Kyong Mi Choi , Yujin Lee , Younhee Lee , Jihyun Hwang

DOI:10.7468/jksmed.2025.28.1.1 Vol.28(No.1) 1-4, 2025

Starting in 2025, the journal will continue under a new title: Mathematics Education Research and Practice (MERP), formerly Korean Society of Mathematics Education - Series D: Research in Mathematics Education. This change reflects the journal’s expanding scope, integrating both theoretical and practical aspects of mathematics education in alignment with growing interdisciplinary and applied academic trends. In this editorial, we discuss revised scope of MERP and invite contributions from a diverse range of researchers and practitioners in four article types.

Amanda Meiners

DOI:10.7468/jksmed.2025.28.1.5 Vol.28(No.1) 5-21, 2025

A course instructor was guided to focus on a practical, evidenced based mode to rehumanize their secondary mathematics methods course in the United States of America by their own past K-12 teaching experiences and intentions to incorporate issues of diversity, equity, inclusion, and social justice using the Street Data framework, specifically the deep learning section using small talks. Small talks are approximately 5-minute, once per 50 minutes of class time, student lead discussions that introduce their classmates to the life stories of identities that have been oppressed within STEM, particularly mathematics. To reduce bias, the instructor explains their positionality and how a community was created that allowed students to be the experts and gain provide the insights to others into their course and learning through deep learning. As such, the following research questions developed: 1) After engaging in the humanizing mathematics activity, what shifts did PTs experience? and 2) How do PTs anticipate humanizing (incorporating a community with equity and justice) within their future mathematics courses? To evoke deep learning, small talks were positioned on three specific foci that aligned with deep learning from Safir and Dugan (2021): redefining success, building coherence, and making learning public. Results indicate PTs intend to pass the opportunity of small talks on, giving voice to their future students, families, fellow teachers, their school, and their community leaders one day.

mathematics education, secondary methods, equity, justice

Ken W. Li , Merrilyn Goos

DOI:10.7468/jksmed.2025.28.1.23 Vol.28(No.1) 23-63, 2025

This experimental study attempts to investigate how and to what extent peer collaboration affects students to evaluate regression model fitting and diagnose the problems associated with an unfitted model. Forty-nine students who voluntarily participated in the study were randomly assigned to one of these three groups: A, B, or C and there were four stages in the study. Students in groups A and B were allowed to have peer discussions about the workflow of a regression modelling in Stages I and III respectively, whereas students in Group C worked on their own in both stages. In Stage II or IV, all students in these three groups attempted three questions individually. It was found that students with pre-task discussion (A) demonstrated higher ability of accomplishing straightforward tasks, e.g., differentiating the functional roles of two variables, x and y; reading statistical graphs; defending successful data transformation, etc. than students with post-task or no discussion. Students with post-discussion (B) were more proficient in modelling and graphing regression data and validating the assumption of data normality than those with pre-task discussion or no discussion at all. On the other hand, students who had no discussion (C) performed better in checking the assumptions of homoscedasticity, independence, and linearity of data; hypothesizing data transformation; making a prediction with a transformed regression model and so on than those students with pre-task or post-task discussion. Hence, the effect of peer collaboration on students’ regression diagnostics performance is dependent on the types of regression tasks.

pre-task discussion, post-task discussion, social interaction, regression diagnostics, vocational education

Jing Zhang , Siyu Sun , Qiping Kong

DOI:10.7468/jksmed.2025.28.1.65 Vol.28(No.1) 65-89, 2025

Historical research suggests a positive correlation between students' performance and their math learning experience, particularly through the psychological state of Flow. Flow, characterized by cognitive efficiency, motivation, and positive affect, plays a crucial role in enhancing students' engagement and learning outcomes in math. However, the measurement of students’ Flow experience in math learning haven’t adequately been studied. The aim of this study was to develop and validate the tool Math Flow State Scale (MFSS) to measure students’ flow in math learning based on Flow theory. We used two samples (sample1, n=373; sample2, n=477) to assess the scale's reliability, factor structure, and validity. Data from sample1 was used to conduct exploratory factor analysis (EFA). Based on the results of EFA, a 26-item MFSS with good construct validity was developed. Data from sample 2 was used to conduct the confirmatory factor analysis (CFA) to assess the validity of alternative models and suggested the most fit one. Results have shown that the eight-factor with 24 items MFSS has both good reliability and construct validity. This could support further research exploring the relationship between students' math flow experience, math performance, and other related factors, using similar methodologies to gain deeper insights into how these elements interact and impact overall learning outcomes.

flow theory, measurement, validation, math flow state scale

Kyong Mi Choi , Jess Jensen

DOI:10.7468/jksmed.2025.28.1.91 Vol.28(No.1) 91-94, 2025