Uneingeschränkter Zugang

Machine Learning Based Big Data Analytics for Education in Curriculum Reforms

 und   
27. Feb. 2025

Zitieren
COVER HERUNTERLADEN

Zhang, Z. (2023). Big data-driven digital transformation of education: Key applications and practical paths. China Education Informatization, 29(10), 17-27. Zhang Z. ( 2023 ). Big data-driven digital transformation of education: Key applications and practical paths . China Education Informatization , 29 ( 10 ), 17 27 . Search in Google Scholar

Tang, X., & Hu, Q. (2021). Research on big data analysis in education. Journal of Hunan First Normal College, 21(4), 90-94. Tang X. Hu Q. ( 2021 ). Research on big data analysis in education . Journal of Hunan First Normal College , 21 ( 4 ), 90 94 . Search in Google Scholar

Li, X. (2016). Big data analytics in higher education: Opportunities and challenges. Open Education Research, 22(4), 7. https://doi.org/10.13966/j.cnki.kfjyyj.2016.04.007 Li X. ( 2016 ). Big data analytics in higher education: Opportunities and challenges . Open Education Research , 22 ( 4 ), 7 . https://doi.org/10.13966/j.cnki.kfjyyj.2016.04.007 Search in Google Scholar

Yilmaz, E. A., Balcisoy, S., & Bozkaya, B. (2023). A link prediction-based recommendation system using transactional data. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-34055-5 Yilmaz E. A. Balcisoy S. Bozkaya B. ( 2023 ). A link prediction-based recommendation system using transactional data . Scientific Reports , 13 ( 1 ). https://doi.org/10.1038/s41598-023-34055-5 Search in Google Scholar

Ciscar, A., Saiz, J. C., & Navarro, J. A. (2018). Machine learning and pattern recognition. Ciscar A. Saiz J. C. Navarro J. A. ( 2018 ). Machine learning and pattern recognition . Search in Google Scholar

Cai, J., Luo, J., Wang, S., et al. (2018). Feature selection in machine learning: A new perspective. Neurocomputing, 300(26), 70-79. Cai J. Luo J. Wang S. ( 2018 ). Feature selection in machine learning: A new perspective . Neurocomputing , 300 ( 26 ), 70 79 . Search in Google Scholar

Dipti, T., & Bhoyar, K. K. (2024). Feature selection techniques for machine learning: A survey of more than two decades of research. Knowledge and Information Systems, 66(3), 1575-1637. Dipti T. Bhoyar K. K. ( 2024 ). Feature selection techniques for machine learning: A survey of more than two decades of research . Knowledge and Information Systems , 66 ( 3 ), 1575 1637 . Search in Google Scholar

Xu, P., Wang, Y., Liu, Y., & Zhang, H. (2013). Analysing learning changes from a big data perspective—Interpretation and implications of the report “Promoting Teaching and Learning through Educational Data Mining and Learning Analytics” in the United States. Journal of Distance Education, (10), 11-17. Xu P. Wang Y. Liu Y. Zhang H. ( 2013 ). Analysing learning changes from a big data perspective—Interpretation and implications of the report “Promoting Teaching and Learning through Educational Data Mining and Learning Analytics” in the United States . Journal of Distance Education , ( 10 ), 11 17 . Search in Google Scholar

Wu, Q., & Luo, R. (2017). Prediction of learning achievement and teaching reflection based on online learning behaviour. Modern Education Technology, 27(6), 18-24. Wu Q. Luo R. ( 2017 ). Prediction of learning achievement and teaching reflection based on online learning behaviour . Modern Education Technology , 27 ( 6 ), 18 24 . Search in Google Scholar

Rawashdeh, A. Z., Mohammed, E. Y., & Arab, A. R., et al. (2021). Advantages and disadvantages of using e-learning in university education: Analyzing students' perspectives. Electronic Journal of e-Learning, 19(3), 107-117. Rawashdeh A. Z. Mohammed E. Y. Arab A. R. ( 2021 ). Advantages and disadvantages of using e-learning in university education: Analyzing students’ perspectives . Electronic Journal of e-Learning , 19 ( 3 ), 107 117 . Search in Google Scholar

Cheng. (2018). Greek membership and academic performance: Evidence from student-level data. Applied Economics, 50(28), 3185-3195. Cheng (2018 ). Greek membership and academic performance: Evidence from student-level data . Applied Economics , 50 ( 28 ), 3185 3195 . Search in Google Scholar

Zaremba, W., Sutskever, I., & Vinyals, O. (2014). Recurrent neural network regularization. Eprint Arxiv. Zaremba W. Sutskever I. Vinyals O. ( 2014 ). Recurrent neural network regularization . Eprint Arxiv . Search in Google Scholar

Abdulkareem, N. M., & Abdulazeez, A. M. (2021). Machine learning classification based on random forest algorithm: A review. International Journal of Science and Business, 5. Abdulkareem N. M. Abdulazeez A. M. ( 2021 ). Machine learning classification based on random forest algorithm: A review . International Journal of Science and Business , 5 . Search in Google Scholar

Bu, X., Wang, S., & Zhang, Y. (2017). A review of the theory and application of K nearest neighbour algorithm. Computer Engineering and Application, 53(21), 7. Bu X. Wang S. Zhang Y. ( 2017 ). A review of the theory and application of K nearest neighbour algorithm . Computer Engineering and Application , 53 ( 21 ), 7 . Search in Google Scholar

Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
1 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Biologie, Biologie, andere, Mathematik, Angewandte Mathematik, Mathematik, Allgemeines, Physik, Physik, andere