Tag Archives: job

LET’S DO THE TEACH!

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?

Who knows.

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.

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Teachin’ Time! (sort of.)

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?

Preachin’ the Teachin’

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.

Saturday Solipsism

Ha.

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.)

Duuuuuuuuuude

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)

YAYZ

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.)

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I can’t believe I’m getting paid for this.

I’m so lucky to have a job that brings me happiness. I know it’s not a permanent one (unfortunately), but to be paid to do something that doesn’t even feel like work is freaking awesome.  The summer session of stats is over this Thursday. Now that I’ve (almost) finished teaching three sessions of intro stats, I think I’ve figured out the main reasons why I love this job so much.

The obvious one: I love statistics.
I think I kind of always have, I just didn’t know it. When I started college back in the stone age in 2006, I went into psychology not because I didn’t know what major to pick and that’s kind of the “default” one, but because I was actually interested in methods of quantifying intelligence. After I took the class I’m teaching now (STAT 251), I kind of changed my mind and became interested in psychological testing in general. Then it was recommended that I take MORE stats classes in order to solidify my chances to get into a psychometrics program…and, well, we all see where that’s led. I just really, really like stats.

I’m imparting knowledge.
This is a totally cliché reason, I know, but it’s a reason nonetheless. There’s something very satisfying about imparting knowledge to people. It’s like giving them power. I think it’s even more satisfying in the case of statistics because a lot of peoples’ visceral reaction to a stats class is either “god, this is going to be so BORING” or “god, this is going to be so HARD” or a combination of the two. I love showing (or at least trying to show) that stats can be both fun and fairly easy if you get a solid understanding of what you’re actually doing when you do stats.

It’s intro statistics…
Intro classes are broad as hell. A lot of time, in my opinion, they exist to kind of help “weed out” people from certain majors before getting more in depth with the history/materials of whatever the major is (or to put it in a less sinister-sounding phrasing: they’re “survey” classes used to give people a general sweeping idea of what the major entails before they fully engage in it).

STAT 251 is like that too, but there’s actually kind of an extra bonus to that. Since it’s a broad intro class and we have to cover a lot of stuff, we really can only touch on the stuff that’s really, really important. That really, really important stuff is actually the really, really useful stuff—it’s the statistics that non-statisticians use. It’s the stuff that biologists use. It’s the stuff that advertisers use. It’s the stuff that a person working for a big business uses. It’s “hey, you only gonna take one stats class ever? Here’s the stuff that will get you through most of your life.” Because you WILL use something from this class at LEAST once. I’m definitely not saying that more “complex” stats aren’t important…I’m just saying that this is the stuff that even those people who stand at the entrance of a stats class with their fingers in an “X” and yelling “No…nooooooooo!” will probably use. And that’s cool.

…and almost everyone has to take it.
You really get a mix of ability/familiarity with the material in an intro class, I think. In the case of stats, some people are coming right out of high school and have taken AP stats. Others have never heard the term “median.” Both this semester and last semester I had students come up to me who said something to the effect of, “I was terrified to take stats because I knew nothing about it and people always said it was hard (or “I hated AP Stats!). But this class was actually really cool and I’ll definitely be using this stuff in [insert major here].” Seriously. I think one person said they even want to go for a stats minor. That produces so much freaking glee you don’t even know, and that’s actually probably the biggest reason why I like teaching intro so much: you get to expose people to stuff they’ve never seen, and in doing so, there’s always the chance that you’ll spark an interest or fascination (Tests and Measurements did that for me, holy hell). Every time a student tells me they like the material or that they really got something out of the class I just want to jump up and down and hug them. But I don’t. Because then I would get fired for being inappropriate.

It’s fun.
I have yet to dread going to work. Even dragging my unwilling body out of bed at 6 AM, my mind’s like, “ooh, get up you lazy fool! Today you get to teach them REGRESSION!” I think that’s the reason, too, why I don’t exhibit any of my usual public speaking anxiety when I’m teaching: I just love stats and I love talking about stats and it’s a really casual thing for me rather than being something I have to prepare for or rehearse 4,000 times. Like…I would teach for free simply because it makes me so freaking happy (but don’t tell anyone that, I need money to keep going to school, haha).

END!

A post! ApostapostapostapostaPOST!

