Chris Filip dissertation blog

Deconstructing and analyzing crowd-sourced games

Category: Research

Reading: Noise Battle

I’ve read the second of two gamified app proposals I have found while searching for gamification on Google Scholar (really sorry, UCS Summon, you don’t work that well). It’s a proposal called “Noise Battle: A Gamified application for Environmental Noise Monitoring in Urban Areas” written by 4 students at the University Jaume I Castello in Spain. It’s been written to be presented at the 2013 Association of Geographic Information Laboratories for Europe (AGILE) conference. Much like the other proposal that I’ve read, Towns Conquer, this takes a problem and tries to write a gamified app proposal for it. Let’s have a more in-depth look at the proposal and see if it will sink, like Towns Conquer, or manage to hold its own.

Much like Towns Conquer, this paper has all the signs of not stopping to think too much about the game design elements behind it. I’m guessing this and Towns Conquer were part of a university assignment, because there are the same key texts quoted in it, Zicherman’s SAPS model and Lazarro’s 4 keys to fun, then they talk about the back end and front end of the app, it’s still on the Android platform, not released yet etc. Unlike Towns Conquer, however, this gamification example actually looks like it could work.

Noise Battle uses citizens as sensors literally. Users would be using an application on their Android phone in order to record environmental noise from their surroundings which they would then upload to a central location to get processed. Why I think this would work is because it requires users to do multiple monitorings of noise in areas, at certain time intervals. Like Towns Conquer, it uses the same “you conquer this part of the town if you record a noise”, but unlike Towns Conquer, it makes sense to have parts of town change owners. The people behind this thought that they would split the town in a grid, and then when a person records ambient noise in that location (traced by GPS, I assume), they win that square in the grid. There are a few factors that they take into consideration when deciding who owns a square, like the amount of time since the last recording, the quality of the current recording and so on.

It seems like it could work. The reason why this is, in my opinion, is because it makes sense: you need people to do a repetitive task, and you incentivise them by allowing them to take parts of their town as their own. Maybe even think of a cooldown mechanic where a square cannot be retaken until at least a day has passed, or have two types of capture, nocturnal and during the day. There are a lot of possibilities from which a really nice game could come out of this. They also think of other, smaller details which I really liked, such as giving the player the option to create an avatar and customize it (yay, a use for those pesky points in gamification models!), creating “bonus squares” which need to be captured if a square is not specifically popular or an importance tier based on where noise patterns tend to change the most, such as in a town’s centre.

What I need to decide at the moment is if this model is better because it has been thought of with a more design approach or simply because the task is more fitted for gamification. I think that it’s a mix of both: repetitive tasks fit in much better with the model of “conquering areas” than one-off tasks, as was the case with Towns Conquer. It seems that although both teams have been given a similar brief and same key texts, this team managed to make a much better decision with their needs and came up with a gamified app which could easily be turned into a game, given some minor design attention. Good job!

Chris F.

Garcia-Marti, I; Rodrituez-Pupo, L; Diaz, L; Huerta, J. (2013). Noise Battle: A Gamified application for Environmental Noise Monitoring in Urban Areas. AGILE 2013 Available at 


Reading: Cathedral and the Bazaar

As I sit here, listening to Daft Punk, I ponder what I too from Eric Steven Raymond’s “The Cathedral and the Bazaar”. It’s a text that I’ve heard about before, while at ITO, and one that both Peter and Rob have recommended I read. Following their advice, I decided to do just that. So, what have I learned after this 40-page read?

First, I’d like to start with a summary. This paper contains 19 of Raymond’s teaching for advocating open-source software development. Here they are:

  1. Every good work of software starts by scratching a developer’s personal itch.
  2. Good programmers know what to write. Great ones know what to rewrite (and reuse).
  3. Plan to throw one [version] away; you will, anyhow. (Copied from Frederick Brooks’ The Mythical Man Month)
  4. If you have the right attitude, interesting problems will find you.
  5. When you lose interest in a program, your last duty to it is to hand it off to a competent successor.
  6. Treating your users as co-developers is your least-hassle route to rapid code improvement and effective debugging.
  7. Release early. Release often. And listen to your customers.
  8. Given a large enough beta-tester and co-developer base, almost every problem will be characterized quickly and the fix obvious to someone.
  9. Smart data structures and dumb code works a lot better than the other way around.
  10. If you treat your beta-testers as if they’re your most valuable resource, they will respond by becoming your most valuable resource.
  11. The next best thing to having good ideas is recognizing good ideas from your users. Sometimes the latter is better.
  12. Often, the most striking and innovative solutions come from realizing that your concept of the problem was wrong.
  13. Perfection (in design) is achieved not when there is nothing more to add, but rather when there is nothing more to take away. (Attributed to Antoine de Saint-Exupéry)
  14. Any tool should be useful in the expected way, but a truly great tool lends itself to uses you never expected.
  15. When writing gateway software of any kind, take pains to disturb the data stream as little as possible—and never throw away information unless the recipient forces you to!
  16. When your language is nowhere near Turing-complete, syntactic sugar can be your friend.
  17. A security system is only as secure as its secret. Beware of pseudo-secrets.
  18. To solve an interesting problem, start by finding a problem that is interesting to you.
  19. Provided the development coordinator has a communications medium at least as good as the Internet, and knows how to lead without coercion, many heads are inevitably better than one.

Most of these apply to computer programming, but there are a few that are of use to employers and business owners in general, and those are the ones that refer to ways of motivating your programmers or opening up the source of your program to the community. There are also a few of them which apply to designers, like the one which urges you to listen to other people as well, because their ideas might be great and you could use them, or discussion with others will trigger something in you which will become a great idea. It’s interesting that this paper mentions this, because without knowing about it, I was talking about the same thing in my 2012 start-of-the-year talk at UCS.

It was an interesting but tedious read for me, because other than the really good teachings that I mention above, it talks about a software development project using Linux. It’s great to see the iterations that his software went through, and understand how development works within the open-source community, but it seemed very familiar and akinto what we do at the Computer Games Design course when we use the AGILE methodology. We iterate and release often, listen to feedback from our users, and reiterate based on it, which makes me think that AGILE is derived from this method of development and delivery.

It’s a great source for understanding why open-source development is great, and the lessons are interesting, but that’s about all that I got from reading it.

Other than the quotes from above, the thing that I found most interesting in this paper was an annex at the end of the paper, a sort of revision, that was made a few years after the original release of the paper, after the guys from Netscape decided to release the source for their browser which ended up to be what we now know as Mozilla (whose Firefox happens to be the browser I am writing this on at the moment). It seems that they had some really big problems at the beginning, because Netscape still clung unto the Cathedral model too much, releasing stuff only when they believed it was done, which Raymond says it’s at the same time a great example of how awesome open-source development can be and how can it fail. Like we all know at the moment, the Mozilla project was highly successful, with their browser being in the top 3 most used browsers in the world, and the Mozilla Foundation working at the moment on the release of their phones and mobile operating system, as well as developing a tablet. The quote that got to me, and that, again, I’m glad I have found because I can now quote it properly instead of saying “I thought of this” (which, as we all know, is not permitted in an academic environment), is that “Open-source is not magic pixie dust” (Mozilla project principal, after resigning). This is what I keep talking about when people tell me that gamification will revolutionize the world. Yes, just like open-source software, the possibility exists and it’s there, but it’s not magical. It requires quite a lot of work and achieving what I call “high gamification” in order to have a successful gamification model. Just like with any other game, it takes time, iterations and testers in order to have it become good.

Hopefully, over the course of the year, I will be able to prove this to be true.

Chris F.

Raymond, E.S. 2010. Cathedral and the bazaar. La Vergne, TN: [SnowBall Publishing].

Reading: Cheater’s high

I came by this journal article while I was watching an internet show, but it’s a really interesting one. Recently (read in the past month), a journal article has been published in the Journal of Personality and Social Psychology which shows proof (laboratory experiments) which confirm something that most of us already knew: cheating when you’re not aware that you’re hurting another person, makes you feel good. It’s a very interesting 20 page article, and it raised some interesting points, which I believe will help me with my dissertation.

The first things I have learned is that these researchers are doing a study on the possible benefits of unethical behaviour, and while there have been many studies before into this area, apparently only one other study actually took into account the possibility of people having a positive affect from behaving unethically, all of the others focusing on the negative affect of behaving unethically. A bit disturbing was reading about how most of the other experiments in unethical behaviour had people inflict harm to other people(usually via electroshock application), and then measured how they felt afterwards. Other than one or two of the other mentioned studies here, which focused on cheating organizational systems like the US tax collection, nobody thought to do research into why people cheat on minor stuff, like games or time sheets, and that’s what this study set out to experiment with. They created 6 experiments through which they analyzed different types of stimuli and conditions in which their subjects might want, could or had to cheat, and then gave them a test to see how they felt about themselves, after doing the same test before the cheating happened.

