The Differential Effects of Data‐Driven Learning on Explicit and Implicit Knowledge in Young Learners

Data‐driven learning (DDL) has been shown to promote explicit knowledge, but its efficacy in fostering implicit knowledge remains underexplored, particularly among younger learners. This quasi‐experimental study investigated the differential effects of paper‐based DDL versus traditional rule‐based instruction on the acquisition of explicit and implicit knowledge of English prepositions ( between , among , and during ). A total of 124 junior middle school students in China were assigned to the DDL, traditional, or control conditions. Mixed‐design ANOVAs on an error correction task (explicit measure) and a timed grammaticality judgment test (implicit measure with d ’ scores) revealed that while both instructional conditions yielded immediate explicit gains, only DDL facilitated sustained explicit knowledge and significant, durable gains in implicit knowledge. Theoretically, the findings suggest that the exemplar‐based inductive processing characteristic of DDL may underlie both the retention of explicit knowledge and the development of implicit knowledge, although the package‐level comparison limits causal claims about induction alone. Pedagogically, the results show that a paper‐based, low‐technology form of DDL is feasible in ordinary junior middle school classrooms and can restructure rule presentation into discovery tasks without new infrastructure.