Development of "Course Components" for Astro 101 Lectures, Part 1

Details Development of "Course Components" for Astro 101 Lectures, Part 1 Development of "Course Components" for Astro 101 Lectures, Part 1

Dec 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005aas...207.2702s&link_type=abstract

American Astronomical Society Meeting 207, #27.02; Bulletin of the American Astronomical Society, Vol. 37, p.1208

Computer Science

Learning

Scientific paper

An estimated quarter-million students take introductory astronomy each year (Fraknoi, A.E.R., 2001). The range in the resources, experience, and interest level of the faculty charged with teaching these classes may be as wide as the range of the science backgrounds of the students. Since each instructor applies his own selection bias as to which topics are key, innovations in astronomical lecturing must be modular and ideally previously vetted if they are to be adopted. Specifically geared to improving learning within the lecture, we present course "components": units which we have pre-tested in the large UMass introductory classes of 300 students. The design is such that a highly experienced professor might use just one for a good new way to cover a single problem topic, or a new professor might incorporate a large number working up a course for the first time. There is no single recipe for "components"; they are developed to suit the particular educational needs of each topic. One might be as simple as a single element of a lecture, or as complex as a 300 student interactive survey, a physical or software demonstration, an instant, in-class assessment via an class-response system (e.g. one of Mazur's "ConcepTests"), and a written or online homework problem. We will show some example components on distance and size scales, mathematics in astronomy, and the properties of supernovae. As this project is ongoing, we are most interested to hear from instructors their perceptions of the topics most difficult to teach, most in need of better demonstrations, and most prone to misconceptions, to help focus our future research ("Part 2").

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