Abstract
The advancement of innovations empowers learners to take in more viable, proficiently, adaptable and serenely. Smart learning, an idea that portrays learning in advanced age, has increased expanded consideration. This paper examines the meaning of Smart learning and shows an applied structure. The smart teaching method structure incorporates class-based separated direction [13], gather based communitarian learning, individual-based customized learning and mass-based generative learning. This paper proposes the Higher Particle Optimization (HPO) clustering as an instrument to trigger learning engagement activities. Utilizing (HPO), learners are clustered utilizing likeness measures construed from watched skill, meta-fitness, and certainty values, notwithstanding viability measures of instructional devices. A reenactment thinks about demonstrates that the (HPO)-based clustering is more ideal than Parallel M-implies grouping.
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Elhoseny, H., Elhoseny, M., Abdelrazek, S., Riad, A.M. (2018). Evaluating Learners’ Progress in Smart Learning Environment. In: Hassanien, A., Shaalan, K., Gaber, T., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017. AISI 2017. Advances in Intelligent Systems and Computing, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-64861-3_69
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DOI: https://doi.org/10.1007/978-3-319-64861-3_69
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