Teaching Statistics After Apartheid | Stats + Stories Episode 161

Delia North is the Dean and Head of the School of Mathematics, Statistics and Computer Science at University of KwaZulu Natal. She has over 25 years’ experience in the teaching and design of Statistics curricula at university. Her passion for teaching Statistics has resulted in her becoming a leading figure in South African Statistics Education circles, evidenced by being Theme Chair, Topic Chair, Session Organizer and Guest Speaker at various international conferences on Statistics Education. She is a member of the South African Statistical Association (SASA) executive committee, chairs the SASA Education Committee and is on a Council member of the International Statistical Association.

Episode Description

Educators are constantly rethinking the way they teach their subjects. Working to find the right mix of history, context, and subject specifics to help students understand and the importance of what they’re learning. Statistics is no different, stats professors and teachers continually looking for the best way to help their students connect to the subject. It can be a complicated process becoming even more fraught during moments of political upheaval or revolutionary change. That's the focus of this episode of stats and stories with guest Delia North.

+Full Transcript

Rosemary Pennington: Educators are constantly rethinking the way they teach their subjects. Working to find the right mix of history, context, and subject specifics to help students understand the importance of what they’re learning. Statistics is no different with stats professors and teachers continually looking for the best way to help their students connect to the subject. It can be a complicated process becoming even more fraught during moments of political upheaval or revolutionary change. That’s the focus of this episode of Stats and Stories where we explore the statistics behind the stories and the stories behind the statistics. I’m Rosemary Pennington. Stats and Stories is a production of Miami University’s Departments of Statistics and Media, Journalism and Film, as well as the American Statistical Association. Joining me is regular panelist John Bailer, Chair of Miami’s Statistics Department. Richard Campbell former chair of Media, Journalism, and Film is away. Our guest today is Delia North. North is Dean and Head of the School of Mathematics, Statistics, and Computer Science at the University of KwaZulu Natal or UKZN. She’s been with the school since 2004 when she was appointed Head of Statistics. During her time there she’s worked to build capacity of statistics at the Institution as well as nationally in her role as chair of the South African Statistical Association Education Committee. North began her teaching career during Apartheid in South Africa which she says shaped the way she thinks about how statistics should be taught. Delia thank you so much for being here today.

Delia North: Thank you very much for inviting me. It’s indeed a great honor and I look forward to our conversation.

Pennington: Just to get us started I was wondering if you could talk about what that experience was like teaching during Apartheid, and you have sort of said it sort of helped you understand there was an urgent need to change the way statistics should be taught, so maybe you could talk through some of that for us?

North: Thank you. My training was primarily as a theoretical statistician. I liked mathematics at school, and I went to University to study mathematics and computer science, it was very new in 1977. When I got to University all students doing computer science were forced to do statistics. But statistics was only taught in the second semester because you needed a vast amount of calculus from the first semester to be able to understand it. So, I started statistics in semester two and immediately enjoyed it. As we progressed through the years of undergraduate had took statistics courses, every single one that I could, and I found that I was enjoying it much more than computer science for example, and eventually left computer science. And I majored in mathematics and what was called mathematical statistics. And it really was mathematical statistics. The University had a single large computer on campus which took an entire floor of a building called the Univac and you had to walk for about 15 minutes to get to the Univac and that’s what made me drop computer science actually and end up doing statistics because I thought it was a big waste of time to do computer science and I enjoyed statistics but all I needed was my calculator. I mean we never got to use the Univac if you were doing statistics. So I went on to do a Master’s and a Ph. D. in measured theoretic probability very mathematical I was good at it, I enjoyed it and I felt I’d made the decision to be an academic statistician where I would teach mathematical statistics but primarily theoretical probability; I loved it. Just after that, I got married I stayed home for eight years when I had three little boys and when I came back to my shock and horror, everything had changed. Univac was gone, everybody had PCs and the world was different. The academic world was different, but also Apartheid had ended just at the time and I was not teaching at what called historically disadvantaged institution and I was to teach many many students that had not had mathematics training at school. I don’t know if you know but during Apartheid the African schools were not taught mathematics. So, I had many students doing certain schools in statistics who had not been trained in mathematics. So, it was a whole new problem and all I knew was how to teach mathematical statistics well so suddenly I would lie awake really being concerned about this thing about how I could do this. It was really a worry for me, and then I knew about the South African Statistics Association, so I tried my own things. Training the curriculum a little bit too- even though the curriculum was in a mathematical way I knew I couldn’t teach it like that and I was trying to think of ways to do it so I joined the South African Statistics Association, particularly the education committee and I got really involved, and I did what I could locally but there wasn’t a lot of knowledge about how to do it better locally and we had heard about the RASE and I was on the education committee six international conferences on teaching statistics and I became the local chair or the six which was held in Cape Town South Africa and suddenly I was thrown into a whole new world. I got to meet all these people because I was chairing the local organizing committee and it was wonderful.

John Bailer: One thing I heard you just describe as part of when you were reentering into this workforce was in essence that you found yourself encountering students in this post-apartheid context where they didn’t have that kind of mathematical foundations, so how did they know that they would even be interested in statistics? And how did you- what are some of the things that you did in trying to connect to them and help them engage in the discipline?

