Enhancing transfer by learning generalized domain knowledge structures

Transferring one’s knowledge in new situations is usually associated with cognitively demanding processes. The paper explores an approach to facilitating transfer of knowledge by explicitly instructing learners in medium-level generalized but yet domain-connected knowledge structures that are applicable to a broader range of tasks in the domain and could be essential in managing the cognitive load associated with transfer. The paper includes a theoretical analysis of the potential role of the generalized domain knowledge in transfer and an experimental study designed to investigate the effectiveness of explicit instruction in a generalized domain knowledge structure (function–process–structure schema) in technical areas. Forty-nine undergraduate university students with low or no prior knowledge in the domain participated in the randomised 2 (schema-based vs. non-schema-based instruction) × 2 (general-to-specific vs. specific-to-general knowledge sequences) experiment investigating the effects of these two factors on posttest transfer performance and subjective ratings of learning difficulty (interpreted as indicators of cognitive load). The results indicated a significant (p < 0.05) main effect of schema-based instruction; a possible trend (p < 0.1) favouring general-to-specific instructional sequence for posttest test performance; and a significant interaction between the two factors for ratings of difficulty. The paper concludes that (a) transfer within a domain could be facilitated by explicitly instructing learners in generalized domain schemas; (b) general-to-specific approach could possibly be used as a preferred instructional sequence for enhancing transfer; and (c) cognitive load perspective could add some valid arguments to explain the role of generalized domain knowledge in transfer.

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