TODAY WAS A GOOD DAY.

FIRST: my mom got a job, my mom got a job!! Here at the U of I! Now she can leave the insanity of Tucson and come back to the place she calls home. SUPER HAPPY ABOUT THAT.

SECOND: I got a job, too! In addition to teaching in the second half of summer, I’ll be working as a data analyst for the College of Ag from May through July. Now I can finally get some real experience with real data (and lots of it!).

Better brush up on my SAS.

WOOHA!

Is a Profound Catholic Man Considered a “Deep Friar?”

Hello, fellows!

So I’m almost done grading all the assignments/tests for my stats class.

I think things went pretty well this semester, especially considering that I had about five days’ notice that I’d be teaching AT ALL. I think the best part of all of this, though, is the fact that I overcame my fear of public speaking. Seriously, when I had to present my thesis, which was just in front of four people, I really really had to practice a lot beforehand and, once the day came, I had to concentrate to not throw up/not stutter/not run off in fear.

After the first two or three lectures this semester, however, it was the most natural thing ever for me. I love the fact that my passion for stats and my passion for teaching others how to do stats totally eclipsed my fear of public speaking.

That’s a good feeling, my friends.

One thing I think should change, though, is that I really think that STAT 251 needs to be treated like a science class. That is, I think it needs to be bumped up to 4 credits and given a lab. Statistics is like the hard sciences in that it really needs to be applied to be learned. I think a lab—a day where the whole class would go to a computer lab and given an assignment or something to do using SPSS or Minitab or whatnot—would really benefit students.

That’s kind of what PSYC 218 is, actually, but obviously a lot of students who aren’t in psychology won’t be taking 218.

Just a thought. I know I have no control over that, but that’s what I’d change about this class.

Now I’m going to go screw around. BECAUSE I CAN!

Sigh. :)

Today was a very good day, due in no small part to two very enthusiastic stats students. I spent a total of about 6 hours between them talking about stats and HOW FREAKING COOL all these analyses get once you actually apply them to stuff you’re interested in.

 

That is all I feel like saying. Today was a very good day.

So tell me something:

Why in the hell was I not trained with these awesome videos?

I never knew the hidden sexual potential of that job.

I have such an urge to remix this.

Oh Wendy’s. You have achieved a whole new level of cool.

I’m a STATS MAN!

WOO THEY WANT ME BACK!

I’m going to get to teach again next semester!

I might get the TH class or I might get one of the MWF classes, but I don’t know yet. But YAY!

Now comes the incredibly difficult task of NOT creating a schedule for next semester until I know when I’m teaching.

Gonna go spaz now.

I freaking love my job.

LOVELOVELOVELOVELOVE.
Love x 10 billion.

I can’t believe how lucky I was to get this job. I guess the exceedingly horrible luck I had in Vancouver is finally balancing out.

It’s like I’m not even working, dudes. Each time I get a paycheck I’m like “WOAH FREE MONEY!”

I know everyone’s probably sick of me blah-blahing about my job, but hey. I finally have something to blah-blah about. So I’m going to enjoy it.

Guys, can I spaz for a minute?

It totally hit me this afternoon.

I am teaching statistics.

Me.

I am freaking teaching statistics.

At a university.

I am responsible for the beginning statistical education of 137 college students.

The people in charge think I’m competent enough to teach my own section of statistics.

Teaching.

Teaching statistics.

Teaching statistics at a university.

Me.

Holy fslfjsgaahsdfjghlaweroaw.

I’m an educator!

Today I taught my first university class.

It was awesome.

I think it’ll take awhile for it to sink in that I’m actually independently responsible for a class of 130+ students. But I think it’s going to be the most fantastic time ever.

Oh, and I also had classes today!

  • I’m taking SAS Programming, which will end up being super helpful because it prepares us for the SAS certification exam, which would put us way ahead in the job market because pretty much every company that does analyses uses SAS and wants people who know how to use SAS.
  • And…CONCERT BAND! I haven’t played my clarinet in like three years, so the first few rehearsals will be interesting. BUT YAY MUSIC AGAIN FINALLY!

I’m done.

WISSJDFSLHGHDKSHR

I’m so totally in flail mode right now. Happy flail mode.

I have a grad student working for me (because there’s like 150 students in my section). That’s beyond creepy to me.