I will talk about the experiments themselves in a bit briefly (not too interested in all the math-statistic-y stuff), but I found the introductory section to be very interesting, as well as the possibilities that arised in the wake of my reading this.

Another revealing concept that I have found by reading this article is the existence of two states of the human mind, these being the “should” and “want” states, with the “should” state being the idealist, future-looking persona that we have, the one that looks to the future and says that it would like to have something, while the “want” state is conditioned by much more immediate factors and tends to be impulsive. They illustrate it by saying that the “should” state starts you on a diet but the “want” state is the one who eats a cake in the first day of the diet, because it looked delicious.

Related to the two states, an interesting observation is made: “if an individual is not attentive to long-term consequences, unethical acts may fail to induce negative affect in the moment in which an individual makes a decision”, which I’m pretty sure is something that people who run gambling and scamming operations are intrinsically familiar with when it comes to their customers. Make them think in the present, never further than that next hand, keep their eyes on the prize, and they’ll keep playing. This whole paragraph comes after the writers of the article have read about how, if a person believes that something will cause them a negative affect, they are less likely to do it.

Coming back to the reason for which I find this article to be very interesting, it mentions (backed up by previous study) that one of the reasons why people might cheat is to have a “sense of greater autonomy and influence”, to “circumvent rules by which others are bound”(my emphasis) or to “take advantage of other people’s decisions by manipulating the information by which they are making those decisions”. All of these seem to me reasons why people cheat in games and deceive others. As animals, we want to win. As humans, we want to feel special and superior, and of course we will feel better if we believe that we are better than other humans because we know something they don’t know, especially if it’s something that circumvents the rules by which we are all bound, making us more free or giving us an edge, even if it’s just imaginary or something minuscule. We want to feel special, dammit, and if being able to save 2p when I’m shopping for £50’s worth of stuff, then I’ll do it! It’s one of the psychological strategies that marketing people use.

A nice story that the article tells is that of a cashier that “consistently embezzled from her register. She said that she did it because it gave her new goals and a sense of challenge”. I love this, as it proves that when people are faced with what seems like boring jobs, they tend to make games out of it. We could take this a step further and say that she was a game designer without knowing it, really. I’ve seen this done time and time again, people creating games and making their own rules in order to find something challenging in a really mundane job or situation, like staff meetings or a lengthy speech by the school leader when you place bets on whether she’s going to mess up the name of the new member of staff. All of these are small games that we set up for ourselves, and as for the cashier, we could say that she was playing with high stakes, trying to game the system. She knew what she did was not allowed, it wasn’t “inside the rules”, but she did it anyway because she found it fun. This is the reason why I’m a bit taken aback that before 2012 nobody thought that people cheat for fun.

One of the authors cited in this study mentions that “the euphoria of getting away with [cheating] overshadows the material gain”. This quote is very interesting, because it ties in with one of the articles that I have mentioned before, the one about crowding motivation in and out. Corroborated with what that article talked about in regards with the highest amount of work happening in work places in which the rules are lax, it seems to me that if you create a system in which people are allowed to cheat and get away with it, but not gain an over-powered advantage, you might end up getting more out of your employees/players/users than if you enforce very strict rules. People don’t like always being told what to do, and, as I’ve mentioned in the paragraph above, when we’re given rules, we’re trying to find ways around them. If the rules are guidelines or don’t exist, there’s nothing else to do but focus on our actual work or game. To summarize, “let them cheat, if you’re not losing much”.

The next 10 or so pages go through the 6 experiments which the researches have created and put people through in order to demonstrate their theory. They use a lot of math and statistics and PANAS and ANOVA tests and things I don’t really find that interesting in order to measure how people feel before and after cheating. What I did find really interesting about their methods, though, was how they created the tests. They started with a simple, template test, and then iterated. Each time they were reiterating an experiment, they identified a risk in the results of the previous test, isolated why that risk existed in the experiment mechanics, and then changed that, hoping for more accurate results, which is exactly what we’re doing when we’re creating games and making iterations on them. They played with the concept of cheating, with taking away the choice of cheating from the user, with working with and without financial incentives and a few other factors. It felt like reading a game design document to go through the experiments, chronologically.