North: What I found is that most of the students that I’m talking about that didn’t have a strong mathematical background they wouldn’t be in the program to be a statistician. They would generally be doing statistics as a service course. In other words, a one module statistics course to become a biologist. Well, one – yeah they were generally not science students. In fact, the students that chose to do statistics would have gone to some of the schools where mathematics was actually taught. Some private schools taught people of all races. Mathematics and then of course the white and Indian communities with the Universities open to all races. This was formerly a historically black university or a historically disadvantaged institution but most of the students were in the category that hadn’t done mathematics at school and therefore would be doing it as a service course where we would teach one semester of statistics to a student that might not fully understand the concept of percentages and proportions. It really was very very interesting. And but the service course curriculum had been designed years before and it was in fact for example proving based theorem in your one-semester service course. I mean it just wasn’t attainable and I couldn’t just change. So what I did, I put something in called hot seat which I called it hot seat because the seat is hot you can’t sit there for the day but you could book a private lesson with one of the statistics students and I got funding so that when you get some of the actual third-year honors, fourth-year statistics students to help the service course students because what I also found that was interesting I would stay for extended periods at our tutorial of noon where students could one on one ask questions but they would not ask a single question because they were embarrassed that their English wasn’t- we have eleven official languages and the students would not ask a question but the minute I get to my office at half-past four or five o’clock I’d have a row that want to come into the privacy of my office and ask me a question. So then I had the idea of having what I called a hot seat which just means you could book a private lesson like you book a squash court and you could have half an hour of one on one individual attention with the door closed, but it wasn’t enough.

Bailer: That sounds like a tremendous challenge to have eleven official languages. To think about trying to kind of encourage and manage in that context. Have you seen a growth in the number of students that are taking these kinds of service classes and statistics or in terms of the students that are in your school?

North: Very much so and what we’ve done over the years, what we’ve found very helpful is that we, for example, will get students of the different languages- say the local African students that are you know that was a long time ago, I’m not talking about 1994-95 when things changed but also from 2008 onwards in South Africa the education system at school level was identical, a new system came in in 2008 so for the past 12 years students coming into university have all had the same education. So now things are different but still, I find- and I’m glad you asked that language is a problem and that is why we have students of the different language groups maybe that are successful that could be because of what we call supplemental instruction leader and can be a tutor. We particularly don’t just take the best students in class but we try and spend the different types of students and that is how we handle particularly in the very large classes so that is something that we’ve found to be very effective.

Bailer: So, do you have all the instruction in a single language?

North: Yes. All the instruction is in English, although we have tutorial groups and we have what’s called code-switching they might discuss a problem in their language ad then we make groups and particularly in third year I found it interesting we have groups and I walk around the groups and the discussions can be in their home language but their presentations- yeah. And what I’ve found that I actually that I actually went to a talk on this once where they put cameras and watch people when they discuss a problem they like doing it in the home language, but when they do the problem it’s often- because it’s artificially- it’s not from the heart it’s more like the mathematics of how to solve it using which model, happily it’s done in English because that has been taught in English.

Bailer: Oh okay.

North: So, the discussion about what kind of problem it is, the general English what we would do in English, not when it gets to the mathematical modeling part happily everybody does it in English.

Pennington: You’re listening to Stats and Stories and today we’re talking with Delia North of University of KwaZulu Natal. Delia you’ve talked a bit about the sort of you know before this sort of this new educational regime was put in place in 2008 how the mathematical education was very uneven. And it sounds like sort of since 2008 there’s been some improvement, what other ways have you or your institution been involved in trying to increase maybe the representation of people from marginalized groups in the field of statistics, right? So, you talked about sort of this tutoring in the various languages, are there other things you’ve been doing to try to increase the inclusion of marginalized groups in this field in South Africa?

North: Yes, I’ve done that to what I’ve found to be extremely effective. Many years ago, I realized that the problem was often not just the students coming in from communities where maybe they were not at all taught at the same level, in other words, they had varying levels of preparation for University. The problem would continue if we couldn’t help the Inservice teachers. Because the curriculum changed. In 2008 everybody had this new curriculum but the pre-service teacherswould all get the new content and one particular day I was with this person that and I’d seen him and I just happened to be speaking to the statistics general and I didn’t know and I said don’t you work with stats South Africa and he said and it was just at the time when this was on my mind all the time how to teach Inservice teachers and I said to I said you know you’re pretty high up in stats South Africa and he said yeah, I’m the- are you supposed to ensure that the man in the street the citizen in South Africa can read your because I saw that in your mission and vision so how bout you start something- I’ve got some plans but I’ve got no money, how about you start something where we train Inservice teachers? And then we started talking and the next thing he made a program called Math’s for Stats, meaning the maths at school can help stats and he made me the Master Trainer. So, it’s a fun thing to do and then we had people that we had to train in every province and he took two teachers from every province virtually and eventually it was run through a program and I would fly up to Johannesburg and retrain the what was called the subject advisors and they would then, in turn, teach teachers, but it all was too diluted and too slow. So when we had in South Africa in 2009 I was asked to organize a teacher program because I then had got the name that nationally I was doing a lot of training and through South African Statistics Association I tried to get other universities and I realized that we could only do it on a large scale if many people were involved, people with knowledge and all wanted to do this, and then we had ISI in South Africa in 2009 I decided that I wanted it to be a lasting legacy and try and think of something that could make this big problem go away with other words how could I do it? And I realized I could only do it if I worked through the proper structures. So I involved Statistics of South Africa which by then had done a lot of training that they’d sponsored, that I had been involved with and also my university we were the University of KwaZulu Natal, we’d merged and I decided that- I spoke to my staff I was head of statistics at the time and I got almost everybody on board and I said decide which 300? If I just say- if I advertise, I’ll get the wealthy schools that have got bringing their people so I went to the department of education I said who are your 300 worst-performing schools in mathematics? You find the schools and I’ll go stats on Africa because I don’t have an admin to get hold of those schools because anywhere in my province- and our province is pretty big so I asked the stats south Africa to was on my side and he said they would do the admin and I said these are the schools, faxed them, every school must send a teacher and we had the most amazing program for five years and what was really fantastic is that the statistics department as a group would work with me on a Saturday morning and we’d run three parallel groups. We had the primary school, then we had the intermediate group, and then we had the senior group with other 10,11,12 and we’d work through the statistics part of the curriculum, and I learned so many lessons there. It only worked because no money exchanged hands. wanted to pay the teachers money and I said if you’d do that first of all somebody living close by will tell me they live in the north of my province I’m not going to police that. let’s tell the school’s here’s an opportunity and I will do it so well that they’ll be fighting to come back and I’ll do it very well the first week and I spent a lot of time and what I found was interesting. Teachers came a long way some of them told me that you’d get up at two o’clock in the morning because they don’t have cars they had to come on public transport to get there by eight. And they would just get them a pack of notes and by the end of it it was five cents away it only pays tens, and all fives would I give them a bound book with all their materials. And I would give them each little one to to the class and every week I’d give them a gift where everything was around fun activities to learn probabilities and I would give them the sheets and exercises and a lot of them were about rules of society and it was fun and the teachers got so excited they wanted to come back and then I would also do certain surveys to get certain information so we could do some modules and do some modeling on some attitudes, it was really a wonderful project and I found that if you gave the teachers a hot meal when they arrived and a hot meal at lunch and when I spoke to my staff afterwards after the first week so many said I’ll do it once to I’ll do it every week because it was such an eye opener for our staff and for us to see how desperate these teachers were and what they wanted was posters to make the classroom look pretty so I got sponsoring to make laminated posters and we’d give them big colorful posters with fun such activities on them and that just seemed to make such a difference that giving them little gifts not money and using the little bit of funding I could get to make their classrooms look pretty and they just absolutely loved it.

