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 moved offices today! I got “promoted” to the fifth floor where all the professors/post docs are. I met the lady who will be taking over my desk in my old office (she’s from Russia and is in the theoretical math area) while I was cleaning out all my crap. She’s super nice and said she wants to come to my lectures so she can refresh her stats, haha.
Here’s a pic of my new office:
I’m sharing it with two post-docs, but one of them isn’t teaching this semester and spends most of his time at Foothills, so he probably won’t be around. The other teaches a math class. Calculus, maybe? I can’t remember.
Anyway, the windows are west-facing, so we’ll get the hot afternoon sun, but there’s no way this office can be hotter than my previous one. That thing was a furnace.
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.
So I picked up all my TA evaluations a few days ago because the department gets rid of them once you’ve graduated and I wanted to make sure I picked them up before I forgot to do so.
Anyway, today I feel like useless garbage (I mean, even more so than normal), so I decided to get a little ego boost from the reviews. These are my favorite comments.
- “Best TA I’ve had”
- “I feel like she can teach better than prof”
- “I have nothing but amazing things to say about her”
- “She could easily be a professor”
- “It is evident that she cares about students’ success”
- “Claudia has helped and taught me more than any of my other teachers”
- “Very friendly and welcoming and is good at creating a fun environment for learning”
- “Goes through questions and tells you information that not even the prof mentions”
- “She is very, very good (better than my prof)”
- “Should be offered a job should the need arise”
- “One of the best TAs I’ve had over my 4 years”
- “I found her lab sessions and office hours were highly beneficial to my learning (even better than the lectures)”
- “She is a very good teacher, gifted at it even”
- “Learned better from her labs than lectures”
- “She is the bomb”
Hello, faithful readers!
So I just checked my mailbox at school and I found in it a letter from the dean of the Faculty of Science. Turns out, I won the Fred A. McKinnon Award for being “the best Graduate Student TA in the Department of Mathematics and Statistics.”
I get to go to the Faculty of Science awards of excellence reception on the 15th, which is pretty freaking cool.
Now if I can only get a teaching job…
I got another TA award! Yay! I got one for fall 2014; this one is for fall 2015 (they just announced it, though, haha).
I think the reason I didn’t get one in Winter 2015 was because I had only like 8 people in my lab the day I ended up handing out the little review forms, and I don’t think it was a big enough sample for them to even count it (their reasoning is that if there are too few people filling it out, those people can be more easily identified, and the survey is supposed to be anonymous).
Why THE SHIT is 7 PM – 9 PM a valid time slot for a final exam? And why is it on the second-to-last day of finals week?
Oh well. Better to invigilate a final exam than take one, I guess.
Edit: So Scott and I decided to just stay on campus after the final and grade his section of STAT 217 tests. We were there until about midnight, haha. But at least they’re graded now so we won’t have to do them after we grade all the STAT 213 tests tomorrow.
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?
Dudes, check it:
“To determine the best and worst graduate degrees for jobs, Fortune consulted the careers site, PayScale. The site considered the full-range of graduate degrees, including Ph.D.s, master’s degrees, and law degrees.”
The ranking is based upon three factors: long-term outlook for job growth, median salaries at mid-career, and job satisfaction scores.
Guess what was ranked highest?
Median Salary: $131,700
Projected Growth in Jobs by 2022: 23.7%
Highly Satisfied: 71%
Low Stress: 67%
An MS in stats made the list, too!
Median Salary: ($109,700
Projected Growth in Jobs by 2022: 18.2%
Highly Satisfied: 80%
Low Stress: 51%
I know it’s just one ranking, but it’s pretty cool that the thing that I love doing has the potential to lead to jobs that are high-paying and satisfying.
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.
Well, sort of.
Today was the first day of labs, which for me meant running two hour-long labs for the intro stats class here. While today was basically teaching them how to open/use Minitab and how to access their online assignments, in future labs will involve going over concepts taught in class and/or helping them prepare for the midterms.
Not the same as teaching my own class, but it’ll do. Explaining stats is like my favorite thing to do anyway.
SORRY I’M SO BORING HAVE A PICTURE OF THE CALGARY TOWER INSTEAD:
So today I worked a one-day only 10 hour job checking people into The Grove.
It was supposedly supposed to be their busiest day of the year, but I think I literally checked in 12 people over the whole 10-hour period.
Luckily, though, my station happened to be in the bar/lounge thingy, so I spent most of the day watching the Little League World Series. Canada was playing Venezuela. Canada…did not do well.
Interesting game, though.
(YES, I kind of like baseball. Blame my mom, haha.)
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.
I get to teach in the summer!!
And what’s better: it’s not the 7:30 AM section!!! It’s the totally reasonable and much more Claudia-friendly 11:30 AM section, which runs for two hours on M/T/W/Th and starts right after spring semester is done.
I still don’t have any concrete plans past that point—which SUCKS and I hate it—but I’m glad that I at least get to teach in the summer.
I think my favorite part of teaching is helping the students who really struggle with math/stats.
There’s a huge range of familiarity and comfort with math in 251. That’s likely because you only need two years of high school algebra to take it (or, failing that, MATH 108). The stuff we start with isn’t too conceptually hard or even computationally hard—the mean, median, standard deviation, etc. However, the notation for these calculations seems to be what trips some people up.
Example: I’m sure we’re all familiar with the mean and how it’s calculated. Suppose we had a dataset with values 3, 5, 2, 6, and 7. To find the mean, we add up all the values and then divide by the total number of values, which in this case is 5.
But here’s the formula to do that:
If you’re not familiar with summation notation, this calculation, as simple as it is, might look really intimidating, right? And I’d guess that students who have taken MATH 108 as their highest math class at the U of I haven’t been exposed to summation notation. I know we never saw it in MATH 143 (which is a horrible class in general, but I won’t go into that). Personally, I don’t think it was ever explicitly explained until I took MATH 176 (Discrete Math).
Unfortunately, I’ve heard from a LOT of students who are re-taking STAT 251 or who had taken stats in high school that a lot of the “basic” notation we use right at the beginning of class was never really explained. It was just knowledge that they were assumed to already know, and so was glossed over rather quickly.
That really bothers me.
That’s why my favorite part of teaching is actually helping to make sense of these “everybody should already know this” concepts…these concepts that, in actuality, not everybody already knows. I’ve had a lot of students who have taken stats in the past say that no one has ever explained those things to them and that they really appreciated a basic “here’s what this capital sigma means and how to calculate stuff with it” and other such explanations.
And that makes me happy. Not happy enough to alleviate my anger over the lack of standardization across all sections of STAT 251 at UI, but happy.
I was talking to some dude in the Commons today while I was waiting for English to start. We were blah-blahing about school and stuff and he asked me if I was working and going to school at the same time and I automatically said “no.”
I freaking forgot I was employed. That’s how much I love my job: I keep forgetting that it’s a job. I’m getting paid $23 an hour to talk about what I love.
THAT’S SO FREAKING AWESOME I CAN HARDLY STAND IT.
(Sorry, I’ll stop now)
Not only do they want me to lecture next spring, but they want me to do TWO sections! WOOT.
Does that count as a promotion?
(I say yes.)