Learners may obtain high scores while others obtain low scores, the reason for this is due to the failure to take into account the individual differences in learning between members of the same group through technical performance, which appear when applying the educational units, as well as their disparity in the readiness to accept and learn a certain skill, so all learners are subject to the same educational unit and the same repetitions and periods of rest, which leads to the emergence of differences in the ability to learn and performance, but learning by a generative learning strategy works to take individual differences between members of the same group and divide these groups into smaller groups according to the error in technical performance and increase the number of iterations, which helps the learner to reach the degree of automated perfection in the optimal technical performance. Because the generative learning strategy takes into account the time of work and rest between each iteration and another or between a group of iterations, and this is what made the researcher interested in studying this problem resulting from the use of old traditional strategies in learning that make it difficult to accept and learn to apply the curriculum required to learn from the learner.
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