108 – James’ Journey of Innovative Statistics Education

[00:00:00] David: Hi and welcome to the IDEMS podcast. I’m David Stern, one of the founding directors of IDEMS and I’m delighted to be here with James Musioka, Dr. James Musioka, I should say, Impact Activation Postdoctoral Fellow at IDEMS. It’s now our second episode together. Hi, James.

[00:00:25] James: Exactly, yeah. Hi, David. It’s good to be back to the podcast.

[00:00:30] David: I’m hoping next time you’ll be the one interviewing me, but this time I’m wanting to dig in with you into the work we started together, then you took over and carried on, which was really trying to support university statistics education in Maseno and I suppose beyond.

[00:00:52] James: Yeah.

[00:00:53] David: Our first experience with this was when we co taught a course while you were still doing your MSc, is that right?

[00:01:02] James: Yeah, I think that was back in 2011.

[00:01:04] David: Yeah, it’s a long time ago.

[00:01:09] James: It is a long time ago, yeah.

[00:01:11] David: And the nature of the course, I’d taught you a few courses in a similar vein, and the nature of the course was rather different to how other lecturers were teaching at that time, using technology, statistics packages as part of the teaching.

[00:01:28] James: Yeah.

[00:01:28] David: And you then took that, or those ideas, and you went a lot further. Do you want to just talk through some of those experiences about how your thinking on the education related to working with data at university level really started?

[00:01:49] James: Yeah when you started teaching us, and you brought in technology into the teaching and learning of statistics, I think I was rather fascinated by that approach, and it actually helped me to understand, have a deeper understanding of statistical concepts in a way that I hadn’t understood them from my undergraduate degree. I was really delighted with this approach. And I was actually very keen to apply those approaches in my own teaching. So that is why I ran away with those ideas into my teaching.

And, yeah, I found them to be really, I think they helped my students a lot as well from their feedback, from what I got from their feedback. And, yeah, I think they’ve really transformed the way I was teaching statistics, or the way I’ve taught statistics in Maseno, for all that time. What was the first course, the course that we taught together? Was it ANOVA? Yes, it was ANOVA, yes, where we used data and GENSTAT and all that.

[00:02:46] David: GENSTAT Discovery.

[00:02:48] James: Exactly, yeah, the free version, yeah. Many years, indeed.

[00:02:52] David: Yeah. And of course, when Genstat discovery ceased to exist, that was part of the impetus which led to R-Instat, which sort of, you were the one originally pushing that, partly because of the needs for your students.

[00:03:06] James: Yeah, that was in 2015, I think, once GenStat, that free version ceased to exist, then there was a gap because I think we do have some free statistical software packages like R, but for our students, I think it was a steep learning curve to start with that, and so there was a gap there to be filled, and that’s where R-Instat came into play.

[00:03:28] David: But it’s interesting that R-Instat wasn’t quite the solution that you hoped it would be, and part of that is because of computer access versus mobile phone access. Is that part of your experience?

[00:03:42] James: Yeah, I think generally, computer access was a challenge to this approach of teaching generally, not just with R-Instat, even with GenSTAT, but I think as much as it was a challenge, it was also an opportunity. And the students actually, I think we underestimated their level of access to computers. I think from my first course, I was shocked that about a third of the class had access to laptops. And they were willing to share those laptops in class and, then everybody was able to use computers in their learning.

[00:04:15] David: I think I remember that course because the access wasn’t that wide at the beginning of the semester, but actually once that incentive was given, then by the end of the semester, pretty much everybody had access through somebody.

[00:04:30] James: Yes, exactly. Yeah.

[00:04:32] David: Now, I often quote this experience because we were together at that time when you were teaching that course and observing how you taught that and what happened, that totally changed my thinking about the university needing computer labs. Of course, it was ironic that just after that, there was a computer lab built on the back, partly of all the students using the computers, and that disincentivised students having their own laptops, which was a whole different issue.

[00:05:03] James: Yeah, exactly. That lab was useful for this, yeah. I think in a way it improved computer access for the students, because those who could not find access from their friends or colleagues, then they had to come to the lab to access computers. And the other thing that the lab helped with, I think, was the teaching of the MIT courses.

[00:05:23] David: Yeah. Just for context, Maseno had IT courses for all their students, the catchphrase in Kenya is if you went to Maseno University, you were with IT because all the degrees were with IT. Including information technology, you did it with IT.

[00:05:40] James: Or computing with IT.

