In-game Behavior Research Articles

Are stress and engagement in toxicity associated with sleep quality? A study with League of Legends players

Today, millions of people worldwide play popular multiplayer online battle arena games (MOBAs) such as League of Legends. MOBAs are designed to require real-time teamwork to win games. A side effect of this is toxic behavior (an umbrella term for various negative in-game behaviors). Following Transactional Stress Theory, in this study, we consider toxicity as a coping mechanism to better deal with in-game stress that leads to anger and frustration, potentially leading to subsequent sleep problems. Therefore, we asked League of Legends players (N=212) about their experiences within the last 30 days in a retrospective survey study. Our results indicated that perceived stress was, indeed, a positive predictor of sleeping problems, and toxic behavior partially mediated this relationship. These results indicate that some of the toxicity is caused by stress in play and that it may increase the likelihood of the occurrence of subsequent sleeping problems. Therefore, further efforts are needed to help players to develop harmonious means and techniques for coping with experienced in-game stress.

Learning With Board Games: Interplay of Context and Students’ Prior Knowledge

Board games can support engagement, deep information processing and learning outcomes for university students. The instructional context, notably the way an activity is introduced to students, can influence students’ behavior and learning outcomes. Yet, despite its potential important influence on in-game behavior and learning, the impact of the instructional context used to introduce a game-based learning activity has not received much attention. In two studies, we examined how framing a game-based learning activity with a serious or a non-serious context can impact university students’ behavior and learning outcomes. In the first study, 44 graduate students played the same word association game that was either introduced as a game or as a study activity. Results showed that the serious context increased recall as compared to the gaming context. In the second study, involving 87 participants playing the same game, results showed that the gaming context and prior gaming experience also reduced students’ recall. Overall, grouped analysis showed that the gaming context led to poorer learning than the serious context for recognition and recall measures, even when considering prior knowledge, in-game behavior, and prior gaming experience. Theoretical and practical implications for educators are discussed.

Internet gaming disorder and risky behaviours among Czech adolescents: A nationally representative study.

The aim of the present study was to estimate the complex association between Internet Gaming Disorder (IGD), substance use, and other risky behaviours in Czech adolescents whilst providing prevalence estimates of IGD and psychometric information regarding the Czech Internet Gaming Disorder Scale-Short-Form (IGDS9-SF). A representative sample of 3,950 Czech adolescents was recruited through stratified random sampling in the school setting. Disordered gamers showed frequent use of specific substances such as pharmaceuticals, methylenedioxymethamphetamine, and lysergic acid diethylamide. In contrast, non-gamers had higher prevalence of alcohol, cigarettes, sedatives and tranquillisers, and marijuana use. A logistic regression, utilising IGDS9-SF raw scores and average daily gaming time, revealed a U-shaped relationship between gaming and both alcohol and cigarette use. Additionally, conduct problems such as bullying, and risky in-game behaviours were more prevalent among disordered gamers, with the exception of forging parents' signatures. The overall prevalence of IGD was 3.62% (95% CI = [3.1%, 4.3%]), with higher rates in males (5.89%; 95% CI = [4.9%, 7.0%]) than in females (1.45%; 95% CI = [1.0%, 2.1%]). The Czech IGDS9-SF used in the present study showed adequate psychometric properties. The association between gaming and substance use behaviours may be specific and multifaceted depending on the severity of the gaming-related problems. Furthermore, disordered gamers may become more vulnerable due to a higher incidence of conduct problems, bullying (victimisation), and in-game risky behaviours such as engagement with microtransactions mechanics (e.g., loot box) within video games.

It is not just a click: protection of in-game behaviour data as biometric data under the GDPR

This article investigates the potential classification of players’ in-game behaviour data from basic computer peripherals, like keyboards and mouses (behavioural telemetry), as biometric data under the General Data Protection Regulation (GDPR). Modern technologies allow these types of data to reveal a wealth of personal information, including age, gender, emotional states, collaboration abilities, problem-solving skills, economic status, consumption habits, and character traits. The analysis is structured into three sections: understanding the nature of in-game behaviour data, assessing its alignment with the GDPR’s definition of biometric data, and examining the repercussions for gaming companies if such data is deemed biometric. The conclusion asserts that behavioural telemetry and gameplay metrics can indeed be considered biometric under the GDPR, as it plays a crucial role in player identification and exhibits similarities with biometric systems in the context of game analytics processes. This classification implies heightened legal responsibilities for gaming companies, triggering risk-based provisions within the GDPR. The article introduces a novel perspective by suggesting that seemingly innocuous in-game behaviour data may fall under the purview of biometric data.

