Asia Pacific Education Review最新文献

The randomized control trial (RCT) is the primary experimental design in education research due to its strong internal validity for causal inference. However, in situations where RCTs are not feasible or ethical, quasi-experiments are alternatives to establish causal inference. This paper serves as an introduction to several quasi-experimental designs: regression discontinuity design, difference-in-differences analysis, interrupted time series design, instrumental variable analysis, and propensity score analysis with examples in education research.

Attention to the disconnection between culture and mathematics has been addressed then and now (Wilder (in: Graves et al., Proceedings of the international congress of mathematicians, American Mathematical Society, 1950; Liu in Taiwan Journal of Mathematics Education, 8:79–88, 2021b). Recently, studies, workshops, and contests about an approach to relating culture and mathematics, such as incorporating mathematics history or mathematics writings in class, have emerged. However, although the effectiveness of such an approach was proved, employing it as instruction was still significantly ignored, not to mention the approach to creating mathematics literary writings—the goal that the Mathematics-Literature Contest aimed to achieve. Additionally, no empirical studies have systematically assessed the contest, especially from the cultural perspective. Through teachers’ and students’ perceptions, this qualitative case study aims to examine the impact of mathematics literary writings on the development of mathematics teaching/learning and the mathematics culture represented in the contest. Ten teachers and 20 students were interviewed. Data were analyzed by following Yin’s five phases (2016). The study visualizes an evolutionary model of the contest, signifying the development of mathematics culture simultaneously. Results demonstrated that the contest caused teachers and students, who constituted the internal force, to consolidate the mathematics culture, which was enriched by the external force—to reinterpret the connection between mathematics as well as culture and the reform of general education. The developed mathematics culture included elements other than mathematics, such as the Chinese writings and their interactions with mathematics and life experiences. The findings hold implications for mathematics and general education: An interdisciplinary curriculum design can help cultivate teachers’ and students’ intellectual acumen; higher education communities worldwide must follow the trend.

This study aimed to evaluate the effects of intervention using graphic organizers on the cognitive and affective improvement of students with intellectual disability (ID), with learning disability (LD), without disability, and at-risk learners in Korea. A total of 49 peer-reviewed journals and dissertations for the last 20 years were included for conducting this meta-analysis. The overall effect size of intervention using a graphic organizer was .78 (d) (95% CI [.63, .94], ({tau }^{2}) = .28) using a random-effects model. In order of strongest to weakest effects, at-risk learners (d = 1.38), students with LD (d = 1.15), students with ID (d = .76), and students without disability (d = .52). Among student variables, there is no statistically significant difference by school level, but by school type. Among intervention variables, instruction in math (d = 1.43) and Korean (d = .96); cognitive mapping (d = 1.05); 1–19 times, 1–9 weeks, 3–5 times per week; and small-size groups were the most effective intervention conditions. While several variables showed significant subgroup differences, meta-regression analyses revealed that only group size and frequency were significant moderators after controlling for other factors. In summary, intervention using a graphic organizer was more effective for students with disability and at-risk students than it was for students without disability.

In our previous study (Gomersall & Floyd, in Asia Pacific Education Review 24:447–459, 2022), we reported that a group of Myanmar students, who studied online for their high school qualifications during COVID-19, reported drawing on a range of factors to enable them to overcome the adversity and continue their education. Moreover, they claimed that they had benefited from the online experience and were ready to progress to university. This study returns one year later to interview some of the original participants to see if their perceptions became reality. In addition, a group of students from the 2020 cohort are also interviewed so that a comparison can be made between the last group of students who studied ‘normally’ before COVID-19, and those who experienced online learning for the first time. This study addresses a gap in the literature by examining student perspectives of the ways in which they thrived as a result of digitally enhanced learning. We conclude that learning online enabled students to develop personally, enhance their digital skills, and acquire skills and knowledge that could be utilised again in the future. Moreover, those who studied online in both high school and university found the process of commencing online studies at university easier, which supports the tentative conclusion that even in low resource settings, it would be beneficial for schools to explore integrating more digital skills into the classroom.

Causal inference involves determining whether a treatment (e.g., an education program) causes a change in outcomes (e.g., academic achievement). It is well-known that causal effects are more challenging to estimate than associations. Over the past 50 years, the potential outcomes framework has become one of the most widely used approaches for defining, identifying, and estimating causal effects. In this paper, we review the potential outcomes framework with a focus on potential outcomes notation to define individual and average causal effects. We then show how three canonical assumptions, Unconfoundedness, Positivity, and Consistency, may be used to identify average causal effects. The identification results motivate methods for estimating causal effects in practice, which include model-based estimators, such as regression, inverse probability weighting, and doubly robust estimation, and procedures that target covariate balance, such as matching and stratification. Examples and discussion are grounded in the context of a running example of a study aimed at assessing the causal effect of receipt of special education services on 5th grade mathematics achievement in school-aged children. Practical considerations for education research are discussed.

Causal mediation analysis has gained increasing attention in recent years. This article guides empirical researchers through the concepts and challenges of causal mediation analysis. I first clarify the difference between traditional and causal mediation analysis and highlight the importance of adjusting for the treatment-by-mediator interaction and confounders of the treatment–mediator, treatment–outcome, and mediator–outcome relationships. I then introduce the definition of causal mediation effects under the potential outcomes framework and different methods for the identification and estimation of the effects. After that, I highlight the importance of conducting a sensitivity analysis to assess the sensitivity of analysis results to potential unmeasured confounding. I also list various statistical software that can conduct causal mediation analysis and sensitivity analysis and provide suggestions for writing a causal mediation analysis paper. Finally, I briefly introduce some extensions that I made with my colleagues, including power analysis, multisite causal mediation analysis, causal moderated mediation analysis, and relaxing the assumption of no post-treatment confounding.

The purpose of this study was to investigate the school-related factors that influence students’ global citizenship. To explore both student-level and school-level factors that influence students’ global citizenship, we applied a hierarchical linear model using PISA 2018 data from Korea. The results showed that factors related to teacher’s GCED practices and school climate can play an important role in fostering students’ global citizenship. Based on these findings, we suggest that a whole-school approach is needed to promote the inclusion of GCED-related topics in various school curricula and to integrate GCED values into the overall school culture to enhance students’ global citizenship.

Regression discontinuity (RD) designs have gained significant popularity as a quasi-experimental device for evaluating education programs and policies. In this paper, we present a comprehensive review of RD designs, focusing on the continuity-based framework, the most widely adopted RD framework. We first review the fundamental aspects of RD designs, drawing on potential outcomes and causal graphs. We then discuss the validity threats in RD designs, including manipulation, discreteness of the running variable, statistical power, and generalizability. Additionally, we provide an overview of the existing extensions to RD designs. To exemplify the application of RD methods, we analyze the effect of New Jersey’s pre-kindergarten program on children’s vocabulary test scores, using an educational dataset. Finally, we offer practical guidelines in the conclusion to promote the appropriate use of RD methods in educational research.