[00:05:44] David: And the courses that you referred to, the MIT courses, these were courses that we designed in the maths department to be more relevant for the students studying mathematics, statistics, actuarial science, broadly the students that we were teaching.

[00:06:02] James: Yeah.

[00:06:03] David: And as you say, they were taught partly through this computer lab that was then put in. But I want to come back to the fact that my understanding more recently is, and this is part of what Mike and yourself learned with STACK, the access to phones is so much better than the access to computers.

[00:06:25] James: Exactly. Almost every student has a smartphone.

[00:06:28] David: And therefore, if you can give the education using something like Moodle online through a phone, actually, that’s so much easier than if they need to have laptop access.

[00:06:39] James: Exactly. Yeah, we found that to be the case. So with STACK, then we had more students not worrying about computer access because they were then able to do all these exercises using their phones.

[00:06:51] David: Yeah. And I suppose before STACK in statistics, you were using CAST.

[00:06:58] James: Yes. So CAST is this set of statistics textbooks, electronic statistics textbooks, which have dynamic resources to enable the students practice and, solidify their understanding of statistical concepts. And for you to use CAST properly, I think you needed access to a computer.

[00:07:16] David: Yeah, it was a computer based software. It was conceived to be used on computers.

[00:07:21] James: Yeah.

[00:07:22] David: And it’s something where its development has stalled in some sense, but these textbooks still exist and they’re extremely well authored, and they were tailored to local contexts in particular in Kenya. And what you found out when you were using CAST with some of your colleagues was that it was the exercises that made the difference. And it was that learning which then led me to STACK.

[00:07:57] James: Exactly. So yeah, with CAST, we were able to give students these mastery exercises where they could get the same type of question as many times as they would like until they properly understand the concept being tested by that question.

And so I think, because of the challenges with access to computers, I think the opportunity to implement this exercises in STACK came from that. Then we were able to, I think overcome that challenge by taking the questions and translating them into STACK questions. And that transformed actually the teaching of some of the statistics courses like descriptive statistics. I think that was the first time we used STACK for statistics courses.

[00:08:42] David: Yeah, that’s right, this sort of transfer of going from what we’d learnt from CAST and then re implementing that in STACK so it was more accessible through mobile phones.

[00:08:53] James: Exactly, yeah, and then the students could access STACK using their mobile phones and everybody then could have access to those exercises for their learning.

[00:09:01] David: But if I remember correctly, it was actually you who got the funding for the first STACK workshop which then Mike sort of hijacked and then STACK use in Kenya is sort of history, driven by Mike. But this was really your instigation originally.

[00:09:21] James: But if you remember correctly, that funding was not actually for STACK.

[00:09:25] David: No.

[00:09:25] James: We got the funding and then we got this idea of using the funds to run a STACK workshop. And then we had to change the purpose and, yeah, it’s been history since then.

[00:09:37] David: But it’s interesting that it is the maths courses which have really taken off in Kenya and beyond more than the stats courses.

[00:09:46] James: Yeah.

[00:09:47] David: Now, that could just be because Mike is such a different personality to you, but I think there’s more to it than that.

[00:09:54] James: I think so too, yeah. I’m not sure really what could be happening there.

[00:10:00] David: Well, STACK was never designed for statistics.

[00:10:03] James: For statistics courses, yes. I was going to say that, yeah, I think implementing statistics questions in STACK is not that trivial.

[00:10:11] David: And part of what the problem, I believe, has been is with the maths courses, they’ve simply taken standard courses, standard questions as they are, and re implemented.

[00:10:22] James: Yeah.

[00:10:23] David: Whereas for the statistics courses, everything is bundled up with the idea that actually we need to change the way we’re teaching students to interact with data. And so the courses that you’ve actually created, they’re really novel and imaginative. And that’s what you’ve built the questions to do, the sort of relatively standard courses that your colleagues were teaching. You didn’t create the courses for them, so in some sense you were too innovative for others to pick it up as easily.

[00:10:53] James: Yeah, that’s true. So I think for the courses that I’ve implemented STACK here, I had done some work in improving the course, the way it’s taught, bringing in the data and the software into it. And so I think, as you say, I think because that work had been done so this was another sort of level, adding to that. And so I think my colleagues have found it difficult to implement STACK in their teaching because there wasn’t that previous work that they did with their courses. Which is very interesting. Yeah.

But even with the descriptive course, which I used STACK for, I think it’s not been implemented after I left Maseno in the way that I taught that course. And I think it’s for that reason. I think the lecturers are finding it difficult to use those questions because they are not consistent with the way they are teaching the course.