Bailer: You know what you’re doing is inspiring, what you have done is you’ve been a force to change the practice within your country and I just am really impressed I think that’s really cool so you know as you’ve been doing this what we see in our country and what we see around the world is a tremendous increase for statistics for data science for analytics you know just you name it basically in terms of thinking and solving problems with data that we can’t keep up you know universities can’t keep up that all sectors need this, businesses industry, government all throughout are just crying for graduates with the skills like you are helping your students develop and what you told us about is the pipe in terms of the things that you’ve done in terms of the Inservice for the people that are part of the pipeline that are coming into this. I also know about some of the things that you’ve done to attract young women to study statistics. Particularly things like the idea of the teas that you’ve held. So can you talk a little bit about what are the things that you’ve been doing to try to explicitly bring in. you’ve told us about the Inservice work with the teachers to help them prepare and attract and bring them in, what other things have you done that we might learn from?

North: I think what’s really important and what’s been of help to me in regard of trying to get more girls interested in statistics is actually when I’m teaching to look for the qualities that I would expect an academic statistician to have amongst my students- female students, because I need role models. And I’ve got three girls, in particular, I can mention right now but I’d better not mention their names that I noticed when they were second-year students and I would speak to them about possibly thinking about becoming an academic statistician because it’s a job with flexibility and it’s so rewarding and I would give them extra opportunities maybe in tutoring and then I would watch how they tutor, involve them in projects if we were doing a research project I would involve them in their third or fourth year so that they gain extra experience and what I found is those three young ladies are now young academic staff, full-time members of staff and are going to schools like when I did the women in analytics I never just wanted to be me speaking to young girls because I know teenagers don’t want to see somebody their mother or maybe even their grandmother’s age so I will speak to my girls about what I think would be a good idea but I don’t do it. I might give a short talk but they’re the main show and these three young ladies will then speak to the audience and I’ve also got Jennifer Priestly in from state university, she runs the Ph.D. program there because I think you need a wow factor and to be the high like Jennifer Priestly and then the three young girls talking and then mingling. We took a number of schools and said that they could choose two girls that they thought were outstanding and had potential and was interested in analytics but the teacher came with and I think it was important because those girls, I’m speaking to girls but I want the teacher to listen and the teacher must be female by the way, and she must listen and she must go away and inspire other girls and I’ve seen from the video of Jennifer’s talk and thanked them for coming a few months later and I think that was really important to sort of get the pipeline going and what really started was more I was thinking about how to help these girls but especially with the pandemic where the young people of course are helping us with the technology, these young female lecturers we’ve got are absolutely amazing and they’re helping all of us be more relevant and to be able to help us to keep up with the latest trends so I think it’s really important to have that type of example in particular we’ve got people of different races, young ladies that are awesome and are able to really be role models for the young ladies because we are concerned about the problem of young girls even thinking about statistics because what I’m thinking about one of our schools but we need much more. So recently and this may be adds to something you spoke of earlier on this is not only about girls but there’s a project I’m doing with one of the teachers that went to seven with me and we had this big competition and we had a group of teachers that were sponsored. They were winners in a competition that and they went to Brazil with me to with a group and we had a wonderful time. Now one of those teachers has continued with the idea of trying to bulk up statistics and he came to me and he thought of this wonderful project we’re just starting now where students at school from the township area which is really the areas where the less affluent local people stay, local African kids stay there. And they generally would not have opportunities and certainly, the teachers there would maybe not be able to teach statistics to the level that we would like so what they’ve been doing, they thought of this project where they have a poster competition. This is my school and next is this is my community. And the last one is this is my municipality have the whole area of Durban and wider Durban area, but they had not thought of using stats as a data. So we don’t do it with you I’ll partner it with you but only if the teachers on the projects get training because our group of academic statisticians were trained, we will give you posters and materials so not only the children are presenting but now we have classroom access to those- this is just an extra thing we obviously have a full program at university so we try always to train teachers and we’ve already got them into the lab, all the teachers got lessons on how to download the data so when it comes to this is my municipality this doesn’t mark a community in South Africa we’re down to a ward later so we’ve got the data because the plan was just to walk around and interview a few people and say this is my community. Well, you should do that, but you should benchmark it against what really is your community.

