| dc.contributor | 教育學院 | |
| dc.creator (作者) | 莊俊儒 | |
| dc.creator (作者) | Ching, Gregory S.;Chao, Pei-Ching | |
| dc.date (日期) | 2025-10 | |
| dc.date.accessioned | 17-Dec-2025 11:58:54 (UTC+8) | - |
| dc.date.available | 17-Dec-2025 11:58:54 (UTC+8) | - |
| dc.date.issued (上傳時間) | 17-Dec-2025 11:58:54 (UTC+8) | - |
| dc.identifier.uri (URI) | https://ah.lib.nccu.edu.tw/item?item_id=180262 | - |
| dc.description.abstract (摘要) | The COVID-19 pandemic disrupted education worldwide, with mathematics learning particularly affected due to its reliance on cumulative knowledge and structured instruction. This study investigates the influence of socioeconomic background and pandemic-related disruptions on mathematics achievement across countries using data from the Program for International Student Assessment (PISA) 2022 COVID-19 module. The dataset included 109,097 secondary students from 17 participating countries, with mathematics performance measured as the average of ten plausible values. Predictor variables included socioeconomic status, emotional impact, perceived learning loss, family support, and access to digital resources. Multiple linear regression analysis was applied to identify independent contributions of each predictor, while Classification and Regression Tree (CART) modeling captured non-linear interactions and threshold effects. Results showed that socioeconomic status was the strongest positive factor, followed by digital access as a modest contributor, whereas perceived learning loss and emotional impact emerged as strong negative influences. Family support showed limited predictive power when modeled together with other variables. CART analysis further demonstrated that students with high socioeconomic status and low learning loss were most likely to achieve higher mathematics scores, while students with low socioeconomic status were consistently classified as low achievers regardless of other conditions. These findings highlight how COVID-19 amplified pre-existing inequalities in mathematics education, revealing that disadvantage and disruption interact to magnify vulnerability. The study underscores the need for equity-focused recovery policies that address both structural socioeconomic gaps and targeted interventions for learning recovery in mathematics. | |
| dc.format.extent | 97 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | International Journal of Basic and Applied Sciences, Vol.14, No.6, pp.115-122 | |
| dc.subject (關鍵詞) | COVID-19 Educational Disruption; Mathematics Achievement; Socioeconomic Status; Learning Loss; Digital Access; Regression Analysis; Decision Tree Modeling; Educational Equity | |
| dc.title (題名) | Uncovering the impact of COVID-19 disruptions on students mathematics achievement: A CART analysis of selected PISA 2022 data | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.14419/y9ynz887 | |
| dc.doi.uri (DOI) | https://doi.org/10.14419/y9ynz887 | |
