Get Your Facts Straight: Prediction-Based Fact Learning Explained by Metacognitive Surprise about Facts

Prediction-based learning is an effective teaching method for building factual knowledge, i.e., semantic learning. Its effectiveness likely depends on its potential to elicit surprise in learners. Only a few studies tested this hypothesis using a prediction-based learning framework comparable to semantic learning in the classroom. Most of these studies used physiological measures of surprise. However, the link between prediction-based semantic learning and learners' metacognitive surprise remains to be investigated. Using mixed models, we tested and explored to what degree participants' (N = 41; Mage = 21.9 years, SD = 1.5, 73% female) metacognitive surprise about the learning material (numerical trivia facts) explained how well participants learned (continuous metric) and recalled (binary metric) this material during a numerical-fact learning task designed to resemble classroomlike prediction-based learning. In line with our hypothesis, preregistered analyses showed that the more...Show morePrediction-based learning is an effective teaching method for building factual knowledge, i.e., semantic learning. Its effectiveness likely depends on its potential to elicit surprise in learners. Only a few studies tested this hypothesis using a prediction-based learning framework comparable to semantic learning in the classroom. Most of these studies used physiological measures of surprise. However, the link between prediction-based semantic learning and learners' metacognitive surprise remains to be investigated. Using mixed models, we tested and explored to what degree participants' (N = 41; Mage = 21.9 years, SD = 1.5, 73% female) metacognitive surprise about the learning material (numerical trivia facts) explained how well participants learned (continuous metric) and recalled (binary metric) this material during a numerical-fact learning task designed to resemble classroomlike prediction-based learning. In line with our hypothesis, preregistered analyses showed that the more surprising participants found a fact, the more they learned from it. Extending previous work, we found that this link remained when controlling for a) between-fact differences in learning potential and b) facts already known to the participants and when c) participants failed to recall a fact correctly. Further extending previous work, our exploratory analyses suggested that learning also improved when participants perceived the facts as nonsurprising. So, the link between metacognitive surprise and learning may be u-shaped rather than linear. Altogether, these findings hint that learners'surprise about the learning material is one of the factors explaining to what degree learners learn from their prediction mistakes to update their factual knowledge. We forgo conclusions about the link between metacognitive surprise and recall accuracy since the confirmatory and exploratory results were ambiguous and negligibly small.Show less

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Get Your Facts Straight: Prediction-Based Fact Learning Explained by Metacognitive Surprise about Facts