Friday, July 26, 2019

Nudging Students

As a behavioural economist, I obviously teach and do research on behavioural economics-y topics but I don't really, explicitly use any of the tools of behavioural economics in my work. When I want to influence the behaviour of my students I usually resort to the traditional, classical economical methods of fiddling around with the incentives, which in practice means making part of the grade depend on the behaviour I want them to exhibit (ie. working hard, attending lectures). That usually works but not in all situations. So this past year I thought I'd set myself the challenge of applying a proper behavioural economics intervention somewhere in my work.

Here at the Economics Department of Middlesex University we offer a tutoring service to our students provided by either someone called a Graduate Academic Assistant (full-time employee of the university, usually a recent graduate, hired to assist with all kinds of things around the department) or a Student Learning Assistant (a second- or third-year student with high grades who, as far as I understand, gets paid per hour of tutoring). This service is free but it isn't particularly popular. Very few of our students actually take advantage of it. A couple of students come to the GAA over the course of the academic year but I couldn't find any record of students having a tutoring session with an SLA. And it's not that all of our students are acing all their modules and there’s no one that maybe could do with a bit of extra help.

Previously any attempts to increase the pick-up rate of the tutoring service were of the classical economic variation. We, the lecturers, would publicize the tutoring service in our lectures. Especially in the weeks before a big test. Focussing on the benefits (higher grades) and the costs (zero). This approach doesn't seem to have had much of an effect. No matter how often we advertised the service, the number of students using it stayed close to zero. So it looked like a good challenge to apply some of that behavioural economics magic and try to nudge more students in taking advantage of the tutoring service.

But where to start? The Behavioural Insights Team of the UK government has created a very handy framework to help practitioners think about applying the tools and methods of behavioural economics. They’ve called it EAST and the name refers to the idea that if you want to nudge people to behave in a particular way, you should make this behaviour Easy, Attractive, Social and Timely.

The A-element, the attractiveness, I've always found the least interesting. Mainly because to me it seems closest to the traditional economic approach. It focuses on the incentive, the benefit (to the student) of exhibiting the behaviour. The traditional economic approach will generally involve increasing the size of the incentive but, especially in situations where such an increase is not possible, making the incentive more salient is also a fairly standard method. And something that in our present context we already do. We publicize the tutoring service in our lectures and explain their potential positive effect on grades.

The S-element is probably the sexiest. It's the one that gets a lot of exposure when people talk about behavioural economic interventions. Probably also because the social aspect of our behaviour is something that traditional economics doesn't pay a lot of attention to. The classic example of the positive effect of making people aware of existing social norms is Cialdini's towel experiment. Where telling hotel guests that 75% of previous occupants of their hotel room reused their towel, instead of requiring fresh ones every day, made these people more likely to reuse their own towels. The same effect has also been shown in other contexts, from electricity use to littering (but, under certain circumstances, it can also backfire).

I have no doubt that appealing to the social motivations of students could be very successful in changing their behaviour, even it was simply in the form of an enthusiastic testimonial. But in this context privacy issues might be a complicating factor. Even if it was a positive experience for you and it led to, say, finally understanding how to use the mid-point method to calculate price elasticity (and getting a high grade for the test), the fact that you asked for help from a tutor maybe isn't necessarily something you want to brag about or even have announced to your fellow students. Also percentagewise, the number of students who are likely to make use of this service is probably too low to get similar effects as for the 75% of previous guests in your hotel room.

The T-element refers to how people can be more susceptible to change their behaviour at different points in time. I like to think we already used this and that we've probably exhausted its possibilities. As said, an obvious moment to advertise the existence of the tutoring service is right before a big test. The benefits are pretty salient even without having to stress it too much. Overconfidence - I don't need any tutoring. I'm smart enough to figure this stuff out by myself - could be a factor that works in the opposite direction so I usually advertise the service after a big test as well, when the students get their grade back and it is maybe a bit lower than they expected. (Also, I don't think it is very useful to start talking about the service in the first few weeks of the year because of the aforementioned overconfidence being probably even higher and because there are usually enough new and unfamiliar things going on in these weeks so that the message easily gets ignored).

