Predicting science achievement scores with machine learning algorithms: a case study of OECD PISA 2015

Predicting science achievement scores with machine learning algorithms: a case study of OECD PISA 2015–2018 data

Published:2023-08-03 Issue:28 Volume:35 Page:21201-21228
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Acıslı-Celik Sibel^ORCID,Yesilkanat Cafer Mert^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-023-08901-6.pdf

Reference95 articles.

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2. PISA (2021) Programme for ınternational student assessment. https://www.oecd.org/pisa/. Accessed 25 Nov 2021

3. Aksu G (2018) PISA başarısını tahmin etmede kullanılan veri madenciliği yöntemlerinin incelenmesi (in Turkish). Dissertation, Hacettepe University, Ankara, Türkiye.

4. Hu J, Yu R (2021) The effects of ICT-based social media on adolescents’ digital reading performance: a longitudinal study of PISA 2009, PISA 2012, PISA 2015 and PISA 2018. Comput Educ 175:104342. https://doi.org/10.1016/J.COMPEDU.2021.104342

5. Rolfe V (2021) Tailoring a measurement model of socioeconomic status: applying the alignment optimization method to 15 years of PISA. Int J Educ Res 106:101723. https://doi.org/10.1016/J.IJER.2020.101723

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