Influence Analytics Model of the General Education Courses Toward the Academic Achievement of Rajabhat University Students Using Data Mining Techniques-Reference-Cited by-同舟云学术

Influence Analytics Model of the General Education Courses Toward the Academic Achievement of Rajabhat University Students Using Data Mining Techniques

Published:2024 Issue: Volume: Page:117-129
ISSN:2190-3018
Container-title:Smart Innovation, Systems and Technologies
language:en
Short-container-title:

Author:

Bussaman Sittichai^ORCID,Nasa-Ngium Patchara^ORCID,Sararat Thapanapong^ORCID,Nuankaew Wongpanya S.^ORCID,Nuankaew Pratya^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-8612-5_10

Reference20 articles.

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2. Alhabeeb, A., Rowley, J.: E-learning critical success factors: comparing perspectives from academic staff and students. Comput. Educ. 127, 1–12 (2018). https://doi.org/10.1016/j.compedu.2018.08.007

3. Cagliero, L., Canale, L., Farinetti, L., Baralis, E., Venuto, E.: Predicting student academic performance by means of associative classification. Appl. Sci. 11, 1420 (2021). https://doi.org/10.3390/app11041420

4. Nuankaew, P.: Dropout situation of business computer students, University of Phayao. Int. J. Emerg. Technol. Learn. 14, 115–131 (2019). https://doi.org/10.3991/ijet.v14i19.11177

5. Nuankaew, P., Nasa-Ngium, P., Nuankaew, W.S.: Improving predictive model to prevent students’ dropout in higher education using majority voting and data mining techniques. In: Surinta, O., Kam Fung Yuen, K. (Eds.) Multi-disciplinary Trends in Artificial Intelligence, pp. 61–72. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-20992-5_6