key player for interactive dissemination of STEAM resources for e-learning via webinar. In: Auer, M.E., Tsiatsos, T. (eds.) IMCL 2019. AISC, vol. 1192, pp. 675–686. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-49932-7_63

    Chapter  Google Scholar 

  16. Andreev, R., Borissova, D., Shikalanov, A., Yorgova, T.: Model-driven design of eMedia: virtual technology transfer office. In: Lugmayr, A., Stojmenova, E., Stanoevska, K., Wellington, R. (eds.) Information Systems and Management in Media and Entertainment Industries. ISCEMT, pp. 279–298. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49407-4_14

    Chapter  Google Scholar 

  17. Khider, H., Hammoudi, S., Meziane, A.: Business process model recommendation as a transformation process in MDE: conceptualization and first experiments. In: 8th International Conference on Model-Driven Engineering and Software Development – MODELSWARD, pp. 65–75 (2020). http://dx.doi.org/10.5220/0009155600650075

  18. Shamsujjoha, M., Grundy, J., Li, L., Khalajzadeh, H., Lu, Q.: Developing mobile applications via model driven development: a systematic literature review. Inf. Softw. Technol. 140, 106693 (2021). https://doi.org/10.1016/j.infsof.2021.106693

    Article  Google Scholar 

  19. Moradi, H., Zamani, B., Zamanifar, K.: CaaSSET: a framework for model-driven development of context as a service. Futur. Gener. Comput. Syst. 105, 61–95 (2020). https://doi.org/10.1016/j.future.2019.11.028

    Article  Google Scholar 

  20. Santos, F., Nunes, I., Bazzan, A.L.C.: Quantitatively assessing the benefits of model-driven development in agent-based modeling and simulation. Simul. Model. Pract. Theory 104, 102126 (2020). https://doi.org/10.1016/j.simpat.2020.102126

    Article  Google Scholar 

  21. Badreddin, O., Lethbridge, T.C.: Combining experiments and grounded theory to evaluate a research prototype: lessons from the umple model-oriented programming technology. In: First International Workshop on User Evaluation for Software Engineering Researchers (USER), pp. 1–4 (2012). https://doi.org/10.1109/USER.2012.6226575

  22. Lethbridge, T.C., et al.: Umple: model-driven development for open source and education. Sci. Comput. Program. 208, 102665 (2021). https://doi.org/10.1016/j.scico.2021.102665

    Article  Google Scholar 

  23. Orabi, M., Orabi, A., Lethbridge, T.: Umple as a template language (Umple-TL). In: Proceedings of 7th International Conference on Model-Driven Engineering and Software Development – MODELSWARD, pp. 98–106 (2019). http://dx.doi.org/10.5220/0007382000980106

  24. Joy, J., Pillai, R.V.G.: Review and classification of content recommenders in E-learning environment. J. King Saud Uni. – Comput. Inf. Sci. (2021). https://doi.org/10.1016/j.jksuci.2021.06.009

  25. Bachman, L.F.: Statistical Analyses for Language Assessment. Cambridge University Press, Cambridge (2004)

    Book  Google Scholar 

  26. Tasci, T., Parlak, Z., Kibar, A., Tasbasi, N., Cebeci, H.I.: A novel agent-supported academic online examination system. Educ. Technol. Soc. 17(1), 154–168 (2014)

    Google Scholar 

  27. Marler, R.T., Arora, J.S.: Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. Optim. 26, 369–395 (2004)

    Article  MATH  MathSciNet  Google Scholar 

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Acknowledgements

This work is supported by the Bulgarian National Science Fund by the project “Mathematical models, methods and algorithms for solving hard optimization problems to achieve high security in communications and better economic sustainability”, KP-06-N52/7/19-11-2021.

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Authors and Affiliations

  1. Institute of Information and Communication Technologies at the Bulgarian Academy of Sciences, 1113, Sofia, Bulgaria

    Daniela Borissova & Nikolay Buhtiyarov

  2. Laboratory of Telematics at the Bulgarian Academy of Sciences, Sofia, Bulgaria

    Radoslav Yoshinov

  3. University of Library Studies and Information Technologies, 1784, Sofia, Bulgaria

    Magdalena Garvanova & Ivan Garvanov

Authors
  1. Daniela Borissova
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  2. Nikolay Buhtiyarov
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  3. Radoslav Yoshinov
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  4. Magdalena Garvanova
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  5. Ivan Garvanov
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Corresponding author

Correspondence to Daniela Borissova .

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Editors and Affiliations

  1. Bialystok University of Technology, Bialystok, Poland

    Khalid Saeed

  2. VSB - Technical University of Ostrava, Ostrava, Czech Republic

    Jiří Dvorský

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Borissova, D., Buhtiyarov, N., Yoshinov, R., Garvanova, M., Garvanov, I. (2022). Integrated Models-Driven Framework to Generate Various Online and Print Tests. In: Saeed, K., Dvorský, J. (eds) Computer Information Systems and Industrial Management. CISIM 2022. Lecture Notes in Computer Science, vol 13293. Springer, Cham. https://doi.org/10.1007/978-3-031-10539-5_23

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  • DOI: https://doi.org/10.1007/978-3-031-10539-5_23

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  • Online ISBN: 978-3-031-10539-5

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