Exploring curiosity, interest, and surprise: normative ratings of a magic trick video dataset in Italy

Epistemic emotions, including curiosity, interest, and surprise, play a crucial role in learning and cognitive processes by bridging motivation and knowledge acquisition. The Magic Curiosity Arousing Tricks (MagicCATs) dataset, comprising 166 magic trick video clips, provides a standardized tool for studying these emotions in experimental settings. This study provides normative ratings for the dataset within an Italian context, based on a sample of 654 participants aged 18–86. Participants evaluated the videos based on clarity, curiosity, interest, surprise, and confidence in solving the trick, using both binary and Likert scales. Rigorous data screening ensured integrity, enhancing the reliability of the findings. The dataset’s ecological validity, dynamic stimuli, and capacity to elicit multiple epistemic emotions offer advantages over traditional methods. By contextualizing MagicCATs within an Italian framework, this study advances the investigation of epistemic emotions by supporting their simultaneous assessment across a broad adult age range. Applications include experimental psychology, neuroscience, and education, with potential implications for mental health and age-related cognitive research. Data and resources are available for replication and further exploration.