Playing mean: Does it imply a mean player?

Games allow players significant freedom to express themselves and behave as they see fit. As a consequence, in some games more than others, we may encounter hostile behavior. We explored whether players behaving in this manner are simply expressing their personality traits in the game or, rather, adopting this playstyle regardless of them. We conducted a three-year study observing over 250 people playing the turn-based, player-versus-player strategy game Diplomacy. Subjects were asked to fill out a questionnaire to determine their score on the social dominance orientation (SDO) scale—with a return rate of approx. 54%—while their in-game playstyle was analyzed for manifestations of hostile behavior. We found no statistically significant correlation between hostile in-game behavior and participants’ SDO score. However, we did find significant positive correlations between some aspects of this behavior and their success.

Morality in Gaming: Observer Perceptions of Player versus Character Actions

The debate on the impact of violent video games and its influence on players continues despite mixed findings. Using the lens of third person perception research, we explored moral judgments of laypersons, those often at the crux of these public debates. Study 1 investigated whether the player or character is perceived by an outside observer as responsible for moral decisions made within the narrative of a violent video game. Study 2 investigated how those perceptions may impact the observers’ perceptions of the player’s future negative behaviors and personality traits. Study 1 and 2 used a 2 (condition: rescuing vs. harvesting) x 2 (role: player vs. character) mixed ANOVA with role as a repeated measure. We created a brief recording of gameplay leading to a moral decision in Bioshock, an interactive, first-person shooter game, shown to participants. Participants were asked to rate perceived morality of player and character actions. Study 1 showed that participants (N = 51) held the observed player more morally responsible for in-game behaviors than the character within the game. Replicating and advancing Study 1, Study 2 (N = 227) showed support for you are what you eat heuristic, in that observers were more likely to view the negative behaviors of the in-game characters as indicators of negative personality traits of the player. These insights are crucial in the broader societal discourse on the potential link between violent video games and real-world aggression

How environmental perception affects players’ in-game behaviors? Towards developing games in compliance with sustainable development goals

Several research studies have pointed out that players’ in-game behaviors might be affected by different individual differences, such as player type, personality, etc. However, limited information is found about whether players’ environmental perceptions might impact their in-game behaviors towards the environment while playing. To address this research gap, this study analyzes the in-game behaviors data of 640 players within Nintendo’s Animal Crossing: New Horizons (ACNH), as well as their environmental perceptions based on the revised New Environmental Paradigm (NEP) scale, using open data sourced and adapted from Vuong et al. [53] from the Science Data Bank repository. The obtained results revealed that players’ environmental perceptions might impact their in-game behaviors, however this is not always true; the obtained results also revealed that players might behave within the game against their beliefs and perceptions just to level-up in the game. For instance, anti-anthropocentrism players, who are environment-caring, are found to harm the nature within the game. The findings of this study can help to understand how people with different environmental perceptions might behave, hence promoting ecological behaviors. Additionally, they can also help to reveal how to design games that can emphasize environment-friendly behaviors, hence helping to achieve the sustainable development goals of United Nations (UN).

Serious games in high-stakes assessment contexts: a systematic literature review into the game design principles for valid game-based performance assessment

The systematic literature review (1) investigates whether ‘serious games’ provide a viable solution to the limitations posed by traditional high-stakes performance assessments and (2) aims to synthesize game design principles for the game-based performance assessment of professional competencies. In total, 56 publications were included in the final review, targeting knowledge, motor skills and cognitive skills and further narrowed down to teaching, training or assessing professional competencies. Our review demonstrates that serious games are able to provide an environment and task authentic to the target competency. Collected in-game behaviors indicate that serious games are able to elicit behavior that is related to a candidates’ ability level. Progress feedback and freedom of gameplay in serious games can be implemented to provide an engaging and enjoyable environment for candidates. Few studies examined adaptivity and some examined serious games without an authentic environment or task. Overall, the review gives an overview of game design principles for game-based performance assessment. It highlights two research gaps regarding authenticity and adaptivity and concludes with three implications for practice.

