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Recommending effective testers in crowdsourced software testing is a challenge. In this paper, we study the improvement of crowdsourced software testers' skills over time. We propose the project difficulty coefficient to eliminate the influence of the item on the tester's score. The hyperbolic learning curve model and exponential learning curve model are used to fit the learning ability of the testers. The experimental results show that when the test data is large, the exponential learning curve can better simulate the improvement of testers' skills.