[00:11:42] David: And in some cases they’re not consistent with their knowledge and their understanding of statistics and data. And I think it’s worth you telling the story of one of your breakthrough moments, which I remember, which was ESMS.

[00:11:57] James: Yes, actually, that was the first course that helped me to come to the realisation that using data and computers in teaching and learning statistics actually helps you to understand the concepts much better. Yeah, that was the first course that I did, I was at the master’s level and yeah, I was taking this course, which was meant for, I think, master’s students and PhD students who are not in statistics. Yet I was, a statistics major, the course was very basic in terms of the concepts because it was really about, I think, the descriptive topics, but I still struggled with interpretation, for example, and I think that’s the cause that motivated me to think differently about how statistics is taught.

[00:12:42] David: Yeah. I should just say ESMS stands for the e learning course of stats made simple.

[00:12:48] James: Yeah.

[00:12:49] David: And it was not intended for statisticians to take it. And when I suggested you take it, you were my master student at the time, I was thinking more that this would be useful that you could then become a facilitator and help others to take it, which was the idea. And you did. But what you found is that actually it was eye opening for you in terms of your understanding of the statistical concepts.

[00:13:20] James: Yeah, exactly.

[00:13:22] David: Now, I’ve now experienced this many times with other people, including PhD students who have struggled with interpretation and have gone through, have great skill in terms of using tools, who have all the, if you want, mathematical knowledge or enough mathematical knowledge to be able to sort of know advanced statistical data science, machine learning concepts, and yet they can’t interpret simple things.

And this is something which I’ve now experienced so many times interacting with so many people. But you’re one of the few people who then actually took that head on, changed yourself in that way, and then have been really trying to change how you teach others so that they gain those understandings earlier on.

[00:14:23] James: Yeah, exactly.

[00:14:24] David: Can you articulate what this is? Because it’s something which I don’t think I would understand if I hadn’t seen it so often. I haven’t lived through it myself, but can you articulate why it is that these basic concepts, which you knew in theory, you suddenly found yourself really challenged in practice?

[00:14:53] James: I think it boils down to the way statistics is taught. From my own experience, I think the way I was taught statistics was mainly theoretical. I think there was a lot of emphasis on calculations by hand and remembering the formulas. There was less time to think about well, I’ve got a standard deviation of two, what does it mean? Or I’ve got a mean of three. I’ve got a median of this value.

But really contextualising that value was never part of my education, really. And so I think coming out really knowing, the formulas and knowing how to calculate and get the correct value, and then realising that you need to go further than just getting the correct value. I found that to be challenging because I wasn’t trained on how to think beyond the calculation.

And so interpretation is a problem, I think, because the teaching of statistics is really theoretical based. And I think that is where the motivation for me to bring change in the way statistics is taught, I think it came from my own deficiencies, especially when I took the ESMS course and all these other things like the teaching of ANOVA. I think from those experiences, I realised that there is need to change the way statistics is taught so that the students we are producing are able to be useful in society.

Because I think in the real world, calculation is not a problem because we have all these tools, as you’ve said, but really interpreting what you have calculated is more important. I think that yeah, summarises my understanding of why this is a problem.

[00:16:35] David: And in some sense, what you’ve described is not just a problem in Kenya, it is a problem pretty universally. And you’ve seen that quite a bit now because you’ve been very involved in the international statistics education community.

[00:16:51] James: Communities, yes, exactly. We sort of hear these experiences from all around the world. Yeah. But I think it’s, I don’t know whether it’s fair to say that it’s severe in Africa, because it’s a low resourced environment. Yeah, I don’t know whether that could be the reason. I’m thinking it’s a problem universally, but it’s more severe in Africa.

[00:17:11] David: Other countries have been working quite hard and it’s been a hard problem to solve. In the US, they’ve got the Gaise report, which is now well over 10 years old. In New Zealand, they’ve had 20 years, give or take, where they’ve now had interpretation ideas introduced from the first year of primary. And so there have been these global efforts in higher resourced environments, which haven’t had the substantial impact at scale that one might have expected.

But where you’re right in the education systems that you’ve been through, for example, those efforts were not happening, they were still before this recognition of the importance of data and the need to support the education in data skills, one could call it.

[00:18:10] James: Yeah.

[00:18:11] David: My question to you right now is, this is a hard problem to solve.

[00:18:18] James: Yes.

[00:18:18] David: It’s hard anywhere. But you’ve made some progress in what is a hard environment. So, what do you feel about actually making progress on this? And you can stay in your context or you can think more globally.

