There was no actual teaching today, since I usually just take the first day of classes to go over the syllabus, expectations, due dates, etc., but it’s nice to be back in the swing of things.
I am both terrified and beyond excited for this calc class. We’ll see how things go.
It’s weird teaching a small section (120 students) of STAT 213, though, especially after having two sections of 240 students (plus 120 students for STAT 217) last semester.
Jesus, I had 600 students last semester. No wonder I had no time for anything else.
So like I mentioned in an earlier blog, all three of my classes meet right in a row, starting at 9:30 and ending at 1:45.
I don’t mind that, of course, but I can already tell this is going to be brutal on my voice. We’ll see if it makes it to the end of the semester.
So this upcoming semester just went from “I don’t know if I’ll be teaching” to “I might be getting one class” to “I’m getting THREE classes” very quickly.
- THREE CLASSES! They obviously need me, which gives me (hopefully) better chances of a permanent job sometime in the future maybe kinda sorta please?
- These three classes are two STAT 213 classes and the only STAT 217 class being offered this semester. I’ve done these classes before, so prep work won’t be too bad. Hopefully.
- The classes meet back to back to back on Tuesdays/Thursdays and they’re not too far away from one another.
- I will have SIX HUNDRED students. That’s…a lot.
- I’ll probably have to drop that Continuing Education math class, though, just because that would probably be a little too much.
- …That’s pretty much it for the “bad.”
So this week has sucked royal nuts for various reasons. But today I got an email from Jim saying that STAT 213 in the spring was suddenly available and that it could be mine if I wanted it.
And I had to very calmly reply “yes plz give” without actually being like “YES PLZ GIVE!”
So yeah. I get two classes this spring: STAT 213 and STAT 217. I’ll hopefully be getting STAT 217 in the summer, too.
(And, you know, more classes in later semesters as well.)
So I had a meeting with Jim this morning to talk about next semester. Turns out I not only get to teach TWO classes next semester, but one of them is a 300-level class! I’ve never taught a 300-level class before.
It’s called “Statistics for the Physical and Environmental Sciences,” and it sounds like STAT 213 and STAT 217 combined and for people with a calculus background. I also get to teach them R, which is fantastic.
So yeah, I’m SUPER FREAKING EXCITED. I didn’t think I’d get any classes next semester, let alone two.
Let’s hope this trend continues!
I’m probably more stressed about tomorrow’s than some of my students are. I’m worried something’s going to go wrong, because that’s been the defining characteristic of this semester so far.
Sorry for the crappy blogs. Been really busy/stressed/nervous/overwhelmed.
Dudes, teaching this night class is the best thing ever.
Like…I have all day to walk and then go to work from 6 PM to 9 PM? You couldn’t even imagine a better time of day for me to work.
This is so fantastic. My job cannot get better.
Well, actually, I guess the only way it could be better is if there was any sort of permanence to it past this semester. I would love to have this as my career, I really would. But I have to just be patient at this point.
Will everything work out so that I can do this for the rest of my life?
But I really, really, really am hoping it will.
Edit: here’s the room I’m teaching in. This is the view from my little lecture podium.
Holy crapples, this is fantastic.
I think they should have assigned this as required reading to all first-year grad students who had to TA as part of their funding, and then made them re-read it at the beginning of every subsequent year so as not to forget important stuff. It’s also still relevant as an instructor. At least, most of it.
“Many instructors assume that students will read what is handed to them; I think this is incorrect.”
Oh my god, yes. This wasn’t something I ever did as a TA, but as an instructor (both at UI and U of C), I like to take time during the first lecture to actually go over the syllabus and any other important hand-outs. I particularly like to do this in the form of a PowerPoint so that I can really focus on the big things. I think it really helps emphasize what’s important to the students rather than making them wade through a two- or three-page document that includes a little information on every aspect of the class.
“People never learn course material as well as when they have to explain it to others.”
