Hong Nam Dao

Interpreting how multiple variables interact is often challenging for students, especially when statistical learning goes beyond calculation to explanation. In many cases, students can apply procedures correctly but still struggle to make sense of relationships among variables. Although simulation tools have been introduced to support learning, less is known about how they contribute to students’ understanding of multivariate relationships when combined with clear instructional design. This study explored the use of a simulation based learning approach with first year pharmacy students. A quasi experimental pre test–post test design was conducted with 85 students, together with an attitudinal survey involving 229 participants. Students in the experimental group worked with a simulation environment that allowed them to explore how variables interact under different conditions, while the control group followed conventional instruction. Students who engaged with the simulation achieved higher post test scores than those receiving conventional instruction (t(83) = 2.096, p = 0.039, d = 0.46). When pre test differences were taken into account, the instructional effect remained significant (F(1,82) = 22.55, p < 0.001, η² = 0.216). Students in the experimental group also reported greater engagement and confidence in interpreting statistical relationships. Students who worked with the simulation were better able to interpret how multiple variables interacted than those in the control group. From a practical standpoint, the study suggests that using simulation based environments in statistics instruction can support learning activities that foreground interpretation and conditional reasoning rather than routine procedural work, particularly in applied contexts such as pharmacy education.

Escalating global sustainability crises have intensified the need for teacher education programs to prepare mathematics teachers capable of fostering sustainability key competencies through meaningful classroom practices. Although Education for Sustainable Development (ESD) has gained prominence, limited empirical research has examined how pre-service mathematics teachers operationalize sustainability competencies within mathematics activity design, particularly following short, targeted instructional interventions. Addressing this gap, the present study explores how pre-service mathematics teachers design mathematics classroom activities aligned with the Sustainable Development Goals (SDGs) and examines the extent to which a brief training sequence influences the manifestation of sustainability key competencies in their designs. The study involved 54 pre-service mathematics teachers at a Vietnamese university, working in 27 pairs. Each pair designed a lower-secondary mathematics activity linked to a single SDG before and after a three-week design cycle that included a focused workshop on ESD and project-based learning principles as design heuristics. An analytic rubric adapted from prior research was employed to assess five sustainability key competencies—systems thinking, anticipatory thinking, critical thinking, self-awareness, and integrated problem-solving—operationalized through six competence units on a four-level ordered scale (NE, Basic, Integrated, Advanced). Two researchers independently coded all designs, resolved discrepancies through discussion, and analyzed the data using descriptive statistics and non-parametric tests. The results indicate that participants addressed ten SDGs, with predominant emphasis on health and responsible consumption themes, data handling and algebra content, and Grade 8 contexts. Post-training designs demonstrated higher competency levels across all units, with the most substantial gains observed in systems thinking, anticipatory thinking, critical thinking, and self-awareness. These findings suggest that even brief, structured training can meaningfully enhance pre-service teachers’ capacity to design mathematics activities that foreground sustainability competencies, offering both empirical evidence and a practical assessment tool for mathematics teacher education.

The perspective on applying mathematics to solve practical problems is clearly expressed in Vietnam's Mathematics General Education Curriculum in 2018. Therefore, Realistic Mathematics Education (RME) is suitable for the goals of mathematics education in Vietnam and can become one of the fundamental theories for designing mathematics teaching models in high schools. This study presents an experimental result of teaching conditional probability based on RME and following a five-step process we develop, including problem setting, experience, rediscovering conditional probability, forming conditional probability, application. Worksheets containing problems were distributed to 42 students to solve, and their work was collected immediately afterwards. The works will be analyzed to identify emergent models constructed by students. The new result of the paper is from the study of De Lange, Jupri and Drijvers, we propose a mathematization process for teaching conditional probability in Vietnam. The data analysis method is a qualitative method, through observing the students' problem-solving process. Experimental results show that students actively participated in the process of reinventing conditional probability through solving learning tasks.