The Variance of the Display Regarding the Free Riders Effect within Collectivist and Individualist Individuals

This study aims to investigate the difference in the display of free-riding behavior in individuals with collectivist orientations compared to those with individualistic orientations. Free riding refers to benefiting from a public good or resource without contributing one's fair share towards its provision. Understanding the influence of collectivism and individualism on free-riding behaviors has important implications for social cooperation, resource management, and the design of incentive structures. In this natural experiment, the independent variable (individuals' relative individualism-collectivism tendencies) and the dependent variable (free-rider behavior) measured by the frequency of in-game behaviors that advance the objective—are compared to see if they have any causal correlations. A sample of participants was recruited and divided into collectivist and individualist groups according to their cultural orientation scale individualism-collectivism test results to conduct this experiment. The participants are mixed evenly into groups, including both collectivists and individualists, and then provided to build a house on Minecraft's gaming platform. Their behavior is measured through quantitative methods using a designed table to show their in-game contributions and the Likert scale to reflect their in-game behaviour. The prediction concludes that this experiment will reveal a set of data stating that possessing individualistic values decreases an individual's chances of free-riding in a group compared to collectivistic beliefs.

Gender differences in achievement, behavior, and STEM interest among learners using Minecraft

In this paper, we analyze how male and female learners differ in their in-game behaviors, knowledge assessment outcomes, and STEM interest using the What-If Hypothetical Implementations using Minecraft (WHIMC). We also investigate how male and female learners’ self-reported levels of frustration and boredom relate to these outcomes. We examine in-game data, out-of-game assessment data, self-reported frustration and boredom, and results of the STEM interest questionnaire (SIQ) from 175 Grade 8 learners from a school in the Philippines. We found that male learners tend to explore more than female learners. Both genders learn more through more exploration, making more observations, and completing tasks, but only female learners benefit from having more idle time. Male learners had a higher increase in STEM interest compared to female learners, while there is no significant difference in assessment scores between the genders. This study also found that boredom and frustration have a negative impact on academic outcomes, behavior, and STEM interest, especially among female learners. Bored female learners tend to do less well on post-game assessments, explore less, and make fewer observations. Frustrated female learners tend to not complete the task. Female learners who expressed frustration or boredom tend to have a decreased interest in SIQ in the Interest category after playing WHIMC.

Educational Story-Based Game for Capturing the Learner's Personality

In recent years with the help of digital games there is an increasing interest in creating Serious Games for learning through play. With the help of machine learning algorithms, an educational serious game can be used, not only to assist the learner in his/her studies, but also to extract insights about the learner's personality. In game-based learning we take into account that the student behaves differently according to his/her individual characteristics while learning by playing. The most used method to model the learner’s personality is the self-report using questionnaires. The drawback of this approach is that the learner may not assess himself correctly or his/her answers’ may be biased towards the more socially acceptable responses rather than being truthful. In this paper, we explore the idea of having an alternative method of learning a person’s personality model and thus to better create interactive and engaging methods to assist learners in their studies. A story-based game with gamified learning elements was created for helping the learners study and evaluate their knowledge in the programming language C. The students learn by evaluating code snippets and depending on their response the game would give constructive feedback. At the same time students’ in-game behavior is captured and thus their personality traits could be determined. For modeling the learner’s personality we used the Five-Factor Model (OCEAN), a taxonomy of five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), each of which combines many personality characteristics. To evaluate the efficiency of the proposed serious game, we gathered data from 107 first year Computer Science students from the University of Macedonia. The students played the game and filled in the Big Five Inventory (BFI) questionnaire to capture their OCEAN traits. The BFI questionnaire was used as a ground truth. After the data gathering, we used machine learning techniques and also classification algorithms to create our model. The goodness of the model was assessed using different metrics and the results showed that it is effective to model both the extraversion and openness personality dimensions using serious games instead of questionnaires.

An intensive longitudinal dataset of in-game player behaviour and well-being in PowerWash Simulator

The potential impacts that video games might have on players’ well-being are under increased scrutiny but poorly understood empirically. Although extensively studied, a level of understanding required to address concerns and advise policy is lacking, at least partly because much of this science has relied on artificial settings and limited self-report data. We describe a large and detailed dataset that addresses these issues by pairing video game play behaviors and events with in-game well-being and motivation reports. 11,080 players (from 39 countries) of the first person PC game PowerWash Simulator volunteered for a research version of the game that logged their play across 10 in-game behaviors and events (e.g. task completion) and 21 variables (e.g. current position), and responses to 6 psychological survey instruments via in-game pop-ups. The data consists of 15,772,514 gameplay events, 726,316 survey item responses, and 21,202,667 additional gameplay status records, and spans 222 days. The data and codebook are publicly available with a permissive CC0 license.

