STEM education reform plays a critical role in modern education for the country to keep abreast of being competitive in global economy. For a long time, STEM disciplines have been in silos, rendering the students unable to connect learned knowledge with real life problems. The emergence of integrated STEM education in some institutions suggests that, this approach makes students better problem solvers and logical thinkers. This paper provided an overview of what teaching strategies dominate in the implementation of integrated STEM education. The research methodology was based on a review of relevant literature search strategy through ERIC, online databases and journals such as Science Direct, Wiley Online Library, Taylor & Francis Online, SpringerLink, IEEE Xplore Digital Library, JSTOR and Journal of STEM Education. The keywords used in the search included integration strategies, science and technology, teaching and learning STEM, STEM in primary school, STEM in secondary school and STEM in higher education. The results of this meta-analysis revealed that, a project-based learning approach is the dominant strategy in STEM education implementation as this method improves the students' skills and their capability to compete with others in the highly knowledge-based society. Findings from this review will lead educators who are new to STEM education to investigate further on how project-based learning could be effectively implemented in their teaching.

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Based on a synthesis of literature, earlier studies, analyses and observations on high school students, this study developed an initial framework for assessing students’ statistical reasoning about descriptive statistics. Framework descriptors were established across five levels of statistical reasoning and four key constructs. The former consisted of idiosyncratic reasoning, verbal reasoning, transitional reasoning, procedural reasoning, and integrated process reasoning. The latter include describing data, organizing and reducing data, representing data, and analyzing and interpreting data. In contrast to earlier studies, this initial framework formulated a complete and coherent statistical reasoning framework. A statistical reasoning assessment tool was then constructed from this initial framework. The tool was administered to 10 tenth-grade students in a task-based interview. The initial framework was refined, and the statistical reasoning assessment tool was revised. The ten students then participated in the second task-based interview, and the data obtained were used to validate the framework. The findings showed that the students’ statistical reasoning levels were consistent across the four constructs, and this result confirmed the framework’s cohesion. Developed to contribute to statistics education, this newly developed statistical reasoning framework provides a guide for planning learning goals and designing instruction and assessments.

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In multivariable calculus, the concept of multivariable function is one of the most difficult for undergraduate students to study. The main objective of this study is to establish a model of teaching and learning to support students' mathematical thinking in the learning of two-variable functions through a blended learning environment. The impact of this environment on students' learning of two-variable functions and in overcoming students' obstacles are put forward. Findings revealed that blended learning supports students' mathematical thinking and helps in overcoming additional obstacles in mathematical learning. Poor mathematical knowledge of single-variable functions and poor algebraic manipulations are still the main reasons behind student obstacles in learning two-variable functions.

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