<![CDATA[Background: Students in distance statistics courses often achieve lower learning outcomes compared to those in face-to-face settings. Although the Technological Pedagogical Content Knowledge (TPACK) framework has been widely applied in technology-integrated instruction, limited empirical evidence clarifies whether prior mathematical knowledge (PMK) moderates its effectiveness in asynchronous online statistics learning. Aim: This study examined the effectiveness of a TPACK-based online tutorial design in improving students’ statistical literacy and investigated the moderating role of PMK. Methods: A quasi-experimental design involved 170 distance education students (experimental n = 85; control n = 85) classified into low, medium, and high PMK levels. The experimental group participated in a 12-session TPACK-based online tutorial with periodic webinar integration, while the control group received conventional online instruction. Statistical literacy was measured using post-test and normalized gain scores and analyzed through two-way ANOVA and simple effects tests. Results: The analysis revealed a significant main effect of tutorial design (ηp² = .102–.116), indicating higher achievement among students receiving TPACK-based instruction. PMK showed a stronger main effect (ηp² = .215–.230), suggesting substantial differences in performance across readiness levels. A significant interaction effect demonstrated a threshold pattern. Students with medium and high PMK obtained significantly higher post-test scores and normalized gains in the experimental group, while students with low PMK showed no statistically significant differences between tutorial designs. The magnitude of learning gains increased consistently from low to high PMK categories, confirming that instructional benefits intensified alongside mathematical readiness. Conclusion: The effectiveness of TPACK-based online tutorials depends on students’ prior mathematical knowledge. Instructional advantages are pronounced for learners with adequate foundational skills but limited for those with low readiness. These findings emphasize the need for adaptive support mechanisms to ensure that technology-integrated instruction produces equitable outcomes in distance statistics education.]]>
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