In this inter­view, Pro­fes­sor Dorothy Bishop talks to us about how she has used games both for teach­ing chil­dren lan­guage as well as for keeping them moti­vat­ed in psy­cholin­guis­tics experiments.

Dorothy is a psy­chol­o­gist spe­cial­iz­ing in devel­op­men­tal lan­guage dis­or­ders. She is Pro­fes­sor of Devel­op­men­tal Neu­ropsy­chol­o­gy and runs a Euro­pean Research Council Advanced Grant in the Depart­ment of Exper­i­men­tal Psy­chol­o­gy at the Uni­ver­si­ty of Oxford.

There is a growing trend for researchers in the field of psy­chol­o­gy to use games in their exper­i­ments. This inter­view is part of a series inter­view­ing pio­neers in the field of gam­i­fied research who have used Gorilla to develop their exper­i­men­tal designs.

What led you to gam­i­fied experimentation?

Long before Gorilla existed, I was inter­est­ed in doing psy­chophysics with chil­dren to see how fine a dis­crim­i­na­tion they could make between various sounds — because there’s a wide lit­er­a­ture par­tic­u­lar­ly on dyslex­ia and lan­guage dis­or­ders — and the idea that these prob­lems might relate to poor fre­quen­cy discrimination.

What people were doing was going straight from what was done with adults to doing it with chil­dren the same way, and it was incred­i­bly boring! You needed an awful lot of trials and you had these adap­tive pro­ce­dures where it got harder as you went through, so the more you suc­ceed­ed the harder it got. You typ­i­cal­ly needed to get adults to do about 100 trials to get through this pro­ce­dure and after about three or four trials kids would say, “Is there much more of this?”.

The main thing I learned was that to make the task into some­thing the chil­dren would want to do you need sounds. Because we were testing sound dis­crim­i­na­tion, people were very nervous about putting in any audi­to­ry rein­force­ment because they thought, “Well, they’re lis­ten­ing to sounds, it’s going to confuse them if they get other sounds.” But actu­al­ly it didn’t, because the rein­forc­ing sounds were much more complex — more like the sorts of noises that are used in games. When the kids got a ques­tion right they had a gliding sound that went ‘broop’, and as they got more and more answers correct the sound got higher in pitch. At the end of a block you got much more excit­ing things happen with cartoon char­ac­ters jumping around saying, “Well done!” and so on.

Do you think such rein­force­ment strate­gies would work for some­thing educational?

Well the other thing we then moved onto was trying to train com­pre­hen­sion. In these train­ing tasks, there are two key things: there’s the rein­forc­ing sounds, which really make a dif­fer­ence, but the other thing is you have to keep them wanting to get to the next level. The trouble with most exper­i­ments is they are very repet­i­tive. But we found that if you build in levels through which they progress as they learn, it doesn’t actu­al­ly matter if the levels are arbi­trary points in a learn­ing sequence; the par­tic­i­pant doesn’t know the change from level one to level two is actu­al­ly just that you’ve done 12 trials or some­thing. They see it as progress. The markers of the levels need to be some­thing inter­est­ing, so we had char­ac­ters appear­ing on the screen with a message indi­cat­ing their progress.

I think this could make a huge dif­fer­ence not just to chil­dren but also to adults. I had a PhD student who studied adults and kids and when we sub­mit­ted our papers for pub­li­ca­tion, we’d get people saying, “Well, you know, this is very child­ish. You’ve got these jumping dinosaurs. This is insult­ing to adults.” But of course what we actu­al­ly found is that the adults loved it too. It was so much more fun than the typical psy­chol­o­gy experiment they were asked to do. It also depends where you’re recruit­ing from because, if you’re recruit­ing online, you really need to have some­thing in there to defend against the person that’s just going to hit the keys at random to earn the money: if you can engage them to want to progress, it may help with that.

Were the ideas that you had for these stim­u­lat­ing games from your own intu­ition or from prior evi­dence and experience.

It was mainly intu­ition, but also expe­ri­ence. When I was testing chil­dren in a nursery I would talk to the staff there and ask them, “What do you think would make the kids inter­est­ed?”. And they were able to show me the sorts of com­mer­cial­ly avail­able edu­ca­tion­al games that they were using and that gave me more ideas. But oth­er­wise it was very much intuition.

Do you have any worries that because your exper­i­ments are in a gam­i­fied format, the data might be biased in some way?

Not really. You have to think very hard what it is you’re trying to do. In the orig­i­nal psy­chophys­i­cal exper­i­ments we were trying to get an accu­rate thresh­old and the big enemy of that is inat­ten­tion. So what­ev­er you could do to get the child attend­ing hard is going to give you a better thresh­old. I suppose the only problem would be if you were com­par­ing dif­fer­ent groups, you may find that some chil­dren found it more moti­vat­ing than other chil­dren, and that might then pos­si­bly be a con­found. For example if you had some­thing that boys tended to find fun and girls just didn’t you might get a sex dif­fer­ence that didn’t really reflect their abil­i­ties, but just was down to how engaged they were.

Are there any fea­tures that you would like to incor­po­rate in games that you haven’t been able to?

I think adap­tive­ness, where you are actu­al­ly respond­ing to somebody’s reac­tion time and then giving them feed­back con­tin­gent on that, could be very useful. And in terms of what may be missing from exist­ing games and apps I think gen­er­al­iza­tion is impor­tant. When I read the very early lit­er­a­ture on lan­guage dis­or­ders from around the 1960s it was inter­est­ing that there was a lot of rote learn­ing, but there was no gen­er­al­iza­tion to every­day life. So methods started to be devel­oped where a ther­a­pist is very much in a real life sit­u­a­tion respond­ing to a child and they don’t explic­it­ly correct the child, but might repeat what they said with the correct syntax and so on. The idea is that this nat­u­ral­is­tic approach is much more effec­tive than rote learning.

Then in the 1990s the first com­put­er­ized remote­ly-deliv­ered inter­ven­tions began to be released, which aimed to teach chil­dren to hear dis­tinc­tions between sounds. Some of these com­put­er­ized inter­ven­tions were beau­ti­ful­ly gam­i­fied but the problem is that most of the evi­dence sug­gests they don’t actu­al­ly work. You can train chil­dren to get better at the game but it doesn’t gen­er­al­ize. People com­ment­ed that we had gone full circle because it was again rote-learn­ing, only this time computerized.

The way we’ve been trying to test gen­er­al­iz­abil­i­ty in our exper­i­ments is by chang­ing the format of the of the task. So you might have a learn­ing task where you hear a sen­tence and move things on a screen to match the sen­tence. We also give them a pre and post test which is simply a mul­ti­ple choice test where you have to match a sen­tence to a picture. That way we can look at two things: does the child show learn­ing in the course of the train­ing, but also, does it gen­er­alise to a dif­fer­ent format? I hope that if we get better at design­ing games that capture chil­dren’s atten­tion, we might also find we can get gen­er­alise beyond the game, but that is the really big challenge.

This inter­view is part of a wider series of inter­views looking at gam­i­fied research. Make sure to follow this link to have a read through them!


Sid Prabhu-Naik

Sid is a PhD student based in the Depart­ment of Exper­i­men­tal Psy­chol­o­gy at UCL. He worked part time with Gorilla in 2021, helping create a suite of fun games to collect research data to better under­stand some of the cog­ni­tive mech­a­nisms behind lan­guage devel­op­ment. He is also looking at how aspects of gam­i­fi­ca­tion itself can con­tribute to more moti­vat­ed, atten­tive, and ulti­mate­ly suc­cess­ful learn­ing strategies.