As teachers, we must continue to re-engineer our curriculum, experiment with new and different methods of delivering course content, and bring emerging technologies into our classrooms.
The greatest teachers are the ones that turn a B student into an A student, or a failing student into a B student.
Also consider that if you [have] a straight-A student in your class, that student has straight A’s not because of teachers, but in spite of teachers. That’s what having straight-A means. It means you do well, no matter the teaching talent of the teacher. That’s what straight A’s mean. So if you’re a teacher and you put forth your straight-A student as though you had something to do with it, you are deluding yourself.
For those who read my blog or Facebook, you probably noticed that I haven’t been posting very regularly for the past several weeks. This is mostly due to my new job with Heald College Online, where colloquially I will say there has been a “steep learning curve”, or more appropriately a “steep development curve”.
Recently I have been asked by Twin Rivers Adult School to help in the writing of their WIA Title II Grant Application. Like many grants, this one is a team effort, where the subject matter experts are being asked to primarily write the portions of the grant that correspond to their area of expertise. But, not all of these subject matter experts have done a lot of grant writing, and while I don’t want to claim that I have done a tremendous amount of grant writing myself, I have written a few in different contexts that have been successful in receiving an award. So based upon my previous experience I wanted to write up some tips for my fellow subject matter experts at Twin Rivers, and also given that they are a publicly funded school, thought I should make this knowledge available to the world at large.
While I make no guarantees (and bear no liability) that the advice I’m sharing here will produce good results, I will explain my rationale for each “best practice” so you can make your own decision about whether to follow my advice or not. (I really don’t like the phrase “best practice”, but I’ll use it for now, as it is what is commonly used.)
My friend Ruth Ackerman cross-posted a video from the AFT on her Facebook page today, which questions some of the conclusions that some groups make from the mediocre U.S. performance on the PISA. (And I’m not going to dive into that politically charged question right now.)
I think we need to step back further, and ask if the PISA is measuring the “right” knowledge. To try and answer this for myself, I found a set of sample questions for the PISA. And I started to go through and answer the questions. And I found one question where the PISA is wrong.
The question basically is about a science article where it talks about scientists that cloned a cow into five calves. And then asks if the calves have the same genes, the same gender, and the same color. The question appeared to want to see if students could infer the answer, as it didn’t explicitly give this information in the article that it had the student read. And the question wanted to have the answer being “yes” for each one.
BUT, while it may seem to be a reasonable assumption to make that the answer would be “yes” for each, it isn’t necessarily the case for color of the cows. I say this, because people who have cloned their cats have found that they often turn out to be a different color than their original cat, so I suspect this same thing could happen with cows. So what if a student knew had this advanced knowledge and marked “no”… Well, they would have been said to be wrong, when in fact the PISA is likely wrong. (I say likely, as I am not sure that cat and cow clones would behave similarly when it comes to color, but it is no more or less a reasonable or unreasonable assumption as the one the PISA wants the student to make.)
Update: I emailed PISA (firstname.lastname@example.org) this blog entry, but never heard back from them.
This morning I emailed Dr. Baker, the President of the International Educational Data Mining Society, the following open letter that encourages the society to rename itself to the International Educational Data Science Society, which I hope will spark dialogue within the educational data science/mining community.
I just posted the following Quora answer to the question “What are the problems with math education today?”
One of the issues with math education that is rarely considered, is a question of “what should be learned”? While I echo other respondents who say that there is not consensus on the goal of math, if we at least assume that one important part of mathematics is how it can be used, then there are scientific methods of determining which particular parts of math are important to know for a particular context (nation, career, etc.), but I have seen little in the way of research on this, and less in the way of using the research that is available.
For example, in the U.S., not a single state nor the Common Core State Standards require students to know what a Trillion means before they graduate high school (Walker 2011), yet they are supposed to know scientific notation and imaginary numbers before graduation… Something seems amiss with this set of priorities.
Walker, J. J. (2011). Missing a “Trillion”: How do we know if we are teaching the right things? SSRN eLibrary. doi:10.2139/ssrn.2194853
I just posted the following comment on a good article from The Economist about How science goes wrong:
Part of the problem with science, at least in the United States, stems from our STEM (Science, Technology, Engineering and Math) education. Science education still emphasizes the amazement of scientific results over understanding and following the philosophy of science. Just look at any science fair, and one can see this attitude in full evidence. Further, our math curriculum (even with improvements from Common Core) is still geared towards the science of the cold war, with most emphasis on ideas towards calculus, instead of a focus on understanding statistics. And of the greatest irony (and almost hypocrisy), scientific methods are not used to determine what should be taught in science or math curriculum. Instead there is still an emphasis of eminence over evidence, such that even Common Core relied mostly on committees of select experts and educators, than to use large scale data analysis of the needs of the job market or even to look at what is needed to truly build a pathway towards teaching students the math and methodologies necessary to be scientists, including more knowledge in statistics, data science, and the philosophy of science. If we want to have a solution to the future of science, we must start today with those students who will be our future scientists.