Pennington: Well Delia that is all the time we have for this episode of Stats and Stories, thank you so much for joining us today.

Bailer: Yes, thanks, Delia.

North: Yes, thank you, thank you for the interview.

Pennington: Stats and Stories is a partnership between Miami University’s Departments of Statistics and Media, Journalism and Film, and the American Statistical Association. You can follow us on Twitter, Apple Podcasts, or other places where you can find podcasts. If you’d like to share your thoughts on the program send your emails to statsandstories@miamioh.edu or check us out at statsandstories.net and be sure to listen for future editions of Stats and Stories, where we explore the statistics behind the stories and the stories behind the statistics.

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Teaching Better | Stats + Stories Episode 153

Dr. Ellen Yezierski is the Professor of Chemistry and Director of Teaching Excellence at Miami University. Yezierski became familiar with the challenges of actively engaging students in large classes while pursuing her Ph.D. in the Department of Chemistry and Biochemistry. She has worked to integrate her research on the particulate nature of matter and conceptual change to improve teaching in large lecture courses. Her research interests include inquiry instruction, teacher change, and the effects of high school teacher professional development on teachers and their students.

Episode Description

Recent COVID-forced move to online instruction for both K through 12 and higher-ed has come an intense discussion of best teaching practices in digital spaces. While the focus has been on teaching online, the conversation has foregrounded long-standing debates over pedagogy and practice in education. Understanding what works in the classroom is the focus of this episode of Stats and Stories with guest Ellen Yezierski.

+Timestamps

What is the Centre for Teach Excellence At Miami 1:35

What drew you into helping people teach better? 2:37

Have we gotten better? 4:10

How do people learn? 6:15

How do you define effectiveness? 7:40

What can be done about a fear of science? 11:10

How does learning change with more skill? 14:45

Online learning in the COVID-19 world 18:12

How to recruit good STEM teachers? 23:11

Building trust with students 25:40

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+Full Transcript

Rosemary Pennington: With the recent COVID-forced move to online instruction for both K through 12 and higher-ed has come an intense discussion of best teaching practices in digital spaces. While the focus has been on teaching online, the conversation has foregrounded long-standing debates over pedagogy and practice in education. Understanding what works in the classroom is the focus of this episode of Stats and Stories, where we explore the statistics behind the stories and the stories behind the statistics. I'm Rosemary Pennington. Stats and Stories is a production of Miami University's Departments of Statistics and Media, Journalism and Film, as well as the American Statistical Association. Joining me are regular panelists John Bailer, Chair of Miami Statistics Department and Richard Campbell, former Chair of Media, Journalism and Film. Our guest today is Ellen Yezerski. Yezerski is a professor of chemistry at Miami University and received her Ph.D. in Science Education before becoming a professor she spent six years as a high school chemistry teacher. At Miami, Yezerski has served as the Director for the Center of Teaching Excellence since 2018. Ellen, thank you so much for being here today.

Ellen Yezerski: Thanks, Rosemary. Glad to be here.

Pennington: Just to get us started, could you tell us a little bit about what The Center for Teaching Excellence does at Miami?

Yezerski: Sure, the Center for Teaching Excellence has been established for about over 40 years and our goal is to work side-by-side with colleagues to improve teaching, and we do that in a number of ways. We do it through programming, we do it through faculty learning communities, we sponsor the original Lilly Conference on College Teaching, but overall, the big themes would be supporting faculty and helping them learn, and then building communities- specifically communities that practice around effective teaching. And it's been a great run so far, and we have been very busy of late.

John Bailer: So, what drew you into wanting to be- to help people teach better? I mean, you know, it’s one thing that teacher discipline as a chemist and as someone who is trying to convey science and engage learners in science, but what took you to the sort of the next level of teaching the teachers?

Yezerski: Sure, well, I've spent my whole career thinking about learning and students learning more effectively, and I would say that when I first started in higher education my goal was to support pre-service teachers who are going to be high school chemistry teachers, and also I got into research on faculty development for high school teachers. And so, it was a natural kind of transition to move to that same space in higher education. And I think what happens is that we know that what happens in the classroom and what happens in learning is all driven by what the teachers do and the teachers' choices and their expertise and their sets of beliefs and ideas about learning, and so having an influence there, I think, is the kind of the nexus to improving student learning.

Richard Campbell: So Helen, like you, I started out as a high school teacher; high school English for five years. And also and this is just a more general question on teaching, I remember when I started my Ph.D. program I had already had experience as a teacher and that was not a problem for me, but I felt like teaching graduate students how to teach- we didn't do a very good job at that. And has that improved and is that something that you tackle? I think this is part of a kind of the larger issue of teaching in science as well.

Yezerski: You know, Richard, I would say that there are pockets all over the country in particular Ph.D. programs where they're focusing on how to support people in learning pedagogy. But we have to think about what a Ph.D. is. A Ph.D. is a research degree, right? And it is this opportunity for people to be taking a deep dive into uncovering some new disciplinary knowledge and it might not match, right, learning how to become a faculty member where teaching is a big part of your responsibility. And so, there's definitely a gap, but I'm not sure that it's necessarily the responsibility of the Ph.D. program to close that gap because of what the Ph.D. represents. That sounds like a cop-out but there seem to be other places, and particularly in my discipline, where professional organizations are saying all right, what can we do about the lack of readiness for people going into higher education to meet the demands, not just a research but also of teaching and service, being a good colleague and a leader in a really complex environment. You know, how can we support people to do that? And so, I think you know the American Chemical Society, for example, is stepping up to do some really valuable faculty development for new chemists who are going into faculty positions. And you know, I'm sure ASA is doing things. So it's kind of like we need to all get together and say alright, what does the whole system look like? And what are the pieces parts of that system? And who can step in and help without compromising some of the things that I think are really important, like that deep dive into building disciplinary knowledge?

