[What follows is pretty free form, so sorry if it's hard to follow.]
Yesterday, I went to a talk on science education in the twenty-first century. The main points from the talk were:
- Traditional lecture-style teaching results in 10-20% retention of knowledge.
- Working memory can last for at most 7 distinct topics.
- Examples, analogies, and images decrease the working memory load.
- Explain things as cohesive units rather than as disjoint parts.
- Even if the choice is insignificant, the ability to have a choice increases motivation.
- Most students leave classrooms with less “expert-like” thinking than when they entered.
… So, if it isn’t really clear, I research a lot on education in STEM areas. And, the longer I am in college, the more I am convinced that many professors have no idea where the bar should be set on how students should preform. A particular favorite is a professor who explained his curving scheme thusly:
Of course there will be a curve! I list everyone by their uncurved score and then [moving his hands in a window/gap creating fashion up and down] go ‘hmm there.’ And divide the grades that way [with partitions].
In all honesty, this seems to be the primary methodology for curving computer science courses, including ones where exams are already curved. And it seems detrimental to students learning. This arbitrary curving indicates that one did better than some percent of students, while giving no evidence of what material was actually learned.
I am currently grading the second programming course in the curriculum. And I feel like banging my head against a wall while doing so. Students make mistakes on material covered in the prerequisite course. Repeatedly. After I dock points and write a comment on what error occurred.
The professor for this course disproves of me grading students harshly. This includes docking points for having unnecessary looping and requiring that all of their variables be more meaningful than ‘x.’
The professor I am working under is also the professor for one of my courses. My project is notably more difficult than others (many have settled on game A.I. while I’m doing computer vision and machine learning). On more than one occasion, he has indicated that he feels it is too complex for me. I’m not sure if this is cultural or because he feels I can’t succeed or that it shows an example of higher difficulty that others should be able to do.
From elementary through high school, in gifted education and accelerated learning courses. College is the first setting where I am always in classes that are designed for the middle. College is also, interestingly, the first time that I have tested notably worse than my peers and been told that I can’t do something.
I find myself questioning why I am compared to everyone rather than judged on my own qualities. I have had professors grade me more harshly for being clever, and I don’t agree to this. But, if I’m choosing to do work at a different level, why should I be discouraged? And, to be fair, I think students working at a lower than mean level have a right to work at that level.
Professors need to work on showing students why subjects are important and how to learn them. Professors are typically passionate about their subjects, they should share this passion.
