Abstract
E-education allows significantly automating the learning process. One of the key elements of e-learning is testing. The use of tests allows an objective and unbiased assessment of student knowledge. However, this automated approach requires high-quality tests that are relevant to the theoretical material and practical skills acquired by the student while taking an e-learning course. This paper proposes the use of the K-medians clustering algorithm, which makes it possible to divide the test questions into separate clusters in order to analyze them and further improve the tests, and possibly the entire e-course as a whole. The paper presents fragments of program code that can be used by other researchers in solving clustering problems.
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References
Baftiu, N.: Application of intelligent applications for controlling software and hardware devices. Technium Rom. J. Appl. Sci. Technol. 3(7), 1–13 (2021)
Hassouni, B.E., et al.: Realization of an educational tool dedicated to teaching the fundamental principles of photovoltaic systems. J. Phys: Conf. Ser. 1399(2), 022044 (2019). https://doi.org/10.1088/1742-6596/1399/2/022044
Kaniadakis, A., Padumadasa, E.U.: Can e-learning enable the transition to university for computing and electronic engineering students from low socio-economic status? A socio-cultural approach. J. Inf. Syst. Educ. 33(1), 87–97 (2022)
Khazaal, Y.M., Hammo, A.Y.: Survey on software code clone detection. Technium Rom. J. Appl. Sci. Technol. 4(3), 28–36 (2022). https://doi.org/10.47577/technium.v4i3.6361
Rozhkov, A., Bulatova, M., Noda, L.: Mobile blogging as a mean to improve journalism education. Int. J. Interact. Mob. Technol. (iJIM) 14(21), 38–50 (2020). https://doi.org/10.3991/ijim.v14i21.18465
Tyrkba, K.V., Asmyatullin, R.R., Ruzina, E.I.: Drivers of e-learning market: case of China. Res. Econ. Anthropol. 42, 175–185 (2022). https://doi.org/10.1108/S0190-128120220000042017
Gamage, S.H.P.W., Ayres, J.R., Behrend, M.B.: A systematic review on trends in using Moodle for teaching and learning. Int. J. STEM Educ. 9(1), 1–24 (2022). https://doi.org/10.1186/s40594-021-00323-x
Tsarev, R.Y., Yamskikh, T.N., Evdokimov, I.V., Prokopenko, A.V., Rutskaya, K.A., Everstova, V.N., Zhigalov, K.Y.: An approach to developing adaptive electronic educational course. Adv. Intel. Syst. Comput. 986, 332–341 (2019). https://doi.org/10.1007/978-3-030-19813-8_34
Zaini, A., Santoso, H., Sulistyanto, M.P.T.: Fault tolerance strategy to increase Moodle service reliability. J. Phys: Conf. Ser. 1869(1), 012095 (2021). https://doi.org/10.1088/1742-6596/1869/1/012095
Chernyshov, P.S.: Analysis of the latest changes in methodological recommendations in the field of information support of the educational process. Int. J. Human. Nat. Sci. 9–2(60), 61–66. https://doi.org/10.24412/2500-1000-2021-9-2-61-66
Alnasraween, M.S., Shahadab, F.H.: Obstacles of teaching distance universities courses in light of E-learning quality standards. Cypriot J. Educ. Sci. 17(4), 1244–1257 (2022). https://doi.org/10.18844/cjes.v17i4.7145
Long, R.W., III., Watanabe, H.: Adapting e-learning for Japanese EFL students. Int. J. Inform. Educ. Technol. 12(4), 299–304 (2022). https://doi.org/10.18178/ijiet.2022.12.4.1618
Putro, H.P.N., Hadi, S., Rajiani, I., Abbas, E.W.: Mutiani: adoption of e-learning in Indonesian higher education: innovation or irritation? Educ. Sci. Theor. Pract. 22(1), 36–45 (2022). https://doi.org/10.12738/jestp.2022.1.0004
Kansal, A.K., Gautam, J., Chintalapudi, N., Jain, S., Battineni, G.: Google trend analysis and paradigm shift of online education platforms during the COVID-19 pandemic. Infect. Dis. Rep. 13(2), 418–428 (2021). https://doi.org/10.3390/idr13020040
Maatuk, A.M., Elberkawi, E.K., Aljawarneh, S., Rashaideh, H., Alharbi, H.: The COVID-19 pandemic and e-learning: challenges and opportunities from the perspective of students and instructors. J. Comput. High. Educ. 34(1), 21–38 (2021). https://doi.org/10.1007/s12528-021-09274-2
Odeh, A., Keshta, I.: Impact of COVID-19 pandemic on education: moving towards e-learning paradigm. Int. J. Eval. Res. Educ. 11(2), 588–595 (2022). https://doi.org/10.11591/ijere.v11i2.21945
Nikolaeva, I., Sleptsov, Yu., Gogoleva, I., Mirzagitova, A., Bystrova, N., Tsarev, R.: Statistical hypothesis testing as an instrument of pedagogical experiment. In: AIP Conference Proceedings (2022)
Chen, B.: Application of cluster analysis algorithm in the construction of education platform. Lect. Notes Data Eng. Commun. Technol. 98, 424–430 (2022). https://doi.org/10.1007/978-3-030-89511-2_54
Hu, L.: Research on the construction of college English online education resources based on cluster analysis algorithm. In: ACM International Conference Proceeding Series, pp. 2763–2767 (2021). https://doi.org/10.1145/3482632.3487510
Ushakov, A.V., Vasilyev, I.: A computational comparison of parallel and distributed K-median clustering algorithms on large-scale image data. Commun. Comput. Inform. Sci. 1090, 119–130 (2019). https://doi.org/10.1007/978-3-030-33394-2_10
Zhu, H., Shi, Y.: Brain storm optimization algorithms with k-medians clustering algorithms. In: Proceedings of the 7th International Conference on Advanced Computational Intelligence, ICACI 2015, 7184758, pp. 107–110. IEEE, Wuyi (2015). https://doi.org/10.1109/ICACI.2015.7184758
Craw, S.: Manhattan distance. In: Sammut, C., Webb, G.I. (eds.) Encyclopedia of Machine Learning. Springer, Boston (2011). https://doi.org/10.1007/978-0-387-30164-8_506
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Aljarbouh, A. et al. (2023). Application of the K-medians Clustering Algorithm for Test Analysis in E-learning. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Software Engineering Application in Systems Design. CoMeSySo 2022. Lecture Notes in Networks and Systems, vol 596. Springer, Cham. https://doi.org/10.1007/978-3-031-21435-6_21
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