A Typology of Metagamers: Identifying Player Types Based on Beyond the Game Activities

Previous research on player profiles or types is based on players’ in-game behaviors and their motivations to play games. However, there are many other activities related to digital games beyond playing the games properly. Using learning analytics methods, the study investigates the prevalence and interconnections between these different metagame activities and classifies gamers based on their use thereof into distinct profiles. The results show that digital game–related information-seeking activities are key metagame activities with connections to other metagame activities. Three distinct profiles of players were identified based on their metagame activities: versatile metagamers, strategizers, and casual metagamers. The results contribute to the existing literature on metagaming and provide insights for game studies, game design and marketing, and digital games and learning.

The influence of online multiplayer games on social capital and interdependent well-being in Japan

This study examines the effects of online game behaviors and players' characteristics on social capital and sense of belonging generated in multiplayer online games, and then on interdependent well-being. Hypotheses testing was performed using the partial least squares structural equation modeling based on an online survey conducted in 2021 (n = 383). Communication with close persons, acquaintances, and strangers all impact bridging social capital and bonding social capital, respectively, with the effect of communication with strangers being the strongest. Both extroversion and materialism positively impact bridging social capital and bonding social capital, while the impact of demographic variables is not found. Moreover, communication with close persons, strangers, bridging social capital, bonding social capital, and materialism positively impact belonging. Finally, belonging positively impacts interdependent well-being, and bridging social capital positively impacts interdependent well-being through belonging. This study shows the importance of interaction with strangers, and those players could develop broader and deeper social relationships in online games. Moreover, this study is the first to examine players' communication with players across different relationship types to clarify the social effects of in-game behaviors on interdependent well-being.

Measuring Cognitive Abilities in the Wild: Validating a Population-Scale Game-Based Cognitive Assessment.

Rapid individual cognitive phenotyping holds the potential to revolutionize domains as wide-ranging as personalized learning, employment practices, and precision psychiatry. Going beyond limitations imposed by traditional lab-based experiments, new efforts have been underway toward greater ecological validity and participant diversity to capture the full range of individual differences in cognitive abilities and behaviors across the general population. Building on this, we developed Skill Lab, a novel game-based tool that simultaneously assesses a broad suite of cognitive abilities while providing an engaging narrative. Skill Lab consists of six mini-games as well as 14 established cognitive ability tasks. Using a popular citizen science platform (N = 10,725), we conducted a comprehensive validation in the wild of a game-based cognitive assessment suite. Based on the game and validation task data, we constructed reliable models to simultaneously predict eight cognitive abilities based on the users' in-game behavior. Follow-up validation tests revealed that the models can discriminate nuances contained within each separate cognitive ability as well as capture a shared main factor of generalized cognitive ability. Our game-based measures are five times faster to complete than the equivalent task-based measures and replicate previous findings on the decline of certain cognitive abilities with age in our large cross-sectional population sample (N = 6369). Taken together, our results demonstrate the feasibility of rapid in-the-wild systematic assessment of cognitive abilities as a promising first step toward population-scale benchmarking and individualized mental health diagnostics.

A comparison of machine learning algorithms for predicting student performance in an online mathematics game

ABSTRACT This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students’ (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2) what types of in-game features (i.e. student in-game behaviors, math anxiety, mathematical strategies) were associated with student math knowledge scores. The results indicated that the Random Forest algorithm showed the best performance (i.e. the accuracy of models, error measures) in predicting posttest math knowledge scores among the seven algorithms employed. Out of 37 features included in the model, the validity of the students’ first mathematical transformation was the most predictive of their posttest math knowledge scores. Implications for game learning analytics and supporting students’ algebraic learning are discussed based on the findings.

