Since Bruner’s introduction of discovery learning in the 1960s, there has been an ongoing and intensive debate on the value of inductive teaching methods (e.g., problem-solving followed by instruction, such as in problem-based learning and productive failure) compared to deductive teaching methods (instruction followed by problem-solving, such as direct instruction). Although it has been strongly argued that problem-first inductive methods are incompatible with human cognitive architecture as perceived by cognitive load theory, the main goal of this position paper is to appeal to broaden cognitive load research on inductive and deductive methods, and especially, their orchestration in educational programs of longer duration. We describe eight possible sequences of problem-solving and instruction and conclude that, when well designed, at least six of these sequences can be compatible with cognitive load theory, including productive failure and problem-based learning. We suggest that rather than comparing inductive with deductive methods, future research should also include inductive methods that use different types of supported problem-solving in combination with expository and inquisitory instruction. We propagate a design perspective, looking for the instructional goals, learner characteristics, and other conditions that make selected teaching methods effective, efficient, and attractive.

自从布鲁纳在 20 世纪 60 年代引入发现学习以来，关于归纳教学方法（例如解决问题后进行指导，例如基于问题的学习和生产性失败）与演绎教学相比的价值一直存在激烈的争论方法（指导后解决问题，例如直接指导）。尽管人们强烈认为问题优先的归纳方法与认知负荷理论所认为的人类认知结构不相容，但本文的主要目标是呼吁扩大归纳和演绎方法的认知负荷研究，特别是它们的认知负荷研究。持续时间较长的教育项目的编排。我们描述了八种可能的问题解决和指导序列，并得出结论，如果设计良好，其中至少有六种序列可以与认知负荷理论兼容，包括生产性失败和基于问题的学习。我们建议，未来的研究不应将归纳法与演绎法进行比较，而应包括将不同类型的支持性问题解决与说明性和探究性教学相结合的归纳法。我们传播设计视角，寻找教学目标、学习者特征以及其他使所选教学方法有效、高效和有吸引力的条件。