Dr Rachel Fewster - Tertiary Teaching Excellence Teaching Profile

Senior Lecturer, Department of Statistics, The University of Auckland

Beginnings

Not many people start their careers intending to be statisticians, and I’m no exception. My statistical career began when I was an undergraduate in Cambridge, studying mathematics. None studied statistics by choice: it was a compulsory component of our maths degree, and one regarded with disdain by the student body. I remember one time when the lecturer said, ‘We’re not going to prove this result rigorously’, and a posse of students staged a walk-out. For me, though, the subject began to gain appeal. Whatever the walk-out students thought, we were seeing for the first time deep mathematical development that also had concrete application in the real world. I realised that this was my ticket to a career that would combine my chosen subject of mathematics with my desire to be useful.

From Cambridge I went to St Andrews in Scotland, to start a PhD in statistics. By the end of my PhD, the most striking thing I had learnt was how little I knew. My training was in maths and theory, and I knew next to nothing about statistics in the real world. The idea of me teaching applied statistics to classes of 300 first-year students was downright comical. I looked for research jobs instead, and in 1999 joined The University of Auckland as a postdoctoral fellow, not realising that teaching applied statistics to classes of 300 first-year students was exactly what my new job would entail. Thus began my teaching career, on the basis of a lucky misunderstanding.

Learning to teach

The Stats 101 team comprised about 10 lecturers and three thousand students. Being propelled into this environment for my first teaching experience was one of the luckiest breaks of my career. The teaching team was inclusive, supportive, and ultraorganised, and it created constant on-the-job mentorship. The team was honoured by a National Tertiary Teaching Excellence Award in 2003, and I was fortunate enough to walk right into it. Meanwhile, as I scrambled to learn the material often only a few days before the students, I had no illusions of grandeur or aloofness. This foray into applied statistics was a joint undertaking. Educational axioms, such as valuing the intellectual input of the audience and establishing a sound rapport within the class, were matters of necessity rather than philosophy. It’s striking how many excellent teachers feel that they started off on the back foot, and perhaps this is no coincidence. My interactions with students were formatively defined, and they haven’t changed since. There is no ‘them and us’: it’s all ‘us’. The most important lesson I learnt from the Stats 101 team was, however, something a little different.

Bringing the subject to the students

As a mathematical student, I had given scant thought to the job of the lecturer. I had certainly never perceived that I might be the object of anybody’s ‘teaching philosophy’! The key to good teaching was obvious: you gave out clear lecture notes, with clear headings – Theorem – Proof – Theorem – Proof. The only possible thing that could go wrong with a lecturer was if you couldn’t tell where their theorem stopped and their proof started. That was it.

When I looked at the lecturing materials of the Stats 101 team, however, theorems and proofs were conspicuously absent. Instead, there was motivation, insight, and example. Quietly horrified, I thought to myself that I’d soon fix that up. I started making extra lecture slides to show the class, dispensing with the motivation and showing the theory instead. The result was 300 blank faces. It finally dawned on me that what I was seeing in the Stats 101 lecture book was good teaching! The team was working with thousands of students who, by preference, would rather be elsewhere, and was convincing them that statistics was fun, interesting, and relevant to their lives. I’ve never looked back. Motivation, insight, and example form my overriding philosophy. As teachers, we have to bring the subject to the students, not the other way round. Our job is to gauge our audience and work out how best to present the material to resonate with them. Those protesting students all those years ago in Cambridge were making the same point: if you don’t teach us the way that we like, you’ll lose us. Without realising it, I myself had been drawn to statistics because the lecturer presented it as a subject that I already liked – mathematics.

Making statistics fun

These days, I mainly teach mathematical statistics at Stage 2 and 3 levels, to classes of about 80 students. One of the main challenges is diversity in student backgrounds and aptitudes, especially with respect to mathematical ability. I need to maintain the interest of the specialist mathematicians, while simultaneously engaging students who don’t share an interest in theory for its own sake. Somehow, I need to present the material so that all of these students think that they are studying the course the way they like it. This is tricky when the class has lovers and haters of mathematics in equal measure.

Here are my guiding principles in trying to make the course fun and accessible for everyone:

• If people are enjoying themselves, they will think of the material as enjoyable.
• The subject that interests everyone most is themselves.
• Focusing on conceptual understanding of the material enables a course to be intellectually challenging regardless of mathematical background.

