Module: AG0982A - Creative Research

This blog documents my 3rd year research project at Abertay University. The focus of my research is on video game progression, tutorial design, and how to teach the player. My vision statement could be stated as such:

A game often needs to gradually introduce its mechanics and skills to the player. This needs to be done at such a pace that the player is neither anxious nor bored, and needs to be clear without sacrificing challenge. How can this balance be achieved? To investigate this, I've created a simple puzzle game, and released it to a sample of players. I can use data from their feedback to improve my game.

This issue came to my interest when I noticed that many games do a superb job of gradually teaching a player how to master a complicated system (such as Portal), while many other - often more complicated - games are lacking in comfortable and effective tutorship (such as Crusader Kings II), forcing players to resort to online wiki reading, and YouTube guides.

Thursday, 3 December 2015

Feedback On Presentation 2

After presenting my plans for a second time to the class, I received feedback. This feedback addressed my plans towards the conclusion of this project. Currently, I hope to address ideas about tutorials - such as the ideal shape of an excitement or learning curve, whether it requires a "hook" at the start, or whether covert/overt tutorials are preferred by the player. I can draw conclusions in these areas by releasing my game, and reviewing user data scientifically.

However, my tutors reminded me that this would be a difficult task, and that my game only represents a single type of game. Findings from this game might be highly contextual, and not applicable as general rules. With this in mind, I should focus my research on understanding my game in particular, rather than all games and how a designer should approach their tutorials.

Wednesday, 28 October 2015

The Oscillating Flow Model

Mihaly Csikszentmihalyi proposed the 'flow' model as a psychological explanation of an extreme state of joy/focus. He developed the model by studying the work process of painters, many of whom did not expect their art to be profitable, and many of whom lost interest in their work once they were done with it. This raised the question: what was motivating the painters to paint? To answer this question, Csikszentmihalyi developed his flow model, which assumes that human attention is a sort of limited resource, and that people enter the state of flow when their attention is entirely focused on achieving a task (Csikszentmihalyi, 1988)

Csikszentmihalyi's model has a lot to say about human consciousness, and the concept of the self, and how these agents may have evolved. But of the greatest interest to game designers is his assertion that ...

"The universal precondition for flow is that a person should percieve that there is something for him or her to do, and that he or she is capable of doing it." (Csikszentmihalyi, 1988, p.30)

... and, furthermore, that there must be a balance between the skills of a person, and the challenge of the task they're facing, for flow to occur. Too much challenge, and the person is anxious. Too little, and the person is bored. He goes on to explain that flow will cease when an activity's challenge is exhausted. Thus, tic-tac-toe is easily mastered and discarded, but chess remains interesting for centuries.

Flow can be expressed in a graph, like this:

Jesse Schell - mentioning this model - takes it a step further. He argues that, though acceptable, a linear increase in difficulty will be less interesting that an oscillating one. This sinusoidal relationship between challenge and skill - such that the flow's trajectory is punctuated by moments coasting anxiety and moments coasting boredom - can be seen in many games, and will feel more satisfying to the player. Schell gives the example of a shooter where the player is given a weapon. The player must use this weapon to fight an increasing number of enemies, and overcome increasingly difficult challenges, until they eventually pass the most difficult challenge and the 'crest' of the flow oscillation. Following this, the player is given a new, more powerful gun, providing momentary relief of challenge, which rewards the player's efforts. This relief is soon met with increasing challenge again (Schell, 2015, p.141).

This version of flow can also be expressed as a graph:

With this in mind, I'm hoping to create a game that emulates at least one oscillation in the flow channel. The game should begin easy, then ascend to a more difficult level.

- Csikszentmihalyi, M. Csikszentmihalyi, I. S. 1988. Optimal Experience: Psychological Studies of Flow. Cambridge: Cambridge University Press.
- Schell, J. 2015. The Art of Game Design: A Book of Lenses. 2nd ed. Boca Raton: CRC Press.

Thursday, 15 October 2015

Csikszentmihalyi's Flow Model

The flow model is a psychological model about motivation and learning. It's a recurring tenant of my creative research. Developed by Mihaly Csikszentmihalyi, it describes a mental state of extreme focus and joy, called 'flow'. For Csikszentmihalyi, flow is a very central and important emotional component of our lives, but I'm more interested in how it applies to learning, and skill. Below is a graphical representation of flow seen in Csikszentmihalyi's book.
The graph's axes represent the skill of a person performing a task, and the challenge of that task. If the person's skill far exceeds the requirements of the challenge, i.e. if the person finds the task very easy, the resulting emotional state is boredom. Conversely, if the challenge is beyond the participant's skill level, this person will be anxious, or frustrated, with the task. Neither are preferable emotional states, but between these areas is the 'flow channel', where the degree of challenge in the task matches the person's ability to complete it; the challenge is difficult enough to demand the application of their skill, but not so difficult that it is beyond their abilities. Just as a low-skill individual would be happy to complete low-skill tasks, a high-skill individual could perform high-skill tasks and still be in flow.

