Magic Curiosity Arousing Tricks (MagicCATs): a novel stimulus collection to induce epistemic emotions

There has been considerable interest in empirical research on epistemic emotions, i.e. emotions related to knowledge-generating qualities of cognitive tasks and activities such as curiosity, interest, and surprise. One big challenge when studying epistemic emotions is systematically inducting these emotions in restricted experimental settings. The current study created a novel stimulus set called Magic Curiosity Arousing Tricks (MagicCATs): a collection of 166 short magic trick video clips that aim to induce a variety of epistemic emotions. MagicCATs are available for research, and can be used in a variety of ways to examine epistemic emotions. Rating data also supports that the magic tricks elicit a variety of epistemic emotions with sufficient inter-stimulus variability, demonstrating good psychometric properties for their use in psychological experiments

Augmenting Assessment with Learning Analytics

Learning analytics as currently deployed has tended to consist of large-scale analyses of available learning process data to provide descriptive or predictive insight into behaviours. What is sometimes missing in this analysis is a connection to human-interpretable, actionable, diagnostic information. To gain traction, learning analytics researchers should work within existing good practice particularly in assessment, where high quality assessments are designed to provide both student and educator with diagnostic or formative feedback. Such a model keeps the human in the analytics design and implementation loop, by supporting student, peer, tutor, and instructor sense-making of assessment data, while adding value from computational analyses

Epilogue for the IJSME Special Issue: Metacognition for Science and Mathematics Learning in Technology-Infused Learning Environments

The final publication is available at Springer via http://dx.doi.org/10.1007/s10763-016-9726-x