gEYEded: Subtle and Challenging Gaze-Based Player Guidance in Exploration Games

This paper investigates the effects of gaze-based player guidance on the perceived game experience, performance, and challenge in a first-person exploration game. In contrast to existing research, the proposed approach takes the game context into account by providing players not only with guidance but also granting them an engaging game experience with a focus on exploration. This is achieved by incorporating gaze-sensitive areas that indicate the location of relevant game objects. A comparative study was carried out to validate our concept and to examine if a game supported with a gaze guidance feature triggers a more immersive game experience in comparison to a crosshair guidance version and a solution without any guidance support. In general, our study findings reveal a more positive impact of the gaze-based guidance approach on the experience and performance in comparison to the other two conditions. However, subjects had a similar impression concerning the game challenge in all conditions

Beyond Genre: Classifying Virtual Reality Experiences

12 pagesBecause virtual reality (VR) shares common features with video games, consumer content is usually classified according to traditional game genres and standards. However, VR offers different experiences based on the medium’s unique affordances. To account for this disparity, the paper presents a comparative analysis of titles from the Steam digital store across three platform types: VR only, VR supported, and non-VR. We analyzed data from a subset of the most popular applications within each category (N=141, 93, and 1217, respectively). The three classification types we analyzed were academic game genres, developer defined categories, and user-denoted tags. Results identify the most common content classifications (e.g., Action and Shooter within VR only applications), the relative availability of each between platforms (e.g., Casual is more common in VR only than VR supported or non-VR), general platform popularity (e.g., VR only received less positive ratings than VR supported and nonVR), and which content types are associated with higher user ratings across platforms (e.g., Action and Music/Rhythm are most positively rated in VR only). Our findings ultimately provide a foundational framework for future theoretical constructions of classification systems based on content, market, interactivity, sociality, and service dependencies, which underlay how consumer VR is currently categorized

Developing and evaluating MindMax: promoting mental wellbeing through an Australian Football League-themed app incorporating applied games (including gamification), psychoeducation, and social connectedness

Gamification is increasingly being used as a behavioural change strategy to increase engagement with apps and technologies for mental health and wellbeing. While there is promising evidence supporting the effectiveness of individual gamification elements, there remains little evidence for its overall effectiveness. Furthermore, a lack of consistency in how ‘gamification’ and related terms (such as ‘applied games’, an umbrella term of which gamification is one type) are used has been observed within and across multiple academic fields. This contributes to the difficulty of studying gamification and decreases its accessibility to people unfamiliar with applied games. Finally, gamification has also been critiqued by both game developers and by academics for its reliance on extrinsic motivators and for the messages that gamified systems may unintentionally convey. In this context, the aims of this thesis were fourfold: 1) to iteratively co-design and develop a gamified app for mental health and wellbeing, 2) to evaluate the eventuating app, 3) to consolidate literature on gamification for mental health and wellbeing, and 4) to synthesise findings into practical guidelines for implementing gamification for mental health and wellbeing. Chapter 2 reports the first study which addresses the first aim of this thesis. Six participatory design workshops were conducted to support the development of MindMax, an Australian Football League (AFL)-themed mobile phone app aimed at AFL fans (particularly male ones) that incorporates applied games, psychoeducation, and social connectedness. Findings from these workshops were independently knowledge translated and fed back to the software development team, resulting in a MindMax prototype. This prototype was further tested with 15 one-on-one user experience testing interviews at three separate time points to iteratively refine MindMax’s design and delivery of its content. The findings of this study suggest that broadly, participants endorsed a customisable user experience with activities requiring active user participation. These specifications were reflected in the continual software updates made to MindMax. Chapters 3 and 4 report the second and third studies which address the second aim of this thesis. As regular content, performance, and aesthetic updates were applied to MindMax (following the model of the wider tech industry), a naturalistic longitudinal trial, described in Chapter 3, was deemed to be the most appropriate systematic evaluation method. In this study, participants (n=313) were given access to MindMax and asked to use it at their leisure, and surveys were sent out at multiple time points to assess their wellbeing, resilience, and help-seeking intentions. Increases in flourishing (60-day only), sense of connection to MindMax, and impersonal help-seeking intentions were observed over 30 and 60 days, suggesting that Internet-based interventions like MindMax can contribute to their users’ social connectedness and encourage their help-seeking. The third study, described in Chapter 4, reports a secondary analysis of data collected for Chapter 3, and further explores participants’ help-seeking intentions and their links to wellbeing, resilience, gender, and age. An explanatory factor analysis was conducted on Day 1 General Help-Seeking Questionnaire (GHSQ) data (n=530), with the best fitting solution resulting in three factors: personal sources, health professionals, and distal sources. In addition to providing more evidence that younger people aged 16–35 categorise apps and technologies for mental health and wellbeing like MindMax alongside other distal social sources such as phone helplines and work or school, our findings also suggest that the best way to target individuals who are least likely to seek help, particularly men, may be through these distal sources as well. Chapter 5 reports the fourth study, which addