Students’ mastery goal orientation tends to decline over the course of compulsory school, especially after the transition to lower secondary school. According to stage-environment fit theory, secondary school is less accommodating to students' needs, interests, and abilities than primary school. In consequence, the perceived person-environment fit declines as well. It is assumed that a strong sense of classroom community in primary school can counteract a potential decline in both of these important individual aspects. Using data from the Swiss longitudinal research project WiSel (“Wirkungen der Selektion”; “Effects of Tracking”), we conducted a latent growth curve model (LGCM) to examine the correlation between the development of students' mastery goal orientation and the development of their person-environment fit during the transition from primary school to lower secondary school. Perceived classroom community was assumed to benefit from these developments. The results show that both mastery goal orientation and person-environment fit decrease during the transition to lower secondary school. A strong sense of classroom community in fifth grade leads to a smaller decline in both constructs. Implications for educational practice are discussed.

Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.