Assessing exams I’m fond of analyzing the outcomes of exams I give. My favorite assessment is to look at how the score on each exam question correlates with the overall total score, and to plot this correlation coefficient versus the fraction of students who got that question correct. Roughly, I’d like the plot to turn … Continue reading Graphs and Grading: Winter 2016
I’ll guess that most people reading this don’t believe in homeopathy, astrology, or the existence of lizardlike extraterrestrials that walk among us. This is probably not because any of us ourselves have researched these topics, but rather because we are unconvinced by their proponents, and also perhaps because these ideas have not managed to break … Continue reading Scientific publishing for non-scientists
I’ll continue describing a graduate biophysics course I taught in Spring 2015. In Part I, I wrote about the topics we covered. Here, I’ll focus on the structure of the course — books, assignments, in-class activities, and the students’ final project — and note what worked and didn’t work. (What didn’t work: popsicle sticks.) Click … Continue reading Recap of a graduate biophysics course — Part II
In Spring 2015 I taught a graduate biophysics course for the first time. It was a first in several ways: the course didn’t exist before, so I developed it from scratch, and it was also the first graduate course I’ve taught in my nine years as a professor! I’ve been thinking for months that I … Continue reading Recap of a graduate biophysics course — Part I
In Part I, I wrote about how I started exploring the topic of machine learning, and we looked briefly described one of its main aims: automating the task of classifying objects based on their properties. Here, I’ll give an example of this in action, and also describe some general lessons I’ve drawn from this experience. … Continue reading Learning about (machine) learning — part II
Machine learning is everywhere these days, as we train computers to drive cars, play video games, and fold laundry. This intersects my lab’s research as well, which involves lots of computational image analysis (e.g.). Nearly everything my students and I write involves writing or applying particular algorithms to extract information from data. In the past … Continue reading Learning about (machine) learning — Part I
(A more technical post than most, in which we look at bacterial population densities, and watch a movie.) This term I taught a graduate biophysics course, about which I’ll write a recap later. Bacteria came up a lot in the course, both because they’re important but also because they offer many nice illustrations of how … Continue reading Bacteria and Boltzmann
A friend pointed me to a recent study looking at the earnings (salaries) of people with degrees in different majors — for example, what’s the average salary of a physics major? Or a history major? The authors of the study are economists, and in my opinion put forth in their exposition of the study an … Continue reading How much is that physics major in the window?
Next term, I’ll be teaching a brand-new graduate biophysics course. (It’s the first time teaching a graduate course in my eight years as a professor!) I’ve spent quite a while thinking of what should be in it and how the course should be structured. Here, I’ll just note my list of topics (below, with a … Continue reading T-minus 9 days for my graduate biophysics course
What makes a good exam question? Not surprisingly, I try to write exams that most students who are keeping up with the course should do well on — almost by definition, the exam should be evaluating what I’m teaching. But I also want the exam to reveal and assess different levels of understanding; it would … Continue reading What have I got in my pocket?
The Eighteenth Elephant 