U of C has a thing up here for their 200-level stats classes called “continuous tutorial.” This is kind of like drop-in homework help where a TA staffs a computer lab for an hour, and during that hour students from STAT 213 and STAT 217 can drop in, work on homework, and ask questions of the TA if they have them. During my first continuous tutorial, I botched the hell out of a really simple probability question while helping a student. It wasn’t because I didn’t know how to do that type of problem, but because I hadn’t done that type of problem in quite some time, I blanked on the very simple solution and really confused the student. Brilliant, right? It is super important, both as a TA and as an instructor, to actually work through the homeworks assigned to the students and make sure you know how to do them. Because there’s not a lot of things more embarrassing than blanking on a question covering a subject that you supposedly know well enough to teach to the students.
“To me, motivating means addressing the history, culture, and usefulness of mathematics.”
LAKJSDFLASKFJALKF ASDFYADJFSDJ YES YES YES YES YES YES YES A THOUSAND TIMES YES
If you can put the topic into some sort of “non-computational” context, I think students are apt to be more open to it, approach it with less fear, and maybe even get excited about it. This is such an important idea to me, you have no idea.
What’s the only thing better than teaching stats?
Teaching an evening class of stats!
(Which…I guess…is still teaching stats…just…just humor me here.)
I talked to Jim today and not only does it sound like I’m going to get to teach in the spring (which is like the first summer session at UI), but I’ll get to teach the super late “none of the other instructors want this timeslot” evening class of 217. That means I can spend ALL DAY WALKING before going in to work, especially since I’ll already have my class notes mostly prepared (due to teaching 217 this semester).
That’s going to be awesome.
Now I just need to somehow get a course to teach for fall, haha. I will do everything in my power to make this a permanent thing.
Teaching is over for the semester.
I am sad.
But I’d be a lot sadder if I didn’t have anything to teach next semester.
I really, really hope that I’ll continue to be needed as a lecturer. Hell, I don’t need any major job security at this point. If it has to be semester-to-semester for a while, I’ll take it.
I just…I want to keep doing this. This is what I’m meant to do with my time on this earth, I’m sure of it.
It’s TEACHIN’ TIME!
I don’t think I can properly convey my excitement over being able to teach statistics again. I mean, I guess I’ve been running labs for the past two years, but it’s just not the same, you know? I really feel like teaching statistics—especially intro statistics—is what I’m meant to do with my life.
And I know this position is only temporary (I’m technically only hired through December 31st of this year), but I’m going to do whatever I can to see if I can keep it going longer. Surely some of the higher up professors who teach 213/217 would want an opportunity to focus more on their research or on the upper-division courses they’re teaching, right?
Either way, I am eternally grateful to Scott for really pushing those in charge to hire me. I’m pretty sure I would have never gotten this opportunity without his influence. Now I just have to prove that I know what I’m doing and hope that they need somebody for next semester.
I AM, THAT’S WHO!
This afternoon, in the span of about an hour, I went from hoping to eventually get a teaching job somewhere to hearing that I get to teach a section of STAT 213 in the fall. It’s currently just for that semester, meaning there’s no guarantee that I’ll be hired for any subsequent semesters, but that’s what they said at UI and I worked for two years (plus summers) as a lecturer there before heading to the frigid north.
I am super, super excited, yo.
It’s summer session, which means it’s time for me to be a TA again!
Actually, this semester it’s a little bit different. One of the professors I’m TA-ing for was one I TA-ed for last semester. He knows I want to be a stats teacher at some point and seemed to like the job I did last semester, so this semester he’s letting me basically teach a fourth day of class in place of the lab I was supposed to run.
Which is super snazzy.
I’m also TA-ing for a new class, but it’s a lower-level one than the others, so it shouldn’t be so bad.
I have an exciting life, huh?
We had to write a teaching philosophy statement, summarizing our approach/attitude towards teaching math and stats, for our seminar class. I’m going to post mine here. It explains how I like to think about teaching stats and emphasizes what I consider to be the most important things to keep in mind while delivering the subject to students who may be less than enthusiastic about anything number-related.