[00:18:33] James: I think in my context it is a difficult problem to solve. I think from my experience, changing or trying to help the teaching community or the teaching fraternity to see this is a challenge, I think. Especially with the older generation, I think they easily stay in their comfort zone, which is teach statistics the way they were taught rather than think about a different and a more effective way of teaching.

And so I think in my view, the easiest way to solve this problem would be to bring sort of small changes, through maybe young lecturers who are coming up. I think that’s like a more sustainable way of doing this within my context, I think, and I’m thinking about Maseno here with the Kenyan context in general. That could be the way that this is changed or change comes to our institutions.

I think the students that I taught, they saw the difference in the way I taught my courses compared to the other courses that were taught. And if some of those students can come back to university teaching, I think they would be interested in teaching in that innovative way. And so that could be a way that we bring change in the way statistics teaching is done in the universities.

But I think it’s much more difficult to change these through the people who are there already, and who have been there for many years. It’s really difficult. I think we’ve tried making an effort with that by preparing resources that can help people to just use them as they are, but still, I think it’s been difficult people using those pre designed resources to change the way they teach. It is, I think, through the newer generation that this could happen. That’s my thinking. I don’t know.

[00:20:19] David: It comes back a little bit to this comment you made about people teaching the way they’re taught.

[00:20:25] James: Yeah.

[00:20:25] David: If they have been taught differently, then they can try and teach that way, because they’ve experienced it. Even for yourself, it was in your masters, you were taught differently, and therefore you had some exposure to receiving that. And that’s a really difficult observation. But it is something where it does lead to this sort of slow, patient, generational change. And we see a number of young lecturers coming in with interesting ideas.

My concern is, it’s not easy for them. Actually, it’s not made easy for them to succeed. And therefore, they’re fighting the system, as you had to.

[00:21:07] James: Yes, exactly. That’s another whole different level of problem. Yeah, because there’s a culture already and the leadership is not, may not be supporting the innovations that the young lecturers may be willing to implement.

That is also part of the problems, because I’ve experienced this, even with my teaching, that I am willing to bring in some new things, but then the leadership is not really supportive. And so I think that is a really big problem because it can easily make the young lecturers or the people who are willing to make these changes to fall back to the old teaching methods.

But apart from the courses that I did, like ESMS, that helped me to change the way statistics is taught, there is another component, which I think I forgot to mention. I was lucky to get involved in practical work. So maybe that is something that also helped me to see how statistics is applied in the real world. And that also motivated the way I taught statistics. I think so. I think that played a role, not just the courses. And I think many lecturers are not involved in practical work and therefore they are not aware of how quickly the world has changed, has moved on from their times. And so probably that could be a factor.

[00:22:26] David: I think this is a really interesting point. And again, this is not unique to your context. There’s many of the stats education community who really believe in the association of statistical consultancy with the teaching of statistics, and actually being able to get these data skills so that people are aware of what’s needed.

And this is where, again, the needs which have come out in the data science world, with the bigger data sets, the different sorts of problems, the different requirements coming in. It is those of us who are involved in doing with data, who can be exposed to actually what does it mean to give people the skills to do this? And those skills look very different to what is in most curriculum.

[00:23:21] James: Yes, exactly. Yeah. I think that’s a very important point.

[00:23:27] David: And so, think the simple thing we are concluding is that it is not easy. There is no easy solution to try and improve the way data and statistics is taught. And I want to be careful because data science is so important now. It’s not just about statistics. The advances with machine learning, with artificial intelligence, and how to integrate that in to the teaching, what was originally statistical education. But really now needs to be broader data education.

[00:24:00] James: Yeah, but hopefully I think with time this change may be coming to the institutions, I think so.

[00:24:05] David: You’ve been involved, I think it was last year, in this sort of workshop , where there were a number of institutions starting data science degrees across the African continent, I should say, from North Africa, East, West, South, Central, yeah. It was an amazing sort of group and you were really quite central in this, I was a bit on the periphery. And again the conclusion there was this is hard!

[00:24:30] James: It is difficult, yeah.

[00:24:32] David: A lot of what ended up coming out was people needing to sort of implement what they can do in their context with the people they have in the environment they have. Because what’s needed is hard and those skills aren’t readily available.

[00:24:46] James: Yes, exactly.

[00:24:48] David: You were, if I remember correctly, pushing quite hard to have data really more central into these degrees, but most of the groups who came in needed to make it around the algorithms or the tools.

[00:25:05] James: Yes.

[00:25:05] David: Because that’s where they had knowledge and skills.

