What Makes Two of the World’s Best Reading Systems Tick: Hong Kong and Singapore Compared

When Singapore topped the Progress in International Reading Literacy Study (PIRLS) 2021 and Hong Kong took third place, few observers were surprised. Both systems have hovered near the summit of international reading assessments since 2006, and both are frequently cited as models of educational excellence. Yet a new study suggests that the paths these two Asian powerhouses take toward reading success are strikingly different, and that the differences matter for policymakers everywhere trying to lift literacy outcomes.

The study, published in the journal Large-scale Assessments in Education, was led by Guanyu Chen of the University of British Columbia together with colleagues at Iowa State University and the Hong Kong Examinations and Assessment Authority. Rather than treating the two systems as interchangeable examples of East Asian achievement, the researchers directly compared them within a single analytical framework, using Walberg’s theory of educational productivity to organize factors into four domains: student characteristics, student attitudes and behaviors, family background, and school context.

The technical backbone of the analysis was hierarchical linear modeling, or HLM, a statistical approach designed for data in which students are nested within schools. Because PIRLS samples intact classrooms rather than independent individuals, traditional regression would underestimate uncertainty and blur the distinction between student-level and school-level effects. The team used the EdSurvey R package, applying sampling and replicate weights and analyzing five plausible values per student to capture measurement uncertainty in the achievement scores. After listwise deletion of cases with missing data, the final models included 3,619 fourth-graders in Hong Kong and 5,734 in Singapore.

One of the most consistent findings concerned absenteeism. In both systems, students who reported missing school at least once every two months scored substantially lower in reading, with gaps of roughly 24 points in Hong Kong and nearly 30 points in Singapore in the fully adjusted models. This is notable because both jurisdictions tightly regulate attendance: Hong Kong legally obliges parents to ensure schooling during prescribed hours, while Singapore enforces mandatory attendance under its Compulsory Education Act. Despite these structures, around 11 percent of Hong Kong students and 18 percent of Singaporean students reported absences, and their underperformance suggests that digital learning infrastructure alone cannot compensate for lost in-person instruction.

Reading confidence emerged as the single strongest attitudinal predictor in both systems. Students with high confidence scored 47.52 points higher than low-confidence peers in Hong Kong and a remarkable 77.88 points higher in Singapore, effects that remained stable even after family and school factors were added. The researchers frame this through the lens of social-emotional learning, linking self-efficacy and self-management to academic engagement. Moderate amounts of reading outside school, between 30 minutes and two hours daily, also predicted higher scores, though the benefits appeared to plateau or diminish for students reading more than two hours a day, possibly because PIRLS is calibrated to the average global reader.

Not every behavioral factor behaved the same way in both places. Library use was consistently and positively associated with reading achievement in Singapore, where even occasional users outscored non-users by 11 to 16 points, but showed no significant relationship in Hong Kong. Classroom engagement mattered modestly in both systems, while self-reported enjoyment of reading was not significantly associated with achievement in either. These divergences hint that identical interventions may not transfer cleanly between superficially similar systems.

The starkest contrast appeared in the family and school domains. Home socioeconomic status was a strong predictor everywhere, but its estimated effect was more than twice as large in Singapore, where high-SES students outscored low-SES students by about 45 points, compared with roughly 21 points in Hong Kong. Intriguingly, only 5.52 percent of Singaporean students came from low-SES households versus 17.43 percent in Hong Kong, and the authors suggest that Hong Kong’s smaller SES coefficient may reflect greater equity in how educational resources are distributed, a pattern consistent with OECD findings on Hong Kong’s performance in PISA 2022.

Parental reading habits, parental satisfaction with the school, and a school’s emphasis on academic success all predicted higher reading scores in Singapore but were weak or nonsignificant in Hong Kong. The authors caution that these relationships may partly reflect broader differences in school resources and academic culture rather than independent causal effects. Still, the descriptive gaps are telling: 42.25 percent of Hong Kong students attended schools with a low emphasis on academic success, compared with just 15.72 percent in Singapore. The study points to Singapore’s School Excellence Model and initiatives like Read@School as examples of deliberately coordinated family-school alignment, while Hong Kong has pursued parent education through a 2017 task force, Parent-Teacher Associations, and a territory-wide Positive Parents Campaign.

Demographic patterns also diverged. The gender gap favoring girls disappeared in Hong Kong once attitudes and behaviors were accounted for, but remained significant in Singapore even after full adjustment, at nearly 8 points. Age mattered only in Singapore, where older students within the grade cohort scored up to 14 points higher, and birthplace effects were sensitive to which other factors were in the model. At the school level, resource shortages and teacher job satisfaction showed no significant associations with achievement in either system, though the authors note large standard errors that suggest more complex underlying mechanisms.

The authors are careful to stress that the study is cross-sectional and identifies associations, not causes, and they call for causal inference methods and qualitative research to unpack the mechanisms at work. The models explained about 59 percent of school-level variance in Singapore but only about 32 percent in Hong Kong, hinting that unmeasured factors, from peer dynamics to school leadership, may be especially important there. The overarching lesson is that even top-performing systems diverge in meaningful ways: both must support absent students and narrow gaps between privileged and underprivileged learners, but the levers that work in Singapore’s tightly coordinated ecosystem may not map directly onto Hong Kong’s more heterogeneous landscape. For any system hoping to emulate the world’s best readers, the message is that excellence is not a single recipe but a family of locally tuned strategies.

Subject of Research: Comparative analysis of student, family, and school predictors of fourth-grade reading achievement in Hong Kong and Singapore using PIRLS 2021 data

Article Title: Educational productivity in high-performing systems: a comparison of Hong Kong and Singapore on PIRLS 2021

Article References: Chen, G., Qi, Q., Jin, K.-Y., Wang, Z., & Xi, X. (2026). Educational productivity in high-performing systems: a comparison of Hong Kong and Singapore on PIRLS 2021. Large-scale Assessments in Education, 14(1), Article 50. https://doi.org/10.1186/s40536-026-00316-8

Image Credits: AI Generated

DOI: 10.1186/s40536-026-00316-8

Keywords: PIRLS 2021, reading achievement, Hong Kong, Singapore, hierarchical linear modeling, educational productivity, literacy, socioeconomic status, absenteeism, family-school collaboration, social-emotional learning, large-scale assessment