I have, for the majority of my life, been a student, but only recently have I taken on the role of a teacher. From 2012 to 2014, I worked as a lecturer at the University of Idaho, teaching introductory statistics to undergraduate students. Though I was brand new to teaching and wary about teaching material that had the reputation of being boring, difficult, or both, it took me only my first semester to solidify my teaching philosophy and to develop instructional techniques that have been proven effective in getting students interested in and engaged in learning statistics.
My approach to teaching can be best broken into four key components: empathy for the students, flexibility in the teaching techniques and methods, enthusiasm for the material, and the ability to show real-world application of the material. These four components work together to emphasize my core teaching philosophy and goals: in order to best foster learning, teaching should not only cater to the student but cater to the subject being taught as well, allowing for students to have a learning experience that allows them to see both the technical and the practical side of the material.
Unlike many who end up as lecturers in mathematics or statistics, I come from a background heavy in the humanities and the social sciences. Due to this background, I am able to easily empathize with students who may lack a strong mathematical background and thus may be intimidated or nervous about taking a statistics course. Such students are common in introductory courses similar to the ones I have taught, as these courses are usually used to fulfill a course requirement and are often the only classroom exposure to statistics that many students get.
An empathetic mindset—especially when introducing “basic” concepts and notations that may be brand new to many of the students in the class—is a mindset I try to adopt when teaching. Telling students that it’s okay if this is the first time they’ve seen how to calculate a mean or how to read summation notation, and then to walk them through it slowly but without condescension, can go a long way towards fostering a good relationship with them while also making them feel more comfortable with the material. In my two years of lecturing, I had many students comment that they appreciated the fact that I took the time to teach them the very basic components of statistics before delving into the more complicated material and that this helped them feel more at ease in the class.
Along with empathy for the students, another important component in my approach to teaching is to be flexible with how the material is taught. Most statistical concepts can be explained in several different ways—showing students the equations, explaining a concept using an analogy, creating a visual representation of the concept, among others. I have learned that it is important to try to approach and explain a concept from several different angles to allow as many students to grasp the concept as possible. For example, when students are learning about analysis of variance, I have found that some students understood it by looking at the equation for the F statistic, while others understood it by seeing a visual of the variances that the F statistic is actually comparing. Being able to explain a concept from multiple angles helps to make sure that every student is able to grasp the concept and understand it in a way that’s best for them.
The third component to my teaching approach is one that I feel is especially important but often overlooked in the field of statistics—showing enthusiasm for the material. In my own experience as a student, when an instructor fails to show interest for the topic they are teaching, it becomes difficult to remain engaged in the class and ultimately more difficult to learn. For a subject like statistics, which already seems to have a reputation of being dry and boring for many students, it is important for an instructor to be able to show that the material and concepts that they are teaching are more than just equations on a page.
For me, part of showing my enthusiasm for the subject is to really try to give students an “under the hood” look at statistics. Rather than just show them a formula or tell them a theorem, I’ve found that students remain much more engaged if they are shown why a formula is the way it is or why a theorem is important. For example, when teaching students the general formula used to calculate binomial probability, I choose to “derive” the formula by using some basic probability examples and then work up to the actual formula itself. Giving them this deeper glimpse into why the formula is written the way it is not only gives them a better understanding of the formula itself (they are no longer just “blindly” using it but understand the reasons behind it), but it also engages them in the process of seeing how and why the formula works.
Another way of showing enthusiasm for the subject is to present students with fun and interesting examples of concepts they are being taught. For example, after students learn about visuals like bar charts and histograms, I like to take a few minutes and show them some examples of poorly constructed or exaggerated graphs used by the media or by politicians. Bringing some humorous or interesting examples into the classroom can help keep students engaged and make them more interested in the subject.
