Computer Science – Learning
Scientific paper
May 2002
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002aas...200.2601s&link_type=abstract
American Astronomical Society, 200th AAS Meeting, #26.01; Bulletin of the American Astronomical Society, Vol. 34, p.677
Computer Science
Learning
Scientific paper
Following in the footsteps of its older sibling, Physics Education Research, Astronomy Education Research (AER) uses the systematic observation and inference techniques honed in astronomical research to understand how students in our astronomy courses learn and how faculty can be create more productive learning environments. Not surprisingly, initial investigations have focused on traditional concepts that faculty eternally find students struggle with--moon phases, seasons, and gravity. Although the results of these repeated investigations usually reproduced identical results, much of the evolution of AER has been to find which educational research methods produce the most rigorous and insightful results and how best to use these results effectively in classrooms. Above all, all results strongly suggest that students leave astronomy courses deeply understanding far fewer concepts and having much lower attitudes toward science than we would like. As such, this presents a motivation, framework and agenda for future work.
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