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Understanding the determinants of academic achievement (AA) is crucial for virtually every stakeholder interested in personal development and individual and societal wellbeing. Extensive research in several areas, such as education, economics, or psychology, has addressed this topic, identifying a vast number of determinants that impact high school students' AA. In this work, we perform a meta-analysis, including a weight analysis of 49 quantitative studies that investigate this topic, exploring the best predictors of high school students' academic success. We also explore moderation effects. Our results show that academic self-efficacy and socioeconomic status are the best predictors of AA, and they are statistically significant. Other statistically significant predictors, albeit less common in the analyses, are mastery avoidance, motivation, sleep habits, and work avoidance. Implications for theory and practice and directions for future research are discussed. [ABSTRACT FROM AUTHOR]

Understanding the determinants of academic achievement (AA) is crucial for virtually every stakeholder interested in personal development and individual and societal wellbeing. Extensive research in several areas, such as education, economics, or psychology, has addressed this topic, identifying a vast number of determinants that impact high school students’ AA. In this work, we perform a meta-analysis, including a weight analysis of 49 quantitative studies that investigate this topic, exploring the best predictors of high school students’ academic success. We also explore moderation effects. Our results show that academic self-efficacy and socioeconomic status are the best predictors of AA, and they are statistically significant. Other statistically significant predictors, albeit less common in the analyses, are mastery avoidance, motivation, sleep habits, and work avoidance. Implications for theory and practice and directions for future research are discussed.

Along with escalating environmental problems, the role of technologies in mitigating those problems has also increased. Researchers have been studying the adoption of sustainable technologies, and the number of articles on the topic has grown in recent years. The current study presents a weight and meta-analysis that synthesizes and combines previous literature on sustainable technologies adoption, evaluating the state of the art and providing a comprehensive picture of the phenomena. Using 44 articles and 48 datasets, the results demonstrate that attitude, benefits, personal norms, incentives, and perceived behavioral control are the best predictors of the behavioral intention of sustainable technologies adoption. Moreover, journal ranking, innovation, individualism, and long-term orientation, as cultural moderators, as well as electricity access and renewable energy, as energy efficiency indicators, were found to moderate subjective norms and behavioral intention. The findings of this study are relevant for future research support. • A weight and meta-analysis on sustainable technologies (ST). • Clearer and harmonized view of ST adoption research. • Identification of the best and promising indicators of ST behavior intention. • Attitude, benefits, personal norms, and incentives as best predictors. • Moderation of innovation, cultural and energy efficiency indicators. [ABSTRACT FROM AUTHOR]