AND, while I was making the syllabus this afternoon, I realized that the grad student working for me is also the TA for the SAS programming class I’m taking. I have that class later in the day on Tuesday/Thursday after I lecture. That’s hilarious.

Edit: dude. I just realized…I GET TO TEACH THEM R.

Edit 2: my TA is the Joe Vandal twin that got jellyfish-mauled in Hawaii when we all went down there for the game.

[insert more flailing]

GUYS GUYS GUYS!

I just got a job as a lecturer for the U of I statistics department. I’ll be teaching the one Tuesday/Thursday section of STAT 251.

HOW FREAKING COOL IS THAT?!

This is what I’ve wanted to do for a long time now: teach statistics!

I’m beyond excited. I’m beyond nervous. It’s a class of 137 students. I have to create the syllabus/homework/exams, figure out how much material I can fit in 75-minute sections of time, practice so that my voice doesn’t waiver like a freak, and I’ve got exactly a week to do it all.

BUT STILL, HOW FREAKING COOL IS THAT?!

[deleted section of me mashing the keyboard in excitement]

 

Edit: aw, yeah.

Adventures in R: Decisions, Decisions, Decisions!

Hokay. So. Here’s the earth. Here’s what’s going down at work:

My boss put me in charge of writing up all these instructions for the ten or so AT programs that are used at Pima Community College. These programs make text/images/etc. on the computer accessible for students who need something to help them learn, be that need from a physical disability (low-vision, blindness, etc.), a learning disability, or some other such thing. These programs can do a lot of things: read text aloud on the computer, enhance displayed text so that it’s easier to read (magnification, color change, background color change, etc.), highlight individual words as their read…things like that.

Cool, huh?

It turns out, though, that of the twelve or so general features we utilize from these programs, each of the programs is able to different things. For example, a person using FS Reader will only able to change voice speed and magnify the screen, whereas a person using Kurzweil 1000 will pretty much be able to alter the visual and spoken text any way they wish.

The problem with this program diversity is that it makes it fairly difficult to help students choose which program is best for them—especially considering you have to keep track of ten different programs, some of which change with each software update.

So one of my tasks at work has been to make some sort of visualization that shows which programs have which features.

Which has turned out to be a more arduous task than first thought. Mainly because it’s difficult to include both the “reading features” (those related to the text-to-speech) and the “visualization features” (those related to how the text can be manipulated on screen).

The most “uncomplicated” visual I could do for the reading features was this pyramid thingy (even a regular flowchart looked horrible).

You don’t want to see the pictures for the visualization features. They’re horrible. There are twelve main features and no two programs have the same features. As you can probably guess, the pyramid looks like somebody vomited words everywhere and the flowchart looks…well, even worse.

My boss finally told me not to worry about a visualization for the features just yet, but I wanted to see if there was a way that I (with my lack of programming skills in everything but R) could make some sort of automatic “decision maker” that would spit out the appropriate program(s) if a user input what features they required.

So what did I, with my lack of programming skills in everything but R, use to do this?

R!

It took like four days, too. Either I’m a moron and over-thought this waaaay too much or it really is this complicated to implement in R.

Either way, here we go:

I wanted to make it so that someone wanting to figure out what AT program they needed could just input a binary YES/NO for each of the four reading options, copy this info in to R, and automatically get an output telling them what they could use. So I made this little Excel thing (click to enlarge, as always).

Next, I had to figure out a way to program my R function so that it would spit out the appropriate program for the given input (e.g., if I needed all four reading features, it would only show me Adobe Reader, EasyReader, Kurzweil and MAGic). This part wasn’t that big of a deal. But when I wanted to also make it possible for the function to spit out the appropriate program for ALL levels of customization (like if I wanted just voice speed to be editable, the function would give me ALL programs as options, not just FS Reader), things got a bit more difficult.