Another interesting concept that I came about when reading through the experiments was that after the first experiment, the researchers thought that maybe non-cheating people felt better about themselves because they chose not to cheat, after seeing almost identical results in self-perception from both cheaters and non-cheaters. I was a bit dazed by this because I did not take this into account: it’s a user’s decision if they cheat or not and yes, maybe some of them will feel better for choosing not to cheat. It is, after all, a meaningful decision, and the players will be affected by it. In order to take this decision away from the people who participated in the study and better isolate the “cheater’s high”, the researchers iterated the experiment into a position where the subjects couldn’t choose to cheat or not, they had someone else give out higher numbers in a test they took. Like this, the choice was taken away from all the users, and some of them cheated by default, because the experiment demanded it. The people behind the study then still got inconclusive results, but attributed them to the possibility of having the “cheating” group feel better because they felt that they out-smarted the person who gave the researchers the inflated results.

In the end, after 6 experiments, the researchers found that there is an element of positive affect when a person cheats, but concluded that more experimentation needs to be done in order to see if it can be better isolated and to understand how it applies in different situations. One particular situation that I find intriguing is to see if cheating as a group has a bigger effect on people, because the possible guilt would be spread among all the other “accomplices” instead of one person.

All in all, one of the best reads I’ve had so far, and one that opens up a whole lot of possibilities for my dissertation, especially since it seriously made me think if I should leave some loopholes open for the players to find and exploit, to make them feel better. You have to understand that in a crowd-sourced game, it’s hard to isolate someone who cheats lightly, and, as I was mentioning in the Towns Conquer post, if you create a leaderboard or any other way of people to identify that they are better than others for a project like OpenStreetMap, people might just add random inaccurate information to the system just to gain points, which is unacceptable in such a situation.

Chris F.


Ruedy, N., Moore, C., Gino, F. and Schweitzer, M. (2013) ‘The Cheater’s High: The Unexpected Affective Benefits of Unethical Behavior’. Journal of Personality and Social Psychology, 105 (4), pp. 531-548 DOI 10.1037/a0034231. [Available at: Last accessed 24th October 2013]

Reading: Towns Conquer paper analysis

I’ve found this paper while I was searching for “Gamification in Volunteering Geographical Information” on Google Scholar because I needed a reference. It seemed like an interesting paper, being linked with all the concepts that I’m studying, and I wanted to find out more, so I downloaded the paper.

A bit different than THIS type of town conquering

It’s a basic paper, much like the original “Gamification in VGI”, in which a few students from Spain decide to make a gamified application for Android and web which will allow users to input the names of Spain’s many provinces, in hopes of cleaning the official Spanish dataset with the names, and completing it with more local knowledge. The reason behind this is because Spain has a lot of dialects of Spanish/Portuguese and the writers of the paper wanted to find out more about names of certain regions, based on the dialects.

The paper starts by mentioning that crowd-sourcing is a really important concept, empowering the citizen, and that they would like to use it in this project, in conjunction with gamification. They mention OpenStreetMap and WikiMapia (first time I’ve seen Wikimapia in an academic paper till now) as examples of crowd-sourcing. It also states that the disadvantage of OSM is “reliance on small communities of “Neo-geographers”” and that their project “aims at tackling these problems by providing alternative motivation specifically a smartphone based computer based game service”. It looks like they didn’t do a lot of research into OSM and all the game apps that I’ve been talking about over the past few weeks.

They then go on to talk about the problems that they hope to tackle through this project and mention that they plan to use gamification. The authors reference Zichermann’s SAPS model and Bartle’s player types without going further than mentioning them as something they’ve looked into.

A description of the app is next. The application will be a map with all the provinces of Spain, which will prompt the user to choose from a list of 3 names for a province, or having the 4th option of inputting them themselves. For each input, the user will receive one point, and the user with the most points in a province “conquers” that region. They mention that the users will begin at lower administrative levels(municipality->province->region), and make their way up, conquering along the way. There will also be badges, and that the game will be released in a few months on the Play Store (paper was published in May, couldn’t find anything on the Play Store).

