| dc.contributor | 教政所 | |
| dc.creator (作者) | 吳政達 | |
| dc.creator (作者) | Wu, Cheng-Ta;Lo, Tsai-Hsin;Huang, Jian-Hao;Chen, Min-Ching | |
| dc.date (日期) | 2026-08 | |
| dc.date.accessioned | 1-Sep-2026 14:15:58 (UTC+8) | - |
| dc.date.available | 1-Sep-2026 14:15:58 (UTC+8) | - |
| dc.date.issued (上傳時間) | 1-Sep-2026 14:15:58 (UTC+8) | - |
| dc.identifier.uri (URI) | https://ah.lib.nccu.edu.tw/item?item_id=184673 | - |
| dc.description.abstract (摘要) | The COVID-19 pandemic has intensified the need for education systems to strengthen knowledge management (KM) processes to recover learning losses and build long-term resilience. Conceptualizing national education systems as knowledge management architectures, this study examines how effectively systems mobilize knowledge-related resources to generate mathematics outcomes. Using TIMSS 2019 and 2023 eighth-grade data from 43 and 35 countries respectively, we apply Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MPI) to assess both static efficiency and dynamic productivity change. Four inputs are operationalized as components of a system-level KM architecture: teacher qualification (knowledge stock), instructional clarity (knowledge transfer process), school emphasis on academic success (knowledge-supportive culture), and safe and orderly climate (enabling context). Outputs include mathematics achievement as well as students’ confidence and enjoyment in mathematics, capturing both cognitive and affective knowledge outcomes. Input-oriented CCR and BCC models identify efficiency frontiers and distinguish managerial inefficiency from scale inefficiency. MPI further decomposes productivity change between 2019 and 2023 into efficiency change (catch-up) and frontier shift (relative productivity movement). Results reveal substantial cross-national heterogeneity in knowledge mobilization efficiency and scale conditions. While some systems improved primarily through frontier shifts relative to peer systems, others experienced stagnation or decline. By integrating international large-scale assessment data with a KM perspective, this study extends educational efficiency research beyond performance comparisons and provides diagnostic insights for scale-sensitive and process-oriented policy design in post-COVID mathematics education. | |
| dc.format.extent | 108 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Communications in Computer and Information Science(CCIS,volume 3105), De La Salle University, DLSU, pp.347-358 | |
| dc.subject (關鍵詞) | Knowledge Management; Educational Efficiency; Data Envelopment Analysis; Malmquist Productivity Index; Mathematics Education; International Large-scale Assessment | |
| dc.title (題名) | Knowledge Resources and Educational Productivity in the Post-COVID Era: A DEA–Malmquist Analysis of TIMSS 2019–2023 | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1007/978-3-032-34189-1_28 | |
| dc.doi.uri (DOI) | https://doi.org/10.1007/978-3-032-34189-1_28 | |
