Impact of different levels of difficulty on immersion in video games Jim Sigailov-Lanfranchi University College Dublin jimsigailov@gmail.com Abstract. Twelve participants played three levels of Tetris that varied by diffi- culty and immersion was measured after each level with a survey. The levels corresponded to the scenarios: [skill of the player > challenge; skill = challenge; skill < challenge]. Flow levels of participants were measured as well. The ques- tion asked was whether different difficulties would influence how immersed players would be, hypothesizing that players would be more immersed when cognitively overloaded than when facing a challenge adapted to their skill. Re- sults showed no significant difference between the different conditions but pointed towards less immersion when the players faced a challenge inferior to their skill. Keywords: Immersion, Difficulty, Challenge, Flow, Videogames, Tetris 1 Background Video games playing is becoming one of the major hobbies across the planet, with three-quarters of all Americans having at least one gamer in their household (ESA, 2019). Consequently, over the past decades, a substantive body of research on video games has appeared and a growing number of research papers are dedicated to de- scribing and analyzing the multi-faceted phenomenology of gaming. Two of these facets that may variate the experience of the player are the difficulty of the game and how immersed the player feels. As many video games propose several levels of diffi- culty and many multiplayer ones propose matchmaking systems where the player faces an opponent of similar skill, the question of how immersion evolves throughout different levels is of interest not only to researchers but also to developers. However, to my knowledge, there is currently very little literature on how different levels of difficulty influence how immersed people are when gaming. This may be due to how the concept of flow state is conceived amongst game researchers. Indeed, flow seems often conceived as “the optimal experience” for gamers (e.g. Brockmyer et al, 2009; Chen, 2007). Because flow, amongst other things, is characterized by a feeling of loss of concern for the self in the real world during the activity, a deep in- volvement with the task undertaken, and an altered sense of time (Cowley et al., 2008), without further research, common sense would make you think that immersion Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). 2 Sigailov-Lanfranchi is maximized (or at least very strong) during flow. Additionally, it is known that in the context of video games, flow varies relatively to the balance of [skill of the play- er/challenge presented by the game] as follows: When difficulty is too low compared to the skill of the player, the game becomes boring, and cannot be flow-inducing. When difficulty matches the skill of the player, and the other conditions relative to the appearance of a flow state are met, the situa- tion is supposed to be flow-inducing, and very immersive. Finally, when the challenge is too high for the player, the situation becomes anxiogenic and the conditions are not flow-inducing anymore. Hence, we end up with a sort of bell-curve in which flow is maximized when [chal- lenge=skill]. Fig. 1 The flow channel (from Keller & Bless, 2008) At a first glance, it may seem that immersion would follow a similar pattern. Yet, let us study this more precisely. When the game is boring, it makes sense to suppose the game as not immersive, as the game is not very demanding, and the mind has cogni- tive room to wander freely. However, we hypothesize that when facing an extreme and anxiogenic challenge, the player would try to gather all attentional and cognitive resources. Consequently, the player could be as immersed, or even more immersed, than in the flow-inducing condition. As aforementioned, previous literature on experimental manipulation of challenge and its impact on immersion is limited. Qin et al. (2010) showed that players tended to feel more immersed when the difficulty was changing up and down than when the difficulty was changing down and up or simply increasing continuously. They also showed that participants were more immersed when subject to a “medium” rate change in difficulty rather than an excessively fast or slow one. However, their paper studied dynamics of immersion throughout non-random changes of difficulty and cannot be extrapolated to determine in absolute terms whether, say, an ‘easy’ difficul- ty is more immersive than a ‘hard’ one. Impact of different levels of difficulty on immersion in video games 3 Cox et al. (2012) also showed that increasing physical demand (by requiring the participants to press more buttons) was not enough alone to increase immersion. Time pressure, on the other hand, by adding both physical and cognitive challenge, success- fully increased immersion. In other words, they showed that some form of challenge can impact immersion. In this context, it makes sense to ask: how do different levels of difficulty impact immersion? This paper starts with 3 hypotheses: 1. Immersion is at its lowest point when the challenge of the game is below the skill of the player. 2. Immersion is high when the game presents a challenge that matches the skill of the player. When this is the case, the player enters a state of flow. 3. Immersion is even higher when the game presents a challenge that exceeds the skill of the player, as the player must gather all attentional and cognitive re- sources to face the challenge. This, in turn, creates deep immersion. I will try to answer the question asked using an experiment where players face three different conditions that vary by difficulty, and measure immersion levels reached during the experience. A measure of flow will be used as a proxy to deter- mine whether the medium level correspond to an adaptive condition where the chal- lenge matches the skill of the player. Keller & Bless (2008) successfully used a paradigm where they controlled the dif- ficulty of the video game Tetris to show that some individuals were more sensitive than others to manipulation of the skill/challenge balance. Here, this paradigm is adapted for our purposes. 2 Methods 2.1 Participants Data was recorded from 12 adults (5 females, 7 males) primarily postgraduate stu- dents, aged between 19 and 29 (mean=24.08, SD=2.39) years. All of the participants owned a personal computer and all but one generally played video games at least once a week. No reward was given for participation. 2.2 Design of the game Three versions of Tetris were adapted from an open source code found online that replicated the design of the version of Tetris originally published by Nintendo for Game Boy in 1989. The goal of Tetris is to manipulate a random sequence of falling pieces (called Tetrominos) and arrange them as to complete lines at the bottom of the screen. The previously fallen pieces stack up at the bottom, and when a line is com- 4 Sigailov-Lanfranchi plete, it disappears. The falling Tetrominos can be moved right and left and rotated by 90° in both directions using assigned keys (left, right and down directional arrows to move, “Z” and “X” to rotate. The up directional arrow also allowed for a clockwise rotation.). The upcoming Tetromino is shown on the right of the screen, as well as a score, the current level, and the number of lines completed. Speed increases correspond to level 1 to 20, that is, falling pieces moving every {887,820,753,686,619,552,468,368,284,184,167,150,133,117,100,100,83,83,66,66, 50} milliseconds. The Tetris music theme, originally played with the game, plays in the background. Fig. 2 User interface and example of situation the player may encounter in the game The three versions programmed tried to create a “boredom” condition (skill>challenge), a “flow-inducing” or “adaptive” condition (skill=challenge), and finally an “overload” condition (skill