Although stating that the purpose behind this is to get as many inputs as possible, after which they will compare them with the official datasets and ask an IGN (equivalent of Ordnance Survey?) officer where conflicts arise, I need to ask myself how many of the users will play fair? The good thing about OSM is that the sheer number of users doesn’t usually allow for a mistake to stay in the map for long, especially in areas with a high density of active users. Another good thing about OSM is the user interaction. I add the name of a street, someone else can modify what I’ve done or add more on top, like sidewalk information or speed limits. With their example, the interaction between users is minimal, with the only thing that users can do being to see what someone else has conquered. It also looks like a user can get a maximum number of points, with 1 point for each region that they name, meaning that after a while, a lot of the users will have the maximum points possible, which leads me to ask what happens when a region has 5 users with the maximum number of points. While I really like the idea of having only a simple radio button layout with a text input for “other” as the forms of input, it also looks like people could just cheat so that they would win the province, and the paper doesn’t talk about that. Also, although it mentions Bartle’s player types, it does not talk about which of those types the game would be for, or how they would motivate the different types to take part in the game.

As a game designer, these are the things that I would like to know when you tell me that you have an idea for a game, especially a non-traditional game like a gamified crowd-sourcing application. Maybe I’m asking for too much. What I did learn from this paper, though, other than an interesting name for such a game, is that as a game designer, I cannot let my dissertation be as lacking in information as this here paper, when it comes to game design concepts. I can’t just skim over gamification as a concept or the mechanics, dynamics and aesthetics of the game that I will be creating, those need to be the core of it. I might skim over the technical aspect, as I’m not a computer science student like the guys in Zurich, I might skim over the more complex geographical aspect of it, since I’m not a geography student, but I absolutely can’t skim over the game design aspect of it, since I’m doing a Games Design course.

Chris F.

CASTELLOTE, J., J. HUERTA, J. PESCADOR and M. BROWN. Towns Conquer:A Gamified application to collect geographical names (vernacular names/toponyms)Anonymous AGILE 2013, 2013. Available at: Last accessed: 24th of October, 2013

Reading: Motivating children to read

Throughout the journal articles that I’ve saved for researching motivation is one that I’ve found interesting not because it sheds some much needed light on my dissertation per se, but because it stands to show that different target audiences require different motivators. This article is written by Amber Gear, Rhonda Wizniak and Judy Cameron at the University of Alberta, and it’s called “Rewards for Reading: A Review of Seven Programs”.

It’s a really short journal article which analyzes 7 different reading programs for kids from kindergarden to grade 6 (7-12 year olds) based on how the reward systems for them were created. I guess you could argue that they were “gamified” and in fact, the study does mention a system that’s similar to leveling up, but I’ll get into that shortly. What I found interesting here were the following notes, based on other research, which mention the factors that influence a good reward system in reading programs.

  • the rewards involve spontaneous and sincere positive feedback and praise;
  • students are rewarded often and immediately following successful
  • students are given occasional unexpected rewards;
  • tangible rewards (e.g., prizes, grades, stars, etc.) are given for meeting clear performance standards;
  • tangible rewards are given for succeeding at increasingly challenging tasks;
  • tangible rewards are items students enjoy (e.g., books, computer games);
  • students are involved in setting up the reward system;
  • student performance is recorded and rewards are phased out when
    behavior increases
  • All of the above are really useful in part of my research, mostly because it shows that people were toying with game-related ideas from before the gamification term was coined, but also because it creates an incentive-creation framework that I can then take and adapt to my own purposes, if I ever were to work with children of those ages or equivalent people. All in all, it’s a nice list. Here’s my thoughts on it.

    I will start with the easier ones:

    tangible rewards are items students enjoy (e.g., books, computer games);

    Make sure that your target audience likes the incentives that you’re giving them. This is probably the most obvious one, but from what I’ve seen in real life it’s often forgotten, most marketers choosing to take the easy way out of offering money as rewards because everyone wants money and they forget that they might get a better-focused audience if they were to give more targeted rewards, i.e. you can give £1000 to a farmer for winning a prize, and hope he will buy a tractor, or you can give him a tractor to begin with, especially if you’re creating your competition with farmers who want a tractor but don’t have one in mind.

    students are rewarded often and immediately following successful

    tangible rewards (e.g., prizes, grades, stars, etc.) are given for meeting clear performance standards;

    These 2 work hand in hand and they draw on basic game design concepts (no, Pavlov, I’m not forgetting you, just trying to make a point): your player needs to know what his actions do, and every time they do that action they should see the same reaction, i.e. pushing the up button will always make your character jump 5 pixels. It works the same with this list as well. When a student meets a clear criteria set for them, they are rewarded “immediately”. For each book read, you get $1 after writing a review for it.

