Is asking students to generate predictions an effective technique to induce meaningful cognitive conflict and to facilitate conceptual change?

教授科学是具有挑战性的，因为它需要改变学生中持续存在和普遍存在的误解。最近的研究表明，产生预测是一种很有前途的策略，有助于儿童修正误解。这种促进作用被发现与当儿童事先产生明确的预测时，对违反预期的结果的增强的生理惊喜反应有关。意外反应的程度进一步表明取决于参与者对他们预测的信心以及预测误差的大小。项目第二阶段的总体目标是更准确地捕捉对意外的预测和随后对误解的修正的影响。为此，我们将建立一个正式的模型，每个孩子的先验信念，并比较他们的生理惊喜反应和信念修订的最佳贝叶斯学习。贝叶斯推理框架对于这个目的特别有用，因为它提供了一个正式的模型，信心，预测误差和信念修正之间的相互作用。它准确地告诉我们，根据概率论，违反预期的结果应该如何用于更新信念和模型（即，理性归纳推理）。因此，我们可以测试a）通过做出明确预测来参与先前模型的儿童是否会做得更好（即，更接近统计学最佳）使用相互矛盾的证据，而不是事先没有使用先前模型的儿童，以及B）信心和预测误差在这种好处的发生中扮演什么角色。

Teaching science is challenging because it entails changing persistent and pervasive misconceptions in students. Recent research suggests that generating predictions is a promising strategy that facilitates children’s revision of misconceptions. This facilitation has been found to be related to an enhanced physiological surprise response to expectancy-violating outcomes when children generated an explicit prediction beforehand. The magnitude of the surprise response has further been shown to depend on participants’ confidence in their prediction as well as on the size of the prediction error. The overarching goal of the second project phase is to more precisely capture the effect of generating predictions on surprise and the subsequent revision of misconceptions. To this end, we will build a formal model of each child’s prior beliefs and compare their physiological surprise response and belief revision to an optimal Bayesian learner. The Bayesian inference framework is particularly useful for this purpose because it offers a formal model of the interplay between confidence, prediction error, and belief revision. It tells us precisely how, according to probability theory, expectancy-violating outcomes should be used to update beliefs and models (i.e., rational inductive inference). We can thus test a) whether children who engage their prior models by making an explicit prediction make better (i.e., closer to statistically optimal) use of conflicting evidence than children who do not engage their prior models beforehand, and b) what roles confidence and prediction error play for this benefit to occur.