Machine Learning in Introductory Astrophysics Laboratory Activities

Autor/in	Smith, Donald A.
Titel	Machine Learning in Introductory Astrophysics Laboratory Activities
Quelle	In: Physics Teacher, 59 (2021) 8, S.662-663 (2 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0031-921X
Schlagwörter	Artificial Intelligence; Man Machine Systems; Introductory Courses; Astronomy; Physics; Science Laboratories; Science Activities; General Education; Electronic Learning; COVID-19; Pandemics + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Mensch-Maschine-System; Einführungskurs; Astronomie; Physik; Allgemein bildendes Schulwesen; Allgemeinbildung
Abstract	A working knowledge of Artificial Neural Networks is rapidly becoming critical for navigating the modern world. Although the last few years have seen an explosion of the use of these tools in research, and there are many do-it-yourself articles on the web, they have not yet filtered down to wide implementation in introductory courses. I report here on my integration of machine learning activities into a general education course on galaxies and cosmology. I describe four lab activities for image classification, and I reflect on the strengths and weaknesses of using these tools in the context of online instruction during the 2020-21 pandemic academic year. (As Provided).
Anmerkungen	American Association of Physics Teachers. One Physics Ellipse, College Park, MD 20740. Tel: 301-209-3300; Fax: 301-209-0845; e-mail: pubs@aapt.org; Web site: http://aapt.scitation.org/journal/pte
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01