    Now we’re getting into the more interesting concepts of this list:

    the rewards involve spontaneous and sincere positive feedback and praise;

    As I was mentioning in my previous reading post, tangible rewards are not the only way forward, especially when you want to work on someone’s intrinsic motivation, like reading a book for the sake of enriching your knowledge or taking part in an adventure. This is why I find this point very important: you shouldn’t just give kids $1 or a cheeseburger when they’ve read a book, because after a while they will think that the only thing they’re losing by not reading a book is that $1 or cheeseburger, and not all the knowledge in the book and act of reading.

    students are given occasional unexpected rewards;

    This is one that I’ve seen a lot in talks about Facebook and social games that exploit the freemium scheme. You give your players a seemingly random (for them, not for the designers) reward of something that’s consumable but really rare in order to give them a taste of it, and then you remember them of it to buy it. This point on the list is not that creepy (really now, out of context it seemed like a drug dealer tactic), but it attaches to the same type of human behaviour: we like surprises, and if we are given a surprise reward for doing something, we tend to do that thing more, hoping to get another surprise reward sometime in the future. As I’ve mentioned, these “occasional unexpected rewards” are something that the designer has included in the game, but that the player has no way of knowing about if they haven’t played the game before.

    tangible rewards are given for succeeding at increasingly challenging tasks;

    student performance is recorded and rewards are phased out when
    behavior increases

    Student performance is recorded -> leaderboards, if they are displayed publicly. The other two, though, are much more interesting. Students are given rewards for succeeding at increasingly challenging tasks, but at the same time rewards are phased out when behaviour increases. This is a leveling up system right here. Put experience and levels in the mix, and that’s it. A student gets $1 for the first 3 books read, but then you give him a longer book to read, and he can be seen as having leveled up. So take into account phasing out rewards, and you’ll see that you give him $5 for the next books read, but only after he’s read the new, more challenging books. He needs to put more effort into it, but at the same time, the reward is greater.

    The last point on the list is one I really like:

    students are involved in setting up the reward system;

    By including the students in setting up the game, or a part of it, such as the reward system, you’re giving them the most important thing that a player can have in a game: meaningful choice. Even if you can only give them candy, at least let them select the flavour, and they will feel like they’ve done something, like they’ve had a say in it and will be more inclined to participate in this, because they did something for it.

    The article then goes on to put 7 different reading programs into a table and awarding each of the programs a tick for the points on the list they respect. Interestingly, most of the programs examined keep detailed records to track student progress, the rewards are items that students enjoy, and praise is given, while none of the programs phases out the rewards when reading increases. The first part of the statement shows that schools know to keep track of students and tell them to strive harder and praise them, as well as understanding the basic wants of a 2004 kindergarden student. The latter shows one of two things, in my opinion: either in 2004 tutors weren’t that familiar with the above-explained concept of leveling up or it did not occur to them that they could use it to motivate advanced students. As someone who has done some teaching before, I understand that a class is made up of mixed people of varying levels of skill, and that the best students of some classes will get bored if they’re left behind, so you need to give them something more challenging to do while you work with the ones who have less skills or learn differently.

    I’ve really enjoyed this short reading, and I actually believe that this blog post is longer than the article itself. Really liked the list and I’m looking forward to see if I can apply parts of it to my projects from now on.

    Chris F.


    Gear, A; Wizniak, R; Cameron, J. (2004). Rewards for Reading: A Review of Seven Programs. The Alberta Journal of Educational Research. 50 (2), 200-203. Available at: [Last accessed: 20th Oct. 2013]

    Reading: Crowding out and crowding in motivation

    I’ve started reading on why people do things in order to better understand the rewards and how they would work for my dissertation. In my travels through academic journals, I found an interesting one by Bruno S. Frey, written in 2012. In his article, he discussed the concepts of “crowding out” and “crowding in” intrinsic motivation. He starts by explaining what the concepts are, then goes on to discuss the different types of motivation and afterwards gives examples of how different rewards have had diverse effects on intrinsic motivation. What I find really concerning at this point in my dissertation is that I realize that in order to experiment how rewards work in the real world, they actually had to apply them to real-world scenarios, using real-world people. They experimented concepts of psychology, more or less, on real people, and in at least one of the cases that I will write about below, it turned out not so good. As a future graduate, it makes me a bit nervous that what I will do will have real world applications and effects that might be positive, but especially that they might be negative. No pressure, Chris.

