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Abstract
The teaching mode combining Massive Open Online Course (MOOC) with flipped classroom has been emerged in recent years since the arrangement can enhance obviously students’ learning outcome. In this paper, we proposed an ensemble approach based on genetic algorithm (GA) for feature selection (EA-GA) for MOOC data analysis, focusing on the prediction of students’ learning outcome. The work is based on the implementation of an online course from a college. The tracking data is collected from both the online MOOC platform and the offline classroom. After combining all data together, a GA based ensemble system is designed to predict students’ academic performances. Some other machining learning algorithms are also derived for performance comparison of different algorithms. Simulation results showed the proposed the EA-GA preforms better than other algorithms to predict well the students’ learning score. The “shared features” found by EA-GA from massive features are helpful to discriminate at-risk students and excellent students for different teaching intervention purpose.
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Acknowledgments
This work was partly supported by the National Natural Science Foundation of China (No. 61772023), the Natural Science Foundation of Fujian Province of China (No. 2016J01735, 2016J01320), and the Education and Teaching Reform Research Program of Fujian Bureau of Education, China (No. FBJG20170119).
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Authors and Affiliations
School of Computer Engineering, Jimei University, Xiamen, 361021, China
Jia-Lian Li, Shu-Tong Xie, Jun-Neng Wang & Yu-Qing Lin
College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
Qiong Chen
- Jia-Lian Li
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- Shu-Tong Xie
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- Jun-Neng Wang
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- Yu-Qing Lin
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- Qiong Chen
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Correspondence toShu-Tong Xie.
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Peking University, Beijing, China
Ying Tan
Southern University of Science and Technology, Shenzhen, China
Yuhui Shi
Tongji University, Shanghai, China
Qirong Tang
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Li, JL., Xie, ST., Wang, JN., Lin, YQ., Chen, Q. (2018). Prediction and Learning Analysis Using Ensemble Classifier Based on GA in SPOC Experiments. In: Tan, Y., Shi, Y., Tang, Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science(), vol 10943. Springer, Cham. https://doi.org/10.1007/978-3-319-93803-5_32
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