Scaffolding is widely used in online learning; however, it is unclear whether scaffolding can effectively enhance students’ online learning performance. To evaluate its effectiveness, we conducted a meta-analysis that included 83 effects sizes from 32 articles published between 2011 and 2021. The findings demonstrated that scaffolding had a significant role in improving students’ online learning performance with an overall effect size of 0.53. In addition, we analyzed the effects of five moderator variables to gain insights into how scaffolding affects students’ online learning performance under different conditions. The discipline, learning outcome type, and scaffolding type were identified as significant moderators. It is expected that the research results will guide teachers to design online scaffolding strategies and improve students’ online learning performance.

How adolescents’ after-school behaviors, self-management, and parental involvement are associated with their academic success and personal development has drawn growing attention. This study systematically examined how these three factors predict academic achievement. Data were collected from 353 seventh-grade students through a self-designed daily behavior log sheet and self-management app, and multiple linear regression analysis was conducted to identify key predictors. The results indicated that academic achievement was positively related to sleep quality, homework duration, self-assessment, and parental involvement, while it was negatively associated with sleep duration, exercise duration, and the number of daily planned tasks. Despite these insights, the study has limitations, including reliance on self-reported data, which may introduce bias, and the use of a cross-sectional design, which precludes determining the temporal sequence of variables and inferring causal relationships. These findings provide valuable insights for educators, parents, and students; they also emphasize the importance of organizing students’ after-school activities effectively, enhancing their self-management competencies, and encouraging active parental involvement in fostering students’ academic success and overall development.

This study examined how the time management behavior of first-year college students predicted their academic performance. Data on 44 objective indicators of daily time management behaviors were collected from 110 first-year students via a WeChat Mini Program, through one month of consecutive daily tracking. To identify stable predictors, Least Absolute Shrinkage and Selection Operator (LASSO) regression with 5000 bootstrap resamples was conducted, and variables with high selection frequency were subsequently entered Elastic Net regression to examine explanatory relationships. Six key behavioral indicators were found to predict overall academic performance. Subject-specific models revealed varying associations: time management behaviors appeared more influential in subjects such as Physical Education and English, while their role was less evident in Mathematics. The number and nature of retained predictors also differed across disciplines.