Just like the A, the E-element, for Easy, can be interpreted as a bit of actually fairly traditional economics. In my mind, making particular behaviour easy means lowering the cost. But this cost doesn't necessarily have to be financial which is probably where the behavioural economics comes in. The tutoring service is already free for the students. But there are other costs involved as well. Time, for instance, but I don't think there's a lot of gain to be made there. One aspect of the process that is quite cumbersome, is the way in which appointments for a tutoring session were supposed to be made. The GAA was relatively easily approachable because they have a dedicated office where students could drop by and they didn't necessarily have to e-mail beforehand to make an appointment. But still, for some students having to approach someone in person like could be a bit of a psychological threshold. The SLA's were even harder to track down. As part of publicizing the tutoring service, we always included the contact details of the SLA's but that still meant that the student wanting extra help needed to approach someone they didn't know to ask them for a favour at an unspecified time and location. I can imagine all of this might be a bit of a hurdle to ask for help.

So I figured that here was the opportunity to make improvements and apply some behavioural economics. By simply making the process to make an appointment easier. I am a lecturer on one of the first-year modules so that seemed like a good enough context to try it out. I asked the GAA and the SLA's which hours during a typical week they would be available for tutoring sessions. I put these hours into Acuity, a very simple appointment making website, and added options for each of the four first-year modules. The end result was a very basic webpage – with an easy to remember url: - where students were asked which of the modules they wanted help in and to pick free timeslot on their preferred day.

When they had entered their contact details the website would send an e-mail with the request to me and I had to forward it to the GAA or SLA who had said they were available at the requested time (one drawback of using the free version of Acuity was that it only allowed for one user on our side). The agreement was that they, the GAA/SLA, would then get in touch with the student and make further arrangements. Including suggesting a location (the library for instance). The proposed time wasn’t set in stone. If tutor and student came to the realization that another time worked better, they could settle on that time without having to go through the system again. The main idea behind the website was mainly to make it as easy as possible for the student to take the first step in asking for help from a tutor (in that respect it is also an advantage that the, probably confusing, difference between GAA and SLA didn’t matter anymore. A tutor was simply a tutor on the system).

If this was a proper RCT we would have created a control group and randomized allocation to the treatment condition, but that was just not doable in the current context. To be honest, the whole data collection aspect of the intervention was a bit of a mess. To start with, I don't really have exact numbers with regard to how many students made appointments with either the GAA or an SLA previously. I asked around and the GAA said she saw a handful of students in past years but for the SLA the numbers were apparently so low that nobody bothered to register them.

And for this year, with the intervention, I really only have a register of how many requests for an appointment I have forwarded to either the GAA or the SLA’s. That was 26. That is bigger than the ‘zero to a handful’ from previous years, so in that respect it seems that the intervention has worked. It should be noted that 15 (=58%) of the requests came from the same student. This isn’t actually that remarkable. From previous years I got the impression that there often 1 or 2 students in the year who have figured out that getting help from a tutor is something that works for them and make regular appointments. The other 11 requests were from 8 other students in total. (We had about 60 first-year students this year).

But I don’t know how many actual tutoring sessions came out of these 26 requests. I’ve asked the GAA to check. And where I seem to have forwarded her 12 requests, it only led to 6 actual tutoring sessions in her records. Sometimes students didn’t respond to the follow-up e-mails trying to establish the details for the appointment. Sometimes students didn’t show up for an appointment that was made. I assume that this percentage is similar for the SLA’s, but can’t check because they didn’t keep any records.

Despite these numbers being a bit dodgy from all sides I still put them in a graph because that’s what we do with data. Especially if it makes it look like the intervention was a big success.

So, what have I learned from this project?

- Collecting reliable data in a real-world situation like this is much harder than collecting data in a laboratory or online setting, my usual experimental surroundings.
- Still, I like to think the intervention was a success. Talking to some of the SLA’s who had been in this role in previous years as well, they told me that they actually had things to do this year. Sure, there’s lots about the process that can still be improved but creating the website with the timeslots seems to make taking the first step of asking for help from a tutor easier for students.
- Some additional insights: most requests were for the Quantitative Methods module (which wasn’t that unexpected, from their grades it is pretty obvious that a lot of our students struggle with mathematics). And there doesn’t seem to be a very strong relationship between the timing of the requests and when the big tests are. I expected the system to be especially busy before exam time but the requests trickled in pretty much evenly spaced out over the year.
- It was really fun to do. I know the intervention in itself is really very simple. I’m almost a bit embarrassed to call it behavioural economics. It’s simply ‘making something that was a bit of hassle slightly easier’ but a lot of nudging can be described that way. I liked the thinking about the problem in terms of the EAST framework and the solving the puzzles associated with the implementation of the solution idea I had. I especially enjoyed seeing the intervention being quite successful.

(The picture at the very top I've borrowed from this tweet).

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