The effect of self-reflection on information usage and information literacy in a digital serious game

In crisis management decision-making, decision-makers have to combine (limited) situational information with their own experience. Whereas traditional, analog training of decision-making situations in crisis management costs considerable time and effort, digital serious games can be used as more accessible training environments to offer additional training moments. Another advantage is that digital games offer new didactic opportunities, such as inducing specific reflection from the trainees. This study examines the effect of self-reflection through social comparison on information usage and information literacy of players of a digital serious game for crisis management decision-making training. In an experiment, data was collected from 73 participants, 47 were eligible for further analysis, split over two conditions. Participants played two gameplay scenarios in fixed order. Participants in the experimental condition, between the two scenarios, saw a dashboard displaying their own as well as previous players’ in-game behavior up to that point. Participants in the control condition received no intervention between playing the two scenarios. Overall, participants in the experimental condition used significantly more information from more different sources, and compared to the control condition they kept taking significantly more time to decide in the second scenario. No significant between-condition differences regarding information literacy were found. Results indicate that in-game behavior can be (positively) influenced by letting players self-reflect on their own in-game behavior through social comparison. Results also suggest that the dashboard should display more specific information of players’ in-game behavior, providing guidance on what to improve, rather than simply offering a broad overview.

Research into the Relationship between Personality and Behavior in Video Games, Based on Mining Association Rules

Nowadays, people have started to spend more and more time using the Internet, which has a crucial impact on people’s lives. Individual personality type is often the main factor dictating the various behaviors that people carry out, and it dominates their activities when socializing, communicating, and making choices in the virtual world. This study is dedicated to uncovering how the six dimensions of personality traits relate to players’ in-game behavior. This research is divided into two studies. Study 1 uses the K-means method to classify players in “Clash of Kings”, an online strategy video game, according to their activities. Using apriori algorithm, this research analyzes the correlation between in-game behavior and personality. In Study 2, the correlations are validated. In conclusion, not all personality traits are related to in-game behaviors. Players with high extraversion demonstrate more killings and attacks in games. Conscientiousness is negatively related to deaths. Emotionality shows strong extremes. The highest or lowest emotionality scores are associated with killings and attacks, while players with moderate emotionality will behave irregularly. Honesty/humility, agreeableness, and openness to experience are not predictive of in-game behaviors. For game manufacturers, players’ personality traits can be inferred through their corresponding in-game behaviors, to use in order to carry out targeted promotions.

Understanding optimal problem-solving in a digital game: The interplay of learner attributes and learning behavior

Educational video games, with various motivational features and scaffolding support, have high potential for facilitating optimal learning and achievement. However, research on how students utilize game features, identify useful information, and explore solutions to in-game problem scenarios continues to be under-researched. This study aims to unpack the mechanisms underlying users’ in-game behaviors to identify emergent markers of optimal problem-solving performance in an educational video game. Survey data and computer logs were collected from 61 participants (36.4% middle and high-school students, Mage = 13; 63.6% university students, Mage = 21) to address the research inquiry of the present study. Results from the regression analysis not only showed an important link between individual characteristics (i.e., self-efficacy, prior knowledge) and success-striving in-game behavior, but also highlighted the role of self-regulated help-seeking behavior in determining students’ optimal problem-solving pathways. Our findings add new perspectives to existing research of what learning behaviors are crucial for promoting self-regulation in digital game-based learning. These findings provide useful insight on how to design scaffolding tools in an open-ended problem-solving space to encourage student engagement in effective help-seeking behaviors for optimal learning performance.

Examining Students’ Behavior in a Digital Simulation Game for Nurse Training

Digital educational games have evolved in recent years due to the need to support education and training focused on non-technical skills. Data gathered through interaction with the graphical user interface are explored and exploited to analyze the players' experience. Many researchers have pointed the importance of analysis of players’ in-game behavior, which can help to enhance the learning process, identify learners' strategies, and improve the effectiveness of the serious game. This study is devoted to the analysis of students' behavior in a simulation game called CLONE, which targets work scheduling, situation awareness, and decision-making. The students’ performance and their behavioral strategies are examined based on sequences analysis of players' in-game actions. Moreover, outlier detection is proposed as an instrument for obtaining information that might help better understand students’ behavior. The findings of the study show that such indicators as time spent on planning schedule, time spent on inspecting additional information, and intensity of delegation activity are significantly higher for successful games than for lost ones. The sequences analysis and clustering reveal students' prevailing in-game strategies, which mostly consist of inspection, reading medical records, delegation, and scheduling. Eventually, outlier detection discloses the game sessions with uncertain strategies and unstructured scheduling.