So I finally just made a code that included what to output for all possible combinations of the four reading features.

tellme <- function(x,print=TRUE) 
{ A=sum(x[,1])==1 
B=sum(x[,2])==1 
C=sum(x[,3])==1 
D=sum(x[,4])==1 
E=(sum(x[,1])==1)&&(sum(x[,2])==1) 
F=(sum(x[,1])==1)&&(sum(x[,3])==1) 
G=(sum(x[,1])==1)&&(sum(x[,4])==1) 
H=(sum(x[,2])==1)&&(sum(x[,3])==1) 
I=(sum(x[,2])==1)&&(sum(x[,4])==1) 
J=(sum(x[,1])==1)&&(sum(x[,2])==1)&&(sum(x[,3])==1) 
K=(sum(x[,1])==1)&&(sum(x[,2])==1)&&(sum(x[,4])==1) 
L=(sum(x[,1])==1)&&(sum(x[,3])==1)&&(sum(x[,4])==1) 
M=(sum(x[,2])==1)&&(sum(x[,3])==1)&&(sum(x[,4])==1) 
N=(sum(x[,1])==1)&&(sum(x[,2])==1)&&(sum(x[,3])==1)
&&(sum(x[,4])==1) 
O=(sum(x[,3])==1)&&(sum(x[,4])==1)
if (A==TRUE)            
{FSReader="YES"}     
 else if (A==FALSE)            
{FSReader="NO"}
if (A==TRUE|B==TRUE|E==TRUE)                 
{NaturalReader="YES"}            
else if (C==TRUE|D==TRUE|F==TRUE|G==TRUE|H==TRUE|                     
I==TRUE|J==TRUE|K==TRUE|L==TRUE|M==TRUE|N==TRUE)           
 {NaturalReader="NO"}
if (A==TRUE|B==TRUE|C==TRUE|E==TRUE|F==TRUE|H==TRUE)            
{WYNN="YES"}            
else if (D==TRUE|G==TRUE|I==TRUE|J==TRUE|K==TRUE|L==TRUE|
M==TRUE|N==TRUE)            
{WYNN="NO"}
if (A==TRUE|B==TRUE|C==TRUE|D==TRUE|E==TRUE|F==TRUE|
G==TRUE|H==TRUE|I==TRUE|J==TRUE|K==TRUE|L==TRUE|
M==TRUE|N==TRUE)            
{AdobeReader="YES"           
 EasyReader="YES"            
Kurzweil1000="YES"            
MAGic="YES"}            
else if (C==TRUE|D==TRUE|F==TRUE|G==TRUE|H==TRUE|I==TRUE|
J==TRUE|K==TRUE|L==TRUE|M==TRUE|N==TRUE)          
{AdobeReader="NO"            
EasyReader="NO"            
Kurzweil1000="NO"            
MAGic="NO"}
result <- rbind(FSReader, NaturalReader, WYNN, AdobeReader,
EasyReader, Kurzweil1000, MAGic)
return(result)
}

It’s still way too complicated for my taste; I was going to do it with the visualization features, but there are eight of those features and considering I had to do 16 different combinations just for the four reading features, I figured I’d hold off on the visualization features until I get a more streamlined code going for this project.

But check this noise:

Let’s say I was a student who needed to figure out what program(s) I could use based on my needs. I go to this little Excel check box thingy I made and select Voice Speed, Voice Profile, and Volume Control as the three things I need to be able to change.

I copy this info onto the clipboard and run the code in R. This is what it tells me:

FSReader      "NO" 
NaturalReader "NO" 
WYNN          "YES" 
AdobeReader   "YES" 
EasyReader    "YES" 
Kurzweil1000  "YES" 
MAGic         "YES"

Cool, huh?

What if I only needed to be able to change the Voice Profile?

FSReader      "NO" 
NaturalReader "YES" 
WYNN          "YES" 
AdobeReader   "YES" 
EasyReader    "YES" 
Kurzweil1000  "YES" 
MAGic         "YES"

Yay!

Next mission:  to make it better!

Working for the weekend? Not yet, but soon.

I have a job! Well, I WILL have a job in a few weeks (have to wait for the January Council of Counsilness to meet to get my approval). I need to start acquiring money ‘cause once I get my brain under control again, I totally want to go back to school.

It’s not a stats-related job, but it pays well, I can pretty much decide when during the day/week I want to work, and it will afford me the flexibility to take classes once the brain issues get resolved (which they BETTER) and I can concentrate.

And it’s a job that will directly help people, so that’s a good thing. I might also get the opportunity to learn Braille and/or ASL.

In the meantime, I must be frugal (even though I may have ~$3,000 in my Canadian account), try to remain relatively sane, and not have another day like Sunday.

Yeah. Right.