Student ownership in model-based versus image-based astronomy learning

Determine whether students in introductory astronomy courses (ASTRO101) can attain an equivalent sense of ownership and engagement when constructing and fitting models to non-image datasets (for example, HR diagram isochrone fitting using tools such as Clustermancer or pulsar timing analyses) compared to the ownership experienced when acquiring and analyzing self-requested telescope images, and assess the implications for self-efficacy and course design.

Background

The report describes UNC’s OPIS! and MWU! curricula, where students use robotic telescopes and archival data to conduct authentic investigations. These efforts produce large gains in self-efficacy, with students initially exhibiting ownership over images they personally acquired and later transitioning to ownership over final work products like multi-wavelength composite images.

The authors note that some MWU! activities involve non-image data (e.g., pulsar timing) and advanced modeling workflows (e.g., star cluster membership separation and isochrone fitting in Clustermancer). This raises the explicit question of whether introductory students can experience comparable ownership when engaging with model-based analyses versus image-based activities.