This research aims to find out: (1) the more effective learning model on students' divergent-thinking skills; (2) the better adversity quotient on students' divergent-thinking skills; (3) the better adversity quotient to improve students' divergent-thinking skills in each learning model; and (4) the better learning model to improve students' divergent-thinking skills in each adversity quotient. This research uses a quantitative approach with a quasi-experimental type. The fifth-grade students were selected as the research subjects. This research was carried out at the public elementary schools in Laweyan District, Surakarta, Indonesia. Test and questionnaire techniques were used to collect data. The data analysis was performed with the analysis prerequisite, hypothesis, and multiple-comparison tests. The results showed that the learning model and adversity quotient have an influence on divergent-thinking skills; for each adversity quotient, the thinking actively in a social context learning model is better than the creative problem solving and direct instruction learning model; the creative problem solving learning model is better than the direct instruction learning model; and adversity quotient of the climbers is better than that of the campers and the adversity quotient of the campers is better than that of the quitters in each learning model.

Science, technology, engineering and mathematics (STEM) education is regarded as one of the formulas to embracing many of our imminent challenges. STEM education benefits the learners by encouraging interest in STEM disciplines. This daunting task needs everyone’s concerted efforts in creating and innovating mathematics teachers’ classroom practices Therefore, a systematic review was conducted to identify best practices for STEM education following the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) by Moher et al. (2015). The reviewed articles were published from 2016 to 2020 and accessed using the Scopus and Web of Science (WoS) databases. Three themes for best practices were identified namely (a) core competencies encompassing 21st-century teaching skills; (b) instructional designs; and (c) requisite STEM execution. Results of PRISMA determined the dominant STEM practices were critical thinking, communication, collaboration, problem-solving, research-based pedagogy, problem-based learning and project-based learning, technological integration, accessibility, professional development and learning support, evidence of effectiveness, access to materials and practitioner support, and scalability. Mathematics teachers should determine the best STEM practices to employ even though there is a lack of studies on integrated STEM domains. When more students are interested in venturing and exploring into the field of STEM, the high demand for STEM related careers could be met by the younger generation.

Successfully solving reality-based tasks requires both mathematical and text comprehension skills. Previous research has shown that mathematical tasks requiring language proficiency have lower solution rates than those that do not, indicating increased difficulty through textual input. Therefore, it is plausible to assume that a lack of text comprehension skills leads to performance problems. Given that different sociodemographic characteristics and cognitive factors can influence task performance, this study aims to determine whether text comprehension mediates the relationship between these factors and competence in solving reality-based tasks. Additionally, it examines the impact of systematic linguistic variation in texts. Using an experimental design, 428 students completed three reality-based tasks (word count: M = 212.4, SD = 19.7) with different linguistic complexities as part of a paper-pencil test. First, students answered questions about the situation-related text comprehension of each text, followed by a mathematical question to measure their competence in solving reality-based tasks. The results indicate that: a) Tasks with texts of lower linguistic complexity have a significantly higher solution rate for both text comprehension (d = 0.189) and mathematical tasks (d = 0.119). b) Cognitive factors are significant predictors of mathematical solutions. c) Text comprehension mediates the relationship between the impact of students’ cultural resources and cognitive factors and their competence to solve reality-based tasks. These findings highlight the importance of linguistic complexity for mathematical outcomes and underscore the need to reinforce text comprehension practice in mathematical education owing to its mediating role.