Rost Detlef H, Feng Xiaoli
Center for Mental Health Education, School of Psychology, Southwest University Chongqing, 2 Tiansheng Road, Beibei, Chongqing 400715, China.
Faculty of Psychology, Philipps-University Marburg, 35032 Marburg, Germany.
Behav Sci (Basel). 2024 Jan 5;14(1):40. doi: 10.3390/bs14010040.
The importance of self-related constructs in predicting academic achievement has been increasingly emphasized in recent decades. Typically, bivariate associations of self-related variables with achievements have been reported. Research quantifying the combined predictive power of more than two self-variables has been scarce. Moreover, except for the academic self-concept, these variables have almost always been measured across domains, i.e., without considering the specifics of individual school subjects. The current study aimed to statistically predict academic achievement (operationalized via school grades) in three major subjects (Chinese (native language), mathematics, and English (foreign language)) by using subject-tied scales, namely academic self-concept, conscientiousness, need for cognition, perseverance of effort, and consistency of interest. The sample comprised 791 Chinese adolescents. Each scale was related separately to each of the three school subjects. Hierarchical linear regression analyses were run. The control variable, biological sex, accounted for 2% of Chinese grades and 8% of English grades, but not of mathematics grades. Adding subject-specific self-concept scales increased the explained variance to 7% (Chinese), 16% (mathematics), and 32% (English). Further additions to the other four self-related scales did not increase the variances that were accounted for. The discussion underlines the relevance of subject-specific academic self-concepts as predictors for subject-tied academic achievements.
近几十年来，自我相关构念在预测学业成绩方面的重要性日益受到强调。通常，已有关于自我相关变量与成绩之间的双变量关联的报道。但量化两个以上自我变量的综合预测能力的研究却很少。此外，除了学业自我概念外，这些变量几乎总是跨领域测量的，即没有考虑个别学科的具体情况。本研究旨在通过使用与学科相关的量表，即学业自我概念、尽责性、认知需求、努力坚持性和兴趣一致性，对三门主要学科（语文（母语）、数学和英语（外语））的学业成绩（通过学校成绩来衡量）进行统计预测。样本包括791名中国青少年。每个量表分别与三门学科中的每一门相关。进行了分层线性回归分析。控制变量生物性别，解释了语文成绩的2%和英语成绩的8%，但对数学成绩没有解释作用。加入特定学科的自我概念量表后，解释方差增加到7%（语文）、16%（数学）和32%（英语）。进一步加入其他四个与自我相关的量表并没有增加所解释的方差。讨论强调了特定学科的学业自我概念作为与学科相关的学业成绩预测指标的相关性。