Bailer: So, Ellen I have a really easy question. So just you know, so how do people learn? And then, by the way, is I just like to add a quick follow-up, you know, given the, you know, given that simple answer you're going you're going to share with us, how do you get best teach to that the to the way people learn so that that you have the most impact?

Yezerski: So, I hate to disappoint you with the really short answer. It's definitely complicated, but the way people learn is that their brains naturally do it. Like we're built for that; we go through this natural sense-making and meeting-making process in the world, and if you especially watch little people; you watch children, anybody who has had children, grandchildren, nieces or nephews around and watch people grow, you don't need to give them a really good lecture on walking, you know? They figure out how to walk and they figure out through these experiences and interacting with their surroundings and with other people, and so I think that the most important thing that we can do is recognize that people learn naturally and maybe the problem isn't that we don't understand learning, because we actually know a lot about learning. The problem is that our classrooms don't look anything like how we naturally learn. So, if we could reshape those spaces and reshape those experiences to tap into what naturally happens, maybe it's not that scary.

Pennington: So, how do you define effectiveness in a space like a college classroom or even a high school classroom which is an artificially constructed space that you're supposed to learn in, how do we figure out what is effective?

Yezerski: Sure. So, we have to decide what effectiveness means; we have to define effectiveness first. So, for example, one thing we know is that people like naturally construct knowledge from experiences, so if- but maybe not by like listening to somebody talk at slides for 55 minutes, you know? So then, maybe effectiveness kind of parameterized in that way would be- that if the students are more engaged and the students are actually doing something with the content as opposed to just listening to some expert talk about it, then maybe that could be one measure of effectiveness and the measure part is really important right? Because we have to decide, you know, what can we capture? What can we see? What can we count? What can we measure that's going on in the classroom that's going to give us some kind of indication as to the extent to which students are, you know, engaged with the content, right? So, there's a really interesting instrument out there that people have been using- it's called the COPUS- I always figure out what the acronym is. It's a classroom observation protocol for undergraduate STEM. So, STEM, you know science, technology, engineering and mathematics. And it's an observation instrument where every two minutes the person who is collecting the data is indicating what the teacher and what the student happened to be doing, or students have to be doing. And you can imagine that if you wanted to change your COPUS profile, as it were, that you would spend more time having the students doing something than the teacher doing something. And I always say she who does the work does the learning so the COPUS is, you know, kind of a neat way just to look at this very kind of I don't know… I would call it like kind of coarse-level, C-O-A-R-S-E kind of coarse, level indicator of what's going on in the classroom. Now, I think that it's a lot more complicated than what the COPUS captures, but, if you can imagine a group of colleagues deciding that if engagement speaks to assess effectiveness, then maybe measuring engagement would be a fruitful way to go.

Campbell: So, how I have a- I have a confession. So, the only D I ever got in high school in any was a semester in chemistry. So, it also kind of put me off science. I didn't think I was going to be good at science and I think this happens- we talk a lot about this with statistics and math, not so much about science. But I think- I think a lot of students who could actually excel in science go a different direction fairly early on. And I think that happens both in high school and I think it happens to college students as well. Can you speak to that a little bit and maybe more about what can be done in the classroom to sort of deal with that sort of fear of science that some students and adults have?

Yezerski: Yeah, I'm sorry Richard that you didn't have a really good high school chemistry teacher who said, you know, you'd be inspired for my department, right? So, inspired. So, I think what happens is we kind of get these blind spots as experts and we lose touch with important things that a novice is experiencing. One of those things might be the why, I like what's the point right? I don't want to be a doctor. I don't want to be a chemist. Why do I have to even learn chemistry? And if we- and I think if you show students really like neat explosions, that's fun for that 30 seconds, but then it doesn't relate to their life, right? And that's not really the role that science plays. In fact, good chemists control reactions, you know. they don’t blow things up, unless it’s in a bomb calorimeter and they need to do it. Anyway. the key thing there is that the relevance has to be there for people to engage, and we also have to think about how do you kind of shape knowledge in the discipline? You know, how does a novice look at things? And chemistry is a great example because when you're a chemist, you get good at dealing symbols. So, see this is going to relate to statistics. It's coming. When you're a good chemist, you have all of these really convenient, shorthand ways of representing complex ideas, and you manipulate those really easily, and you can talk to other chemists in this super-shorthand, bizarre way, and they know exactly conceptually what you're talking about. But then we try to take that and do that with novices. They don't have the conceptual understanding. They don't have that foundation. They don't know what these symbols mean. So, then they just become really good at manipulating symbols to- you know, get quiz questions right and get good grades and move on, and that's- you know, that's really not desirable. So, we really need to get back to like the core concepts in our disciplines, especially in the sciences, and I'm sure this is something that in statistics education, people are focused on. I mean you can learn all kinds of rules and regs to move symbols around, right, but that's not what statistics is. You know, you have to be thinking about like, what do those values mean? And what does that mean for whatever is out in the world that you're studying and trying to make sense of, you know and use statistics to better understand, you know? And I think a lot of the chemical symbols and things are along those lines too. So, I would say that's what we need. We need to start moving symbols around and start getting into concepts.