Related to the concept of showing enthusiasm for the material, the fourth and final component of my approach to teaching is to make sure to give students some real-world applications of the material they learn in the classroom. This is a component that I think is especially important in teaching an introductory statistics course, as nearly all academic fields employ statistical procedures to some degree, but students from other disciplines often think that they will never use the techniques they learn in class. The main way I employ this component is by using actual data from various different fields in my in-class examples. When teaching regression, I use data from a published psychology study. When teaching analysis of variance, I use data from a plant breeding program or data from a business-related study. I feel that it is important to emphasize to students through examples that the techniques they learn in their statistics courses can and often are applied in their own fields.
My application of these four key components in my teaching has proven effective in providing a good learning experience for students. I consistently received positive teaching reviews during my time at the University of Idaho, with many students commenting that they felt like they truly understood the material and had actually developed some enthusiasm for the field of statistics. I have also recently received a Graduate Teaching Assistant Excellence Award from the University of Calgary for my work as a TA in the fall of 2014. I plan to continue to adapt and modify my teaching strategies and techniques to further my goals as a teacher and to provide a comfortable, thorough, and enjoyable statistics education for students in both introductory courses and more advanced courses.
(Inspired by past experience, past observations, and the complaints of undergraduates from three—count ‘em, three—universities.)
- On the first day of class, go over the syllabus, ask if there are any questions, and then launch right into the material. Omit any form of road map for the course or any reasoning as to why everyone from bio majors to engineering majors to political science majors are required to take the course.
- Pick the driest, most boring textbook possible. Use it and it alone as supplemental material to your lecture notes.
- Assume that all students, regardless of actual background or major, are familiar with such thing as summation notation, factorials, slopes, and calculus. That sociology major sitting in the middle row who’s struggling simply because they don’t know that 5! = 5*4*3*2*1? That’s their problem, not yours.
- Make sure your class is all application, no theory. After all, why would people need to understand the reasoning behind the tests they’re using so long as they know how to do the tests?
- If you cannot implement the above method, try making sure your class is all theory and no application. After all, if you teach the theory really well, odds are the students will be able to derive the practical applications by themselves, right?
- Stick to the most boring examples you can think of, and make sure every example you use is coming from the same area of research. Do you have a background in business? Every example should be business-related and involve as many technical terms as you can throw in there. Same idea if your background is biology or psychology. That way, students can really see how statistics can be used in practically every field—as long as that field is yours.
- There are plenty of cool, funny, and downright fascinating examples where statistics are used in unique and exciting ways. Make sure you keep these engaging examples out of the classroom.
- If there is a topic that the majority of the class is struggling with, assume that it’s their own faults for not studying it well enough and press onward to new material. Breadth, not depth, right? Who cares if there’s a section people are struggling with as long as you cover every chapter in the textbook by the end of the semester.
- Offer only one explanation of each topic. All students learn the same, and thus why waste time trying to explain a concept in two or more different ways? If there is confusion over your explanation as to why we use an ANOVA versus a bunch of paired t-tests for comparing 3+ means, it’s not your problem. Everyone should just be able to understand your explanation with no problem, so long as they’re applying themselves.
- Finally, lecture in the most unenthusiastic voice possible. After all, you’re talking about numbers, right? Numbers are obviously inherently boring and this boringness should be conveyed through your lecturing style. If students are willing to learn, they should be able to get past your droning voice at 8:30 in the morning. Those who fall asleep simply are slackers.
All of the above info must already be very obvious, because so many statistics teachers seem to glean their teaching techniques from at least one or two of the above points.
After all, if we’re not making statistics the most painful subject to learn, we’re not doing our jobs right.
So I taught my last class at the U of I (for now). I’m super freaking sad about it, too. I’d definitely stick around, but:
a) the department can’t give me a permanent lecturing position at this time
b) I’ve decided that teaching stats is pretty much the most perfect job for me (apart from working at Leibniz’ archives). In order to get a real chance at a more permanent position, I need to get a PhD in stats.
Hence, Calgary. So hopefully I’ll be teaching again (relatively) soon.
But since I’ve started working here in 2012, I figured I’ve taught about 550 students. Hopefully at least a few of them have decided that stats aren’t too bad after all.
Still sad, though.