The following undergraduate courses will be showcased leading up to and as part of the College Themester 2023 program.
AST-A 107 – The Art of Astronomy
Instructor: Dr. Liese van Zee
From breath-taking images produced with today’s space telescopes to measurements that infer the presence of black holes, dark matter, and dark energy, the science of astronomy uses light to find the truth about the universe within which we live. In this course, we explore the science of imaging the universe and the technology that makes the images possible. Topics include the night sky, telescopes and cameras, light and color, and the science behind the images.
History and Philosophy of Science
HPSC-X 200 Scientific Reasoning and Scientific Methods
Instructor: Dr. Jordi Cat
Scientists, politicians, administrators and the lay public pay attention to scientific claims and controversies. For instance, is some substance really harmful to our health? For different reasons, we all benefit from reaching informed opinions and informed decisions. You might be the victim or beneficiary of someone’s opinions and decisions. We must first try to understand the claims and then take a critical look at the claims and at any reasoning and procedures behind them. In the best cases, the evidence is never conclusive. The results can always be revised in light of new evidence, better experimental designs and alternative hypotheses. In order to assess and interpret data and to produce and evaluate hypotheses, scientists apply a variety of methods. Different methods may have different goals and limitations; some limitations are methodological, others are practical, others ethical or legal.
In this course we will examine and discuss questions such as, Why accept any scientific claim? How do scientists produce hypotheses and evaluate them? What kinds of hypotheses are there and what are they good for? How do scientists produce, collect and evaluate empirical data, big or small? Do scientists produce and use only numerical data? How do they present quantitative data visually? Can they reason with pictures as well as with numbers? How do they use data as evidence for hypotheses? Why do scientists care about hypotheses that concern a group of individuals that is larger than the ones we actually observe, test and want to deal with? How can a group of different subjects in a study help establish more general results? Aren’t all individuals different, anyway? What’s so special about hypotheses about causal links? How do experimental designs reflect the causal character of such hypotheses? Are all kinds of experimental designs equally useful? Are there different levels of strength of evidence? What can go wrong?