[00:25:10] James: Yeah, and yeah, without data being at the centre of this all, then it could become theoretical, it could fall into the same traps that the statistics education has fallen into.

[00:25:20] David: And this is very much what I have seen as well. You know, we’ve both been involved in teaching these sort of postgraduate courses in problem solving using data. And repeatedly we see that these interpretation skills are not coming across, and quite often, students have gone through maybe even a full undergraduate in statistics or even data science without actually working with data.

[00:25:54] James: Exactly. Yeah, the most recent problem solving course that I was involved in, this was pretty apparently clear. Because we weren’t teaching very hard concepts in that course. They’re very simple concepts, which I think everyone in that PhD class had encountered before, but they really found it challenging working with real data and interpreting the results in the context of that data set. So yeah, I think it is hard, as you say, but there are opportunities there, I think.

[00:26:25] David: I should be clear, that was not real data, that was realistic data.

[00:26:28] James: That was, yeah, simulated data, close to real data.

[00:26:35] David: Yeah, it’s a fun course to teach that one.

[00:26:37] James: Yeah.

[00:26:38] David: But just a final thought. My memory is that your first exposure to statistical software and thinking was not actually from me, but from a former colleague who sadly passed away over 10 years ago. Ely Bodo, when you were an undergraduate.

[00:26:56] James: Yeah. During my undergraduates degree.

[00:26:59] David: And if I’m not mistaken it was actually the innovations he did, possibly with your class or maybe even some classes before you, that led to me going to Maseno.

[00:27:12] James: Yeah. Yeah, I learned that much later.

[00:27:15] David: He was, am I correct that it was related to an internship or a, what was it? Attachment.

[00:27:21] James: Yes, so there was this component that was added to the degree program, where I think at the end of the degree program, you spend three months in a local institution within Kenya, so that you get an opportunity to apply the skills you’ve learned in that organisation. That component in that degree program has really been useful for the statistics students. Yeah.

[00:27:46] David: And am I correct, that Eli Bodo introduced, was it Genstat he introduced back then?

[00:27:52] James: Yeah, so there was even SPSS introduced as well at some point, yeah, to prepare the students for that component of the degree programme. And that component is still there and I think it’s helping the students to see the value of the education. And actually I think I’m glad that you brought this up. I think it is actually through this component that we’ve been getting a lot of feedback from the students that they, for example, the few innovations we did with the degree programs, like the IT courses, they are finding that the skills they got from these courses have been the most useful in those environments.

[00:28:28] David: We’ve known each other now for over 15 years and I have been working, first I was working teaching, but then we’ve been working together now for a long time to actually try to understand how to help others learn with data. And it’s been a challenging journey.

[00:28:51] James: It has been, yeah.

[00:28:52] David: Are there any last thoughts? We should wind up now, but are there any last thoughts you’d like to share about your personal journey or that journey together that we’ve had?

[00:29:04] James: Ah, that’s a very interesting question. Yeah, so I think, it’s been a, I think one word that I can use to summarise this journey is it’s always been a learning sort of experience. I think since those days that I was your student and now we’ve been working together. It’s still a learning process for me in many ways. Yeah, but it’s been very useful.

[00:29:27] David: It’s been a learning process for both of us together, because when I first started teaching you, I was an algebraic geometer. I knew nothing about statistics or statistics education. We’ve been on this journey together. But I think maybe you picked out learning, and I think that’s really important. What have you learned? What do you feel now you can say confidently you understand about this challenging topic?

[00:29:56] James: I think from all these years, I think I have learned that it is possible to, so I’m talking about the topic of innovating statistics education in Africa and beyond, and I think what I can say is that it is difficult, as you’ve said, to bring this change, but it is possible and it is doable, I think in smaller ways at the moment still.

But those changes have a very big impact and so they shouldn’t be underestimated. In my view, I think people shouldn’t be discouraged carrying out these small changes because they do have big impacts. And I’m hopeful that with more time that bigger changes will be possible.

[00:30:36] David: I think you’ve summarised it well. We’ve been for many years now, it is almost 10 years since we started talking about having viral scaling on this. Little changes which become big changes.

[00:30:48] James: Yeah.

[00:30:49] David: And it’s been hard work, and still, there’s a lot to be done to be able to get these ripple effects to really start coming out.

But I think you’re right that there’s sort of something about really, focusing on the small changes because they have big impact, it remains the sort of correct approach and the hope being that they create that ripple.

[00:31:13] James: Yeah.

[00:31:13] David: Thank you. It’s been a pleasure as always.

[00:31:16] James: Thank you very much too.