Predicting User Dropout from Their Online Learning Behavior

Author:

Shayan ParisaORCID,van Zaanen MennoORCID,Atzmueller MartinORCID

Publisher

Springer Nature Switzerland

Reference15 articles.

1. Appanna, S.: A review of benefits and limitations of online learning in the context of the student, the instructor and the tenured faculty. Int. J. E-Learn. 7, 5–22 (2008)

2. Atzmueller, M.: Subgroup discovery. WIREs Data Min. Knowl. Discovery 5(1), 35–49 (2015)

3. Dekker, G., Pechenizkiy, M., Vleeshouwers, J.: Predicting students drop out: a case study. In: Proceedings of the Educational Data Mining, pp. 41–50 (2009)

4. Heng, K., Sol, K.: Online learning during COVID-19: key challenges and suggestions to enhance effectiveness. Cambodian Education Forum (2020)

5. Kassymova, G., Issaliyeva, S., Aigerim, K.: E-learning and its benefits for students. Pedagogics and Psychology, pp. 249–255 (2019)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Assessing the Influence of Time on Features for the Prediction of User Dropout;2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI);2022-10

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