Autonomous driving paper index
Effects of an AI–VR enhanced flipped classroom on English achievement, metacognitive self-regulation, and learning motivation among EFL learners: the moderating role of technological literacy
One-line summary
Traditional flipped classrooms often fail to sustain young EFL learners’ engagement due to passive pre-class tasks and high self-regulation demands.
Engineering notes
Key topics: autonomous driving, control. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Traditional flipped classrooms often fail to sustain young EFL learners’ engagement due to passive pre-class tasks and high self-regulation demands. While Artificial Intelligence (AI) and Virtual Reality (VR) offer potential solutions, their combined impact and the moderating role of technological literacy in primary education remain underexplored. Grounded in Self-Determination Theory and Self-Regulated Learning theory, this study examined the comparative effects of an integrated AI–VR enhanced flipped classroom on English achievement, metacognitive self-regulation (MSR), and learning motivation, and whether AI–VR technological literacy moderated these effects. Using a quasi-experimental pretest–posttest control-group design, 60 fifth-grade Chinese EFL learners were assigned to either an AI–VR enhanced flipped classroom (n = 30) or a traditional video-based flipped model (n = 30). The same instructor delivered both conditions under a fully scripted protocol, with structured classroom observations confirming fidelity. ANCOVA revealed a robust effect on achievement ( \(\upeta_{{\text{p}}}^{2}\) = 0.252, Hedges’ g = 0.96, 95% CI [0.43, 1.49]; surviving Holm–Bonferroni adjustment), and smaller, preliminary effects on MSR ( \(\upeta_{{\text{p}}}^{2}\) = 0.082, g = 0.46, 95% CI [− 0.05, 0.96]) and motivation ( \(\upeta_{{\text{p}}}^{2}\) = 0.072, g = 0.53, 95% CI [0.02, 1.04]) that did not survive multiple-comparison adjustment. Critically, technological literacy moderated all three outcomes (all moderation effects robust under adjustment), with intervention benefits concentrated among higher-literacy learners; bootstrap confidence intervals indicated that precise Johnson–Neyman thresholds were not reliably estimated, so moderation is reported as directional. The findings suggest that AI–VR enhanced flipped instruction is conditional rather than universal: strongest gains accrue to achievement, while affective and metacognitive benefits depend on learners’ technological literacy.
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