The implications for video game design can be simply stated as this: at any given time in your game, the challenge given to your player must be neither too easy, nor too difficult for their skill level. In order for the player to actually enjoy solving the problem, the game must match them with an adequate challenge. Examples in video games of all kinds are ubiquitous. Skyrim is often criticized for having dungeons and monsters that do not increase in complexity or skill. The player may find Skyrim's dungeons a lot of fun at the start of the game, but as they level up and unlock new abilities, in addition to just becoming better at handling the game's combat encounters strategically and reflexively, the skill-to-challenge ratio quickly falls into the boredom zone. But in Crusader Kings II (CKII), a grand strategy game set in medieval Europe, the player is advised by the game to begin a session as the Duke of Normandy, or as King Harold of England, right in the heat of the English war of succession. Navigating this event skillfully requires a good understanding of Crusader Kings's war mechanics, city building, complex political gameplay, and many more elements that a new player - or even a seasoned one - will not be ready to employ. Such an experience easily falls into the anxiety section of the graph, and will likely result in a frustrating and confusing first game of CKII, possibly resulting in the player never trying to play again. All this happens because the game actually suggests that a new player should try to play as these characters, rather than a much easier, much slower-paced and smaller scale start as a duke of Ireland, or vassal of a larger kingdom. In addition, as the game is tailored around historical accuracy, CKII quickly employs gameplay surrounding the crusades and papal politics, long before a novice player has even had a chance to learn some of the basic mechanics.

The game I often cite as a masterpiece of well-paced challenge is Portal. Portal's core mechanic centers around jumping through portals to complete spatial puzzles. With such an unintuitive and unheard of task, employed to solve difficult logic puzzles no less, you would expect the game to suffer from an even less ideal learning curve than Skyrim or Crusader Kings II, as the designers may attempt and fail to predict the player's progressive understanding of a complicated mechanic. But in fact, Portal progresses quite smoothly and quite comfortably for most of its players. It begins with some simple levels that exhibit the basic concept of wall-mounted portals, before handing the player a portal gun that can fire just one portal, then two portals, moving on to introduce momentum and jumping puzzles, weighted cubes, and hostile turrets. Portal finally tests the player's skills in all of these areas, with a series of complicated tasks that include all previous aspects, before one final 'boss' puzzle. These final challenges only occupy the last quarter of the game, thus the common observation that Portal is 90% tutorial. In my experience, most players manage with each puzzle just fine. The game rarely dips into boredom or anxiety. It remains in the flow channel, adjusting the required challenge at roughly an equal rate to the player's progressively increasing skill.

How does Portal manage to stay in the flow channel, where Skyrim falls into boredom, and CKII into anxiety, along with so many other games? Csikszentmihalyi provides some functional guidance to encouraging flow. First, he identifies attention as the primary resource of a person performing a difficult task. He literally analyses it as if it were a resource; the psychological equivalent to physical energy. If several things are on a person's mind, that person is not applying themselves fully to the task at hand; Csikszentmihalyi calls this a state of 'psychic entropy'. If most or all of someone's attention is being applied to just one challenge, however, then the inverse emotional state is achieved - that state being flow. In this somewhat drawn out analysis, Csikszentmihalyi is basically summarizing one of his eight identified characteristics of flow. Four of these characteristics are actually conditions for flow, so I'll talk about these.

1. The task must be possible to complete.
2. We must be able to concentrate on what we are doing (as elaborated on above).
3. The task's objectives must be clear.
4. Immediate feedback must be provided.

It is interesting how closely these correlate with some principles I'm already familiar with in game design. Principle one, for example, is essentially a rephrasing of the 'options principle', 'counter-play', or the law of feasibility. The player must have a chance of actually succeeding at the task you give them. An impossible task is absolutely no fun, and an improbable one is also quite frustrating. This seems simple enough, but I've found that the lack of the options principle appears in unexpected places. For example, in a competitive multiplayer game. If one player is losing, and nothing can be done to actually turn the game in their favour (i.e. there are no options), the result is an extremely frustrated player. A game designer needs to ensure that in almost all situations, the player has the ability to achieve their task.

Principle two is very encompassing and quite abstract. Csikszentmihalyi means it in the sense that an untroubled personal life leaves someone free to focus on their professional work. Game designers don't have much control over their players personal lives, so this principle can only be applied to the game itself. Clean graphical user interface, and avoiding flooding your player with side-quests, are possible examples of this principle.

