Ye Wangqiong, Teig Nani, Blömeke Sigrid
Faculty of Educational Sciences, Centre for Educational Measurement, University of Oslo, Oslo, Norway.
Department of Teacher Education and School Research, Faculty of Educational Sciences, University of Oslo, Oslo, Norway.
Front Psychol. 2024 Aug 21;15:1405786. doi: 10.3389/fpsyg.2024.1405786. eCollection 2024.
Identifying protective factors that promote academic resilience is vital. Nevertheless, due to the variations in the operationalizations of academic resilience, timeframes, data sources, and employed research methods, it remains unclear whether the impact of protective factors identified across studies can be attributed to the factors themselves or to these variations. By addressing these uncertainties, this study aims to provide an overview of the protective factors that have been extensively investigated in academic resilience and their degree of influence. A literature search found 119 empirical studies on protective factors in education settings for children and adolescents. The review analyzed five protective factors groups (individual, family, school, peer, community), three operationalizations of academic resilience (simultaneous, progressive, instrumental), two timeframes (longitudinal, non-longitudinal), three data sources (self-collected, national/local assessments, international large-scale assessments), and commonly employed research methods. The studies analyzed in this review yielded mixed results regarding the impact of the examined protective factors, with measurement instruments and statistical power playing a significant role in explaining the variations. Individual and school-level characteristics emerged as the most well-studied protective factors; individual characteristics were often investigated through "instrumental" operationalization and structural equational models, whereas school-level characteristics were typically explored through "simultaneous" or "progressive" operationalizations and multilevel modeling. Approximately 31 and 16% of the studies utilized national assessments and international large-scale assessment data, respectively. Both data sources promoted the exploration of school-level factors, with the former facilitating the exploration of protective factors across time and the latter contributing to the investigation of teaching-related factors.
识别促进学业复原力的保护因素至关重要。然而，由于学业复原力的操作化、时间框架、数据来源和所采用的研究方法存在差异，目前尚不清楚各项研究中所确定的保护因素的影响是可归因于这些因素本身还是这些差异。通过解决这些不确定性问题，本研究旨在概述在学业复原力方面得到广泛研究的保护因素及其影响程度。一项文献检索发现了119项关于儿童和青少年教育环境中保护因素的实证研究。该综述分析了五个保护因素组（个人、家庭、学校、同伴、社区）、学业复原力的三种操作化方式（同时性、递进性、工具性）、两个时间框架（纵向、非纵向）、三个数据来源（自行收集、国家/地方评估、国际大规模评估）以及常用的研究方法。本综述中分析的研究在所考察的保护因素的影响方面得出了混合结果，测量工具和统计效力在解释这些差异方面发挥了重要作用。个人和学校层面的特征是研究最多的保护因素；个人特征通常通过“工具性”操作化和结构方程模型进行研究，而学校层面的特征通常通过“同时性”或“递进性”操作化以及多层建模进行探索。分别约有31%和16%的研究使用了国家评估和国际大规模评估数据。这两种数据来源都促进了对学校层面因素的探索，前者有助于跨时间探索保护因素，后者有助于对与教学相关的因素进行调查。
