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Neuro-fuzzy assessment of pupil performance based on e-learning platform implementation

Dalibor Petković1, *, Nebojša Denić2

Corresponding Author:

Dalibor Petković

Affiliation(s):

1. University of Niš, Pedagogical Faculty in Vranje, Partizanska 14, 17500 Vranje, Serbia
Email: [email protected]
2. University of Priština, Faculty of Science and mathematics, Ive Lole Ribara 29, 38220
Kosovska Mitrovica Serbia
Email: [email protected]
*Corresponding author

Abstract:

Learning and teaching process for the both, learners and teachers, could be challenging task since every learner has different cognitive preconditions. Hence every learner should have different learning material and different learning paths in order to achieve given learning goals. In this article was made an e-learning platform for teacher and learners based on object-oriented approach. In the platform every learner could has personalized learning contents based on the learners’ background. The personalized learning contents could be achieved by different learning paths for each learner. Object-oriented technique by unified modelling language (UML) was performed for the modelling process of the learning platform. Afterwards the pupil performance was analyzed after the introduction of the e-learning platform by computational intelligence approach.

Keywords:

Pupils; e-learning; computational; intelligent; mathematics

Downloads: 164 Views: 2031
Cite This Paper:

Dalibor Petković, Nebojša Denić (2020). Neuro-fuzzy assessment of pupil performance based on e-learning platform implementation. Journal of the Institute of Electronics and Computer, 2, 12-27. https://doi.org/10.33969/JIEC.2020.21002.

References:

[1] Chen, W., Mason, S., Staniszewski, C., Upton, A., & Valley, M. (2012). Assessing the quality of teachers’ teaching practices. Educational Assessment, Evaluation and Accountability, 24(1), 25-41.
[2] Chowdhury, H., Alam, F., & Mustary, I. (2019). Development of an innovative technique for teaching and learning of laboratory experiments for engineering courses. Energy Procedia, 160, 806-811.
[3] Oproiu, G. C. (2015). A study about using e-learning platform (Moodle) in university teaching process. Procedia-Social and Behavioral Sciences, 180, 426-432.
[4] Wilson, R. (2014). Student absences and student abscesses: Impediments to quality teaching. The Urban Review, 46(5), 831-845.
[5] Rutland, M., & Barlex, D. (2008). Perspectives on pupil creativity in design and technology in the lower secondary curriculum in England. International Journal of Technology and Design Education, 18(2), 139-165.
[6] Glendinning, S. (2017). A new rootedness? education in the technological age. Studies in Philosophy and Education, 1-16.
[7] Eyles, A., Hupkau, C., & Machin, S. (2016). School reforms and pupil performance. Labour Economics, 41, 9-19.
[8] Kazarina, L., Khasanshin, Y., & Smyshlyaeva, L. (2015). Teaching Model of Pupils’ Research Competence Formation in the Context of Humanitarian Subject-oriented Classes of General Education School: Functional and Organizational Characteristics. Procedia-Social and Behavioral Sciences, 206, 241-246.
[9] Maietta, O. W., & Gorgitano, M. T. (2016). School meals and pupil satisfaction. Evidence from Italian primary schools. Food Policy, 62, 41-55.
[10] Bartholomew, K. J., Ntoumanis, N., Mouratidis, A., Katartzi, E., Thøgersen-Ntoumani, C., & Vlachopoulos, S. (2018). Beware of your teaching style: A school-year long investigation of controlling teaching and student motivational experiences. Learning and Instruction, 53, 50-63.
[11] Mulera, D. M. W., Ndala, K. K., & Nyirongo, R. (2017). Analysis of factors affecting pupil performance in Malawi’s primary schools based on SACMEQ survey results. International Journal of Educational Development, 54, 59-68.
[12] Salleh, N. M., & Aiman, M. S. (2015). Improving The Quality Of Pupils’ Response In Science Inquiry Teaching: A Participatory Action Research. Procedia-Social and Behavioral Sciences, 191, 1310-1316.
[13] Singh, R., & Sarkar, S. (2015). Does teaching quality matter? Students learning outcome related to teaching quality in public and private primary schools in India. International Journal of Educational Development, 41, 153-163.
[14] Mattar, D. M. (2012). Factors affecting the performance of public schools in Lebanon. International Journal of Educational Development, 32(2), 252-263.
[15] Giannakos, M. N. (2013). Enjoy and learn with educational games: Examining factors affecting learning performance. Computers & Education, 68, 429-439.
[16] Galbraith, P. L. (1986). The use of mathematical strategies: Factors and features affecting performance. Educational Studies in Mathematics, 17(4), 413-441.
[17] Hungi, N., & Postlethwaite, N. T. (2009). The key factors affecting Grade 5 achievement in Laos: emerging policy issues. Educational Research for Policy and Practice, 8(3), 211-230.
[18] Ortega-Morán, J. F., Pagador, J. B., Sánchez-Peralta, L. F., Sánchez-González, P., Noguera, J., Burgos, D., & Sánchez-Margallo, F. M. (2017). Validation of the three web quality dimensions of a minimally invasive surgery e-learning platform. International journal of medical informatics, 107, 1-10.
[19] Roskos, K., Brueck, J., & Lenhart, L. (2017). An analysis of e-book learning platforms: Affordances, architecture, functionality and analytics. International Journal of Child-Computer Interaction, 12, 37-45.
[20] Fenu, G., Marras, M., & Boratto, L. (2017). A multi-biometric system for continuous student authentication in e-learning platforms. Pattern Recognition Letters.
[21] Benta, D., Bologa, G., & Dzitac, I. (2014). E-learning platforms in higher education. case study. Procedia Computer Science, 31, 1170-1176.
[22] Benta, D., Bologa, G., Dzitac, S., & Dzitac, I. (2015). University level learning and teaching via e-learning platforms. Procedia Computer Science, 55, 1366-1373.
[23] Oproiu, G. C. (2015). A study about using e-learning platform (Moodle) in university teaching process. Procedia-Social and Behavioral Sciences, 180, 426-432.
[24] Dodun, O., Panaite, E., Seghedin, N., Nagîţ, G., Duşa, P., Neştian, G., & Slătineanu, L. (2015). Analysis of an E-learning Platform use by Means of the Axiomatic Design. Procedia CIRP, 34, 244-249.
[25] Luminita, D. C. (2011). Information security in E-learning Platforms. Procedia-Social and Behavioral Sciences, 15, 2689-2693.
[26] Srivastava, B., & Haider, M. T. U. (2017). Personalized assessment model for alphabets learning with learning objects in e-learning environment for dyslexia. Journal of King Saud University-Computer and Information Sciences.
[27] Tsolis, D., Stamou, S., Christia, P., Kampana, S., Rapakoulia, T., Skouta, M., & Tsakalidis, A. (2010). An adaptive and personalized open source e-learning platform. Procedia-Social and Behavioral Sciences, 9, 38-43.
[28] Lethbridge, T. C., & Laganiere, R. (2005). Object-oriented software engineering. New York: McGraw-Hill.
[29] Jacobson, I. (1993). Object-oriented software engineering: a use case driven approach. Pearson Education India.
[30] Rumbaugh, J., Jacobson, I., & Booch, G. (2004). Unified modeling language reference manual, the. Pearson Higher Education.
[31] Jang, J.-S.R, ANFIS: Adaptive-Network-based Fuzzy Inference Systems, IEEE Trans. On Systems, Man, and Cybernetics (1993), Vol.23, 665-685.
[32] Process, R. U. (2001). Best practices for software development teams. A Rational Software Corporation White Paper. Recuperado de: https://www. ibm. com/developerworks/rational/library/content/03July/1000/1251/1251_bestpractices_TP026B. pdf.
[33] Wang, H., & Zhang, B. (2019). Teaching a generative model: Mathematical formulation and solution framework. Computers & Industrial Engineering, 130, 119-126.
[34] Saadon, S., Rambely, A. S., & Suradi, N. R. M. (2011). The role of computer labs in teaching and learning process in the field of Mathematical Sciences. Procedia-Social and Behavioral Sciences, 18, 348-352.
[35] Spinczyk, D., Maćkowski, M., Kempa, W., & Rojewska, K. (2019). Factors influencing the process of learning mathematics among visually impaired and blind people. Computers in biology and medicine, 104, 1-9.
[36] Zou, F., Chen, D., & Xu, Q. (2019). A survey of teaching–learning-based optimization. Neurocomputing, 335, 366-383.
[37] Xu, Y., Yang, Z., Li, X., Kang, H., & Yang, X. (2019). Dynamic opposite learning enhanced teaching–learning-based optimization. Knowledge-Based Systems, 104966.