I try to make the course enjoyable in many ways. Firstly, I learn all my students’ names. This takes time and effort, but is probably the easiest and most effective way to make everyone feel instantly valued. Most of my students grew up overseas, so I ask them about their home countries, and try to find out about special festivals for different cultural groups. I like surprising the students by announcing the appropriate greetings in class – and surprising myself, when they understand my amateur pronunciations!

I try to make my coursebooks look and feel attractive, peppering them with cartoons and comical pictures – hoping that students will enjoy opening their coursebooks and be curious about the material behind the pictures. I aim to pick examples that will intrigue and be infectious: the sort of thing students will tell their friends about outside class. Do plants grow better when you play them heavy metal music? Are vegetarian women more likely to have daughters? The scientific literature abounds with quirky or surprising studies, and using these to illustrate statistical concepts makes the material fun and memorable.

It’s a safe bet that everyone loves hearing about themselves, so I’m an ardent reader of popular psychology books as a source of ideas to illustrate statistical concepts. I like to pick up ideas for experiments that I can do with the class, creating an atmosphere of fun by pitting myself against the students. Can you tell which of these people is lying? Can you fake election results well enough to fool me? Some experiments are more elaborate, for example showing the class videos to ‘clear our minds’ before a stats quiz. It turns out that they perform consistently better in the quiz when shown videos of gifted children than they do when shown videos of soccer thugs!

The environment of learning is crucial to success. If our students are weak at maths, they need to practice. But this is the Internet generation – they won’t be enthralled at working endless exercises from some musty library book. We have to create an environment in which the exercises become enjoyable. With the help of my department’s website expert and colleagues, I developed an online Maths practice system where students can do practice exercises while interacting with listen-and-watch movie snippets. The unusual environment makes it fresh and appealing. Students know that they can get 20 minutes of practice – as social as a session on Facebook – and emerge with the skills needed to tackle the current assignment.

Last words

My courses follow a very traditional model of lectures, assignments, and exams. I don’t do anything very much out of the ordinary. My excellent colleagues showed me the potential of the traditional methods. My inspiring students showed me the rewards. Given an interesting problem and a few token marks, students will explore to great depths and share their spirit of discovery. If we just go to the trouble of learning their names in class, they will reward us for years to come with their stories of success and adventure. Pursuit of knowledge and understanding is a wonderful way to unite cultures from all over the world, and my daily lecture theatre is an amazing opportunity for intellectual and cultural exchange. It was a happy day indeed when I picked the wrong job and found myself teaching applied statistics to 300 first-year students.

Peer and Student Comments

“I raised many questions and realized how willing Rachel was to step beyond her responsibility as a lecturer and just teach. Often we strayed from the theoretical course material and explored real world applications. I was being schooled in the subtleties and limitations of statistics, all because of Rachel’s willingness to assist tirelessly. Her true gift is beyond teaching; she empowers her students to learn for themselves.”
Manav Jaura, BSc student, 2008

“Rachel has an unparalleled ability to transform potentially dry and mundane material into interesting and real examples, in a unique and memorable way. We left her classes not only with a firm understanding of what we had been taught, but also intrigued by the topic and looking forward to finding out more in the next lesson.”
Robyn Scott, BSc student, 2001 — 2003

“Our entire class was amazed at how Rachel made theoretical statistics approachable and engaging to all of us.”
Dr James Russell, BSc student, 2002; PhD student 2003 — 2007

“Rachel is a truly awesome lecturer – really enthusiastic – the love of the subject in every single lecture.”
Anonymous student feedback, 2005

“I have also had the opportunity to observe Rachel lecture to a Stage II class. I have never seen anyone present theoretical concepts so concisely and clearly. In a few brief minutes, with a teaching prop consisting of a bread roll and a drinking straw she was able to connect with her audience and successfully convey the fundamentals of the arcane multivariate technique of principal component analysis.”
Matt Regan, co-leader of the Introductory Statistics Team which won a National Tertiary Teaching Excellence Award in 2003.

“Her novel assignments, year after year, continue to astonish me with their inventiveness, and always test the students’ ability to both do the mathematics, and think critically about building models.”
Dr Ilze Ziedins, Senior Lecturer in Statistics