    So, what exactly is crowding in and crowding out intrinsic motivation?

    Crowding out – taking a crowd of people out? Maybe they got free crumpets

    They are concepts taken from economy (who said Games Design is a narrow field?), and according to Frey, they appear in relation to external reward systems and intrinsic motivation like so:

    1) External intervenions crowd-out intrinsic motivation if the individuals affected perceive them to be controlling. In that case, both self-determination and self-esteem suffer, and the individuals react by reducing their intrinsic motivation in teh activity controlled.
    2) External interventions crowd-in intrinsic motivation if the individuals concerned perceive it as supportive. In that case, self-esteem is fostered, and individuals feel that they are given mroe freedom to act, thus enlarging self-determination.

    Frey goes on to talk about the consequences of the above on the labour market. He states that, according to text-book economics, if a worker is paid more, he will perform better. According to recent studies, however, that may not be true. What these have found out is that, based on the work that a person does, sometimes better pay can actually decrease the efficiency of a worker. 128 experiments have been carried out, and the results showed that tangible rewards have a significant negative effect for interesting tasks. However, verbal rewards have a significant positive impact for intrinsic motivation. Tangible rewards do not crowd-out intrinsic motivation when they are unexpected or not contingent on task behaviour. The conclusion of the experiments is that the main negative effect of tangible rewards is that they undermine self-regulation and that people take less responsibility for motivating themselves.

    In other words, you’re getting paid to do what you’re doing, so it doesn’t matter if you show a genuine interest in it or not. The case studies of this theory are really revealing.

    I will only discuss 2 of the examples that Frey gives. The first one is the frightening one that I mentioned earlier: at a day-care center, parents were sometimes late when picking their children up, and teachers had to stay over the scheduled time in order to wait for them. What the management decided to try and do was to enforce a penalty for the parents who were late, and fined them for “a substantial amount of money”. What the normal economic theory predicts is that less parents would be late in picking their children up, for fear of being fined. However, what happened is that more and more parents came late to pick up their kids. They were no longer motivated intrinsically to do this, by shame or something similar, but instead thought of the fine as a “I can come late” tax, which they could afford to pay. What scared me with this example is that although the experiment was carried out for only 12 weeks and then stopped, the rate of late picking up did not decrease but remained at a steady level. In Frey’s words, the parent’s intrinsic motivation had been crowded out. This scares me because something actually happened in those parents’ minds as a result of the experiment which made them care less for their children.

    The second example is one that has to do with airlines. According to the studies cited in this journal article, the airline which has the least delays is the company which reports the delay as a “team delay”, instead of a “engineering delay” or “pilot delay” or anything else which singles out either a person or a group of people. What I believe happens here is that by knowing that you won’t be singled out if something bad happens, you will try more to better yourself. If you do a boo-boo, the whole team takes the blame, not only you, so you should work as hard as you can and help others, because you have nothing to lose, as opposed to the singled-out model where you might not want to help out a colleague who’s in a bit of a muddle for fear of having the fault falling on your head.

    Frey also cites another one of his own studies which mentions that offering tangible rewards for task efficiency in a volunteering program has reduced the efficiency of the whole program vastly, because volunteers are not motivated by external rewards but by their intrinsic motivation.

    What I took from this article is that people do some things because they want to, because they are intrinsically motivated, and great care should be taken with the reward system, especially in a crowd-sourced project like OpenStreetMap, because it might prove to do more harm than help. People work better if you show support for them, allowing them some creative freedom, showing interest in their passions. Financial or tangible rewards based on how well a person performs their task might make that person work for the reward instead of the reason why they started working in the first place, and as such, reduce their motivation and performance because, to be an incurable romantic, they no longer do it from the heart. Another thing that I liked from this article was that people kept working as hard as before if they were given unexpected tangible rewards. This ties into how people like it when they are being surprised, and will love the one-off reward. In the end, I believe this study shows, among other things, why the “Kill 10 wolves”, “Kill 50 wolves”, “Kill 100 wolves”, “Kill 1000 wolves” progression doesn’t work in lazy MMORPGs

    Chris F.

    Bruno S. Frey. (2012). Crowding effects on intrinsic motivation. Renewal : a Journal of Labour Politics. 20 (2/3), p91-98.

    Crowdsourcing: what is?