I find principle three extremely relevant to tutorial design. Nothing can shut down a player faster than not knowing what they're supposed to be doing, or not understanding how to do it. I experienced a good example of this only a few days ago, playing a horror game called Monstrum for the first time. Monstrum is reminiscent of Amnesia; you navigate corridors and rooms, searching for items and avoiding a frightening monster. However, during my first game it was never made clear to me how I was supposed to finish the level. What was I looking for? What were the win conditions? Without a target to actually aim for, my gameplay was much less engaging. At the same time, this principle crumbles a little when we consider that the challenge in many games, puzzle games in particular, lies in not knowing exactly what to do. In Portal, it is clear that you need to reach the end of the level. What is not clear is the specific steps needed to achieve this goal. The whole fun of the game is figuring out these steps. So I believe the third principle is a balancing act; the player needs an objective, but an unclear path between them and the objective. And again, going pack to principle one, it actually needs to be possible to figure out what this path is.

Finally, principle four is a classic game design imperative. Reward your player for achievement, punish them for failure (but don't punish them too hard). What constitutes a reward, and why a reward might be enjoyable, is an entirely different issue, so I'll just leave it at that for now.

Flow has been employed and investigated by a few game designers, to my knowledge. An excellent example of this is the game flOw, created by Jenova Chen and Nicholas Clark, and I can only assume named after the theory itself. flOw features a microbial snake/worm character swimming around and eating smaller creatures. The game does have levels, each one progressively more difficult, but the player is given the freedom to move between these levels as they see fit. To ensure that the player does actually progress, a level can be cleared, in which case there is no reason to stay, and being killed by a larger creature will knock the player back a level, so the game ensures the player will remain in the flow channel. flOw is available to play online. A link is provided at the end of this post.

Links - flOw

Csikszentmihalyi, M. 2002. Flow: The Classic Work On How To Achieve Happiness. London: Rider.

Thursday, 8 October 2015

Feedback On Presentation 1

Following my presentation that introduced my research subject to the class and my tutors, it seemed that my tutor wasn't entirely clear on what I intend to research. This may be because game design is often overlooked, and little-known to most people outside of the field. It's clear that my following presentations will have to introduce the subject more carefully.

To clarify; game design is the practice of handling a game's behavior, rules, composition, and experiential quality. As a discipline, it has fuzzy boundaries and widely varying roles throughout different game studios, but game design is very necessary for the creation of a good game. I normally like to explain the role of the game designer using Chess as an example.

Chess is a folk game; it's been "designed" by thousands-millions of people throughout the ages. But let's imagine for a second that it was created in a modern board-game studio, from scratch. A lot of people assume that just making the game makes you its designer. Carving the pieces, painting the board, designing the box art, they're often confused with the role of the game designer (given that "game designer" is often shortened to "designer" which, in almost all other fields, is an artistic role, this isn't surprising). These tasks would not, however, be the work of the game designer. Especially in the context of a video game, this kind of thing is handled by the game artist. In the case of Chess, the designer decides how many pieces there are, what they all do, how many squares are on the board (and even if they're going to use a square grid at all). These decisions may seem mundane, but they're often extremely weighted responsibilities that shape the game's quality.

In my case, I'm looking closely at the design of progression, and tutorials. Many video games are so complicated that they need to convey lots of instructions to the player, without boring them. Lots of games still aren't doing a very good job, and I'd like to investigate why this is the case, and how you can do a good job.

When I talk about tutorship, I don't necessarily mean solidly tutorial levels. This method of tutorship is arguably inferior to more integrated, seamless tutorials. Furthermore, even after your player has been taught basic controls and objectives, many games require continuous mastery of new situations and mechanics, so teaching the player should rarely stop at an early point of the game.

My research could focus on several individual topics. Designing overt tutorials and effectively conveying information, experience/difficulty curves, and 'flow'.

Thursday, 24 September 2015

Research Into Learning Curves and Player Metrics

For my creative research project, I'm interested in looking at how difficulty and learning function in video games. I'd like to examine the learning curves, experience curves, and other elements of difficulty in several games. Ideally, I'd like to try and uncover which types of curves and rates make for the ideal level of challenge in a game, with as little frustration or boredom as possible.

I'd also like to look into player metrics, to uncover tried and tested methods of measuring difficult concepts, such as learning, experience, and difficulty. If possible, I'd like to run primary test rounds on players, gathering data on their progression and how they feel the game is going. To do this, it would be ideal to have access to games with notable tutorial styles, such as Super Mario or Portal, but I'd also be interested in creating my own game - such as a simple puzzle game or platformer - and testing its tutorial capabilities.

Areas of note for me to research, so far, include classical learning and experience curves as seen in psychology, Will Wright's take on learning curves, the psychological model of Flow, and information on player metrics such as Seif El-Nasr's Game Analytics.

By the end of this project, I hope to have some answers to questions such as;
- Is player learning in a game constant, constantly increasing, or exponential?
- What constitutes a general ideal learning rate in a game?
- How can this ideal be implemented? How is this difficult to do?
- Can mathematical models describe certain useful learning curves?
- What methods are best for gathering player data?

As an aspiring video game designer, my ultimate goal is a practical, applicable experience in instilling the correct difficulty progression in a video game.