Pennington: You’re listening to Stats and Stories and today we're talking with Ellen Yezerski, the Director for the Center for Teaching Excellence at Miami University. Ellen, you’ve been talking a lot about sort of what novices need, but I wonder how that experience in the classroom of sort of getting- what does that look like for a more advanced student, right? So I mean obviously with the novice relating it back to their life in some way you know help them understand the logic behind the symbols or whatever it is, right, but once you have them in maybe your major or maybe their minor or maybe they’re taking the class because it just sounds interesting and fits into their schedule, how does that change for those more advanced students? How does that engagement and that thinking about what effective is for them, sort of, how should it shift the way a professor or a high school teacher, or any teacher approaches the subject?

Yezerski: That’s a really hard question to answer, but I appreciate it because it really gets everybody thinking. So, you think about as you build expertise as a discipline, how do your ideas change? Like what does it mean that you can do what you couldn’t do last year kind of thing? And I can say specifically in chemistry you start to think about the world on the molecular level. And everything in chemistry has to do with what atoms and ions and molecules are doing, you know? And so, reasoning with chemical ideas means reasoning with models. It really comes down to understanding models and their role in doing science. And so, as you get more and more sophisticated you start to understand what the limitations of those models are, what the generalizability of different models are, and you start to understand that, oh, we had to over-simplify this principle so that we could make sense of it at the end of first-year chemistry. But then oh, in physical chemistry you have enough mathematical understanding that you can now put another layer onto that model, a mathematical version of this particle model, for example. And oh wow, you know, you can ramp up the complexity because we now understand. You know, we have other ways of representing this phenomenon to study or representing the ideas of what’s governing the phenomena we’re studying in nature. So yes, as we’ve built sophistication we get more tools in our toolbox, we get more complex kinds of reasoning, and if we think about how that relates to teaching, right, we have to methodically plan students’ steps up those rungs of the ladder, right? So, one of the things I always talk about in The Center is you have to really understand the structure of your discipline if you’re going to generate meaningful experiences that are going to lead to learning. And it takes a lot of expertise to do that and just because you’re really good and you have a Ph.D. or a Master’s degree, you may or may not understand the structure of the knowledge and the discipline well enough to be able to create those learning experiences that carefully scaffold one another so that students can develop expertise in a meaningful way. That’s, to me, that’s the golden ticket. If we can help faculty to do that they’re going to be highly effective and if we can get faculty to do that within departments as they sequence students courses and experiences, that’s even a golder ticket if that’s a word. More golden ticket how’s that? Sorry, Richard is giving me like a stink eye now.

Campbell: I like it when our guests invent new words.

Yezerski: It is- yeah, who knows, we’ll just keep working on that.

Bailer: Can I change gears just a little bit to think about where we’re living right now in terms of virtual instruction? You’ve suggested the importance of active and engaged learning. And I mean that was for me and thinking about my own journey from learner, to early instructor, to more seasoned instructor- I mean, I certainly am doing things differently. And the active learning part seems- it’s more natural in a face to face environment. Although, here we are remotely with five of us in different locations doing this and we’re able to make this work, but there’s some nuance here that’s a little tougher to build in. So, can you talk a little bit about in these days where we have this kind of distancing and isolation and a lot of virtual learning, what are some takeaways for doing our business effectively?

Yezerski: Yeah so, I don’t have a ton of experience teaching online, but I have been getting way more than I signed up for in teaching my graduate students in this remote way, as well as teaching faculty. And I would say it’s more remote than online because I’m not carefully designing and sequencing asynchronous activities for them to do on their own, like kind of like the hallmark of good online instruction, but one of the things that has been coming up over and over and over since The Center has been working really hard with our colleagues, has been that it doesn’t matter whether it’s face to face, or its online, the principles are the same. It’s all about starting with what does learning looks like? And how can we help people build expertise to be able to evidence that learning? And then it’s like okay, so what tools and spaces and strategies do we have at our disposal to make that happen? And then when we switched to remote and online, all of the tools and strategies changed, right? But we needed to help facilitate or help happen in the learner didn’t – and so because the- kind of the tools changed and the environments changed, some of the weaknesses got blown up. So, I can give you a really specific example. If you have an activity that you want your students to do and you’re in a face to face class, and you give the directions and the students start, and either the directions are poor and they don’t know what to do, or they go off in a different direction than you wanted them to go in, you can correct it right there you can say hey hey hey, can I have everyone’s attention up at the front here? Remember how I said to use model two? I need all the groups to be looking at model one data for this activity. Okay and then there’s this reset and then everything goes. And so, the instructor will have been responsive. The instructor will have, you know, kind of redirected the students in the right direction. But you can imagine that if you gave that same assignment online and it was asynchronous and the directions either weren’t good or the activity had more flaws to it, then what happens is the instructor gets, I don’t know, 100 emails complaining I don’t know what to do, and the stress you know of the instructor, like, this is not going well. This class activity that is supposed to take us from point A to point B in our learning is not happening, and there’s a lot of anxiety because sometimes the students might not offer the critiques in the most constructive way. They might not say something like I don’t believe the instructions are clear enough for me to make the most of my learning; they might not say that. They might say what the heck with number 12 this is ridiculous; I can’t do this. Or what a waste of time, you know? And so, all of those things that we take for granted, in terms of that synchronous, rapid communication and correction, they seem to go away, which really puts a bigger burden on us as instructors to design things that are a little bit more like instruction-proof. And I would say that, to me, is the hardest part because people haven’t necessarily gone through that whole thought-process all the way, you know? They’re familiar with getting those students started, right, and then being able to adjust. Now it’s like you’ve got to get them started and then you’ve got to build in all those checkpoints along the way, and then a really high-quality assessment to help tell you what’s going on and if the students really have met the learning outcomes. And so, I think that’s where we are now in just building our expertise.