    My dissertation will be about crowd-sourcing and gamification. These two usually go hand in hand, but I realized that I haven’t talked much about crowd-sourcing on my blog. The thing with focusing on newly defined concepts is that you can’t really find that many books on it, and if you find any, generally they don’t have it in the library because it’s so new and nobody thought of buying it yet. So, in order to research fields such as gamification and crowd-sourcing, I find myself using Wikipedia and the internet in general more and more.

    From my research, I have found out that what I knew about crowd-sourcing was mostly right, with small modifications. Generally speaking, crowd-sourcing is giving a bunch of people a task, and having them resolve it. You can have lots of ways of distributing the tasks, and different audiences for them, from people who are specialists in their field to “unqualified” workers who do very simple tasks, but the main idea remains the same. A more academic definition for crowd-sourcing, according to Enrique Estellés-Arolas and Fernando González Ladrón-de-Guevara is:

    Crowdsourcing is a type of participative online activity in which an individual, an institution, a non-profit organization, or company proposes to a group of individuals of varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary undertaking of a task. The undertaking of the task, of variable complexity and modularity, and in which the crowd should participate bringing their work, money, knowledge and/or experience, always entails mutual benefit. The user will receive the satisfaction of a given type of need, be it economic, social recognition, self-esteem, or the development of individual skills, while the crowdsourcer will obtain and utilize to their advantage that what the user has brought to the venture, whose form will depend on the type of activity undertaken

    There are many examples of crowd-sourcing, with more appearing as companies realize that this is a VERY cheap way of getting logos (Toyota and Obama) or bottles (Heineken) designed. I believe that the design crowd-sourcing examples are not necessarily relevant for my work, but I thought that they would be good examples. What is important for my dissertation as an example is that Wikipedia is crowd-sourced and OpenStreetMap is crowd-sourced. Other good examples are Waze, a gamified crowd-sourcing app recently purchased by Google, Duolingo, an app that aims to translate the internet and Crowdfynd, a crowd searching app. What all of these have in common is that they don’t give users real-world rewards, but rely on the intrinsic motivation of people who use them. The users of these applications and contributors to these projects are doing so for their own motivations, from trying to prove someone right by showing them a Wikipedia article modified by yourself to knowing that you’re helping others and improving the world in general.

    I should note here that I’ve found an article about Nokia’s launching a crowd-sourcing project for their HERE maps. Although at the moment the project is only open to “experts from local communities”, it’s interesting to see them joining on the crowd-sourced maps bandwagon 7 years after OSM and in the same year as Google, which may have had more impact on this decision.


    Estellés-Arolas, Enrique; González-Ladrón-de-Guevara, Fernando (2012), “Towards an Integrated Crowdsourcing Definition”, Journal of Information Science 38 (2): 189–200

    Reading: Gamification of geographic data collection

    The first new reading for my dissertation is one that I’ve got from an actual tutor while I was attending State of the Map, the international OpenStreetMap conference at which I’ve held a talk(my part starts at 1:33:00) about the risks and rewards of gamification in data entry. It’s a paper called “Gamification of geographic data collection”, written by students at the University of Zagreb.

    It’s an interesting paper, written as an introduction to gamification concepts for people in the GIS (Geographic informational systems) industry. It starts by defining gamification and the SAPS (Status, Access, Power, Stuff) model, then goes into defining the different types of motivation. After talking about intrinsic and extrinsic motivation, different game mechanics are described, such as levels and badges. The authors wrote a short summary, looking at the SAPS model on existing GIS gamified approaches: Foursquare, Waze and Ingress, which have (or used to have, in Foursquare’s case) proprietary data, and OpenStreetMap Reporter and Kort, which are OSM improvement efforts, with Kort being an application developed by students at the university of Zagreb.

    While I was familiar with the game design concepts expressed in it, such as game mechanics, points, badges, leaderboards, challenges, onboarding and engagement loops, I’ve learned some terms which I did not know about, such as Volunteered Geographic Information (VGI) and Location Based Services, Gaming and Social Networks, which tie in beautifully with the games and applications that I will look into when it comes to adding and fixing data from OpenStreetMap.

    Additionally, this paper has given me a few more related papers and books which I will research, such as Hecker’s “Achievements considered harmful” and Sutton’s “Holiday OpenStreetMap project for Swellendam”.

    Odobašić, D., Medak, D. and Miler, M., 2013. Gamification of Geographic Data Collection. [online] Austrian Academy of Sciences Press, pp.328–337. Available at: [Accessed 3 Oct. 2013].