Campbell: I’d like to ask you a little bit about- to switch directions again, like some of the work you’ve done on the lack of good STEM teaching, good STEM teachers, recruiting them in both middle school and high school, and I think in one of your articles I read about and, correct me if this is wrong, but only about 25% of programs- graduate programs, even address the possibility of teaching in high school or junior high school as a career option, is that right? And what do we do about that?

Yezerski: Yes. Right so you’re talking specifically about, I believe, an editorial that was in the Journal of Chemical Education about a project that I’m involved in called Get the Facts Out, and that project is a really great collaboration between the American Physical Society, the American Chemical Society, American Mathematics Association, and we’re trying to change people’s ideas about middle and high school teaching, specifically, chemistry, physics, and mathematics are the areas where we’re trying to, you know, kind of fire-up interest and do that by you know combatting some of the myths that are out there. I think one of the things that we’ve worked on in that project that’s interesting is- sometimes faculty in those disciplines they have a really awesome student who’s really successful and they say yeah, I want to be a high school chemistry teacher. Maybe some of those faculty- instead of saying awesome, I want to connect you with the right people to help you develop your skills so you can kill it as a teacher, they say things like oh, you could do so much more. Why don’t you go to graduate school? Why don’t you go to industry where you can make a lot more money? Or you know you’re so bright you’re better than that. And these are embarrassing messages, right? But unfortunately, people have inaccurate ideas about secondary teaching and the excitement and the challenge and the salary and the benefits that people can experience. So yeah, I think we have a lot of different prongs to that project. One is to help educate faculty about STEM teaching. And maybe some of them aren’t against it, but maybe not promoting it is a problem too, and having it be on that list of viable careers. Like if you’re a chemistry major or, you know, if you’re a physics major. So just getting the word out there and it’s been a really fun project I love the idea of you know confronting ideas and people- it’s like spicy, it’s fun. I like being the contrarian for that.

Pennington: So, one thing that I keep thinking about in relation to my own teaching and as I think about this issue of teaching effectiveness and helping students learn is this issue of trust, which you can’t capture really with a quantitative measure, but seems to be the foundation of all of this. So, how important is it to build trust and are there ways that you have seen in your work at the Center where the instructors can think about how to approach that and make their classroom spaces where trust can be built? So that the student- that when you lead them down this path that seems terrifying, knows that they’re safe exploring the topic with you?

Yezerski: I think that the work that Carol Dweck, who is a psychologist out of Stanford on mindset, on gross mindset versus fixed mindset, are the pop-science words that is used to describe that- becomes a really cool framework for thinking about how do we encourage learning? And are there things that we say and do as faculty that really sends a message that our role is not to develop people, but just to sort and select the people who really already look like me, or have whatever it is- I’m doing air quotes now on the podcast. So, you know, unfortunately a lot of disciplines the sort and select thing has worked for a very long time, and we’ve kept people out of our disciplines that could be, I don’t know, winning Nobel prizes, making the most giant contributions, and, at the very least, just getting us to see things from different perspectives. And so, for us to encourage in our students that we believe that they can learn. I think we also need to help them believe that they can learn. I can’t tell you how many students say you know I’m just not good at math.

Pennington: Yeah. I was one of those as an undergrad. I hated math and then I went to grad school and was like I actually really love math.

Yezerski: They say I can’t do math, or I can’t write, or all these kinds of things, and it’s like hold on a second, you absolutely can grow in that area; let’s figure out how to do that. So, there are some messages that faculty unintentionally send that might say that it’s fixed. I know that for me one of the things I stopped doing in my classroom is I stopped using the word study. Study is just a dirty word in my class; I don’t say study because what I’ve learned is that when I think of studying and when my students think of studying it is not the same activity. So studying to students meant memorizing something, and not working through problems and figuring out patterns and analyzing data, and you know, making sense of things and writing explanations; it doesn’t matter what the homework questions looked like, it seemed, they- studying – learning outside of class and studying were not the same thing to my students. So, I figured that out and I took the word studying out of my syllabus and I don’t talk about studying; I talk about learning outside of class. And when I say learning then, oh okay, well learning is different. My students told me, and this is not original this is Sandra McGuire who is from Louisiana State University, she’s retired now. Sandra- I got the idea, I asked my students like are studying and learning the same thing? And what do you think of when you hear studying? And what do you think of when you hear learning? And when I asked a really really large class that and got some insights and I went oh, maybe I should change my words. So, the message is really important.

Bailer: You know, you’re listed on that grant that you just described as a change agent. I love that as a title and Ellen, it’s pretty clear from the passion in your interests you certainly are bringing that to people’s teaching and learning, so thank you for that.

Yezerski: Thank you. I’m glad you noticed that.

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How to Teach an Intro to Stats Class | Stats + Short Stories Episode 78

Mark Hansen is a professor of journalism where he also serves as the Director of the David and Helen-Gurley Brown Institute for Media Innovation. Founded in 2012, the Brown Institute is a bi-coastal collaboration between Columbia Journalism School and the School of Engineering at Stanford University -- its mission is to explore the interplay between technology and story. 

+ Full Transcript

(Background music plays)

Bailer: Introductory statistics classes have been taught for decades, and some students have viewed it as a source of punishment for past crimes. There are challenges about how we might do this differently. Today we're going to talk on this Stats and Short Stories episode about what should the narrative be in an introductory statistics class. We're delighted to be joined by Mark Hansen a professor of journalism at Columbia University and the director of the David and Helen Gurley Brown Institute of Media Innovation. I'm John Bailer chair of Miami University's department of statistics and I'm joined by Rosemary Pennington a professor in the department of media journalism and film and Richard Campbell former chair of media journalism and film. Mark thank you so much for joining us and I want to start with that question. What should the narrative be in an introductory statistics class?

Hansen: I mean so I'm seriously thinking about going to…because I have a joint appointment in the stat department at Columbia so I'm seriously thinking of like taking on that introductory class now that I know what I know. Because. I mean the narrative burden here is just to say, saying that the mean is five or something is not enough. What does that mean? What's the context behind it? Are there implications for that? Right, like what…again, it goes back to not just telling the story of the dataset like a dataset, right? Oh, there are two outliers here. Oh, it's skewed to the left. Oh, there's three modes. Oh, you know, it clusters in this way…but instead to like take the next step and like get someone on the phone and figure out why this is the way this is or start to do a little research. And I don't know that I've seen how reporting classes work, right, and the way you send people out into the world. They don't start with a data set, they start with a question, right, and how do we address the question. Even when I teach my advanced data class in the J. School I think that last couple years I've been on the criminal justice system and we start with questions like What does it mean to close Rikers. How do we ask questions about that and because it’s a data class, we would like to have some data involved.

Bailer: Go figure!

Hansen: They’ll retreat to their comfort place and they'll just interview a lot of people but you know that interview is a lot more interesting if there's some data analysis done. I looked at the data and I saw this, this and this. We calculated the average transit time between you know between where a family lives and the prison that their loved one is in is incarcerated in, right, and it's this amount of time. What we do with that? Right, like there are things that you can do to make those interviews a lot more interesting so. And a lot deeper and it just I don't know it's…we've tried it also with G.I.S., like teaching mapping not just as a way of visualizing but also as a way of organizing reporting and we'll pair editors with teams so that a team of you know usually a mixed disciplined team but often statistics, data science or whatever, get an editor who will help them ask questions and bring them through this process and it's astounding, it really is.

Bailer: That's a really cool model.

Pennington: Yeah. I was going to say, it wasn’t until I went to grad school I had to learn to run all this stuff by hand and luckily had a stats professor who was sort of saying what are you interested in, let's look at some data and figure out how you can use it and then figure out what tools you need. Then I was like oh I actually really enjoy statistics I wish someone had actually done this when I was eighteen and in a class where I’m like I hate everything about this.

Hansen: Well I mean the thing is and probably one of the last soap boxes that I have to get on is that is that we as a journalism school shouldn't be teaching this stuff. I mean it is historical curiosity that I am teaching python to a group of journalists or that I am I'm you know that we would be teaching mean, median, mode in our introductory data classes, right? That's K-12, that is a proper undergraduate training probably K-12. The fact that they come to us not knowing any of this is like I said, a historical curiosity that will hopefully go away and that when students come to us we can focus instead on how do you use these ideas to really interrogate systems around us, because you know we don't teach students grammar I mean well sometimes we but ideally we're not teaching them grammar…

(Voices overlap)

Pennington: I'm doing that right now.

Hansen: I mean yeah you got to admit, some people are sort of worse writers than others and the ecosystem supports that somehow but there are some basic things that we don't have to teach, right, and this in the same way these basic things in statistics or data, we shouldn't have to teach either and the basic understanding of how computer works and how an interface works and like all that stuff we should have critical thinking skills around the technologies around us long before they get to graduate school…that's just it's shameful.

Bailer: That's a really great point. We're trying to do a lot of things to sort of make sure that we have a vibrant and vital introductory exposure to statistical ideas because you want people to be able to think about asking questions and the data that's required to answer them and always contextualize in the work. I love the way you frame that and I think that's something that we embrace and…

Campbell: I think we need to bring Mark here.

Bailer: Yeah! That’d be fun…

(Collective laughter)

(Voices overlap)

Hansen: But I mean I think I think that there really is there really is something I have to figure out what this experience has meant being in a journalism school because my Dean keeps talking about the durable principles of journalism and at first you know the best that I could tell was what you know what I…because I would co-teach in a reporting class to the data students and mostly I would watch someone like Ann Cooper or you know do her amazin thing. But there were some things like you know like referring to journalism as portable ignorance, right? I love that! Or like I'm slowly, over time seeing what those durable principles are and how we have strategically when the durable principle goes right statistics seems to go left. Like there's moments to bring these things back together and I really I don't know I just think that it's such a shame that students can come away from that introductory stat class and not realize that statistics is amazing. I try to always teach it like…because I remember having our history class. It was a 101 class or something when Wayne Tebow taught it and I came away going, holy sh*t, that is the most amazing like I had never thought I would be oh my gosh and how many students come away from our introductory stat class going oh my gosh that's what I want to do, right? I want to do the T-test. There are no people in our introductory stat class right, Type one and Type two error smashed together with P values, we don't know that there was any conflict around that, we don't know who the people are, we might have historical curiosity like Gossett came from a brewery and tehe tehe right, but that's about it. There's like no nothing of the human side of it and I don’t know, it just feels like such a wasted opportunity. Anyway I mean I'm going off, I'm sorry

Bailer: No, this is great fun! Thank you so much. That's the time we have for this episode of Stats and Short Stories. Mark, thank you so much for being here. Stats and Short Stories, in fact Stats and Stories is a partnership between Miami University’s departments of statistics and media journalism film and the American Statistical Association. You can follow us on Twitter or the iTunes podcast land. You can also find Stitcher, or you can find us on Soundcloud, wherever you want to look, you probably can find us anywhere. If you'd like to share your thoughts on our program send your e-mail to statsandstories@miamioh.edu and be sure to listen for future editions of Stats and Stories we discuss just the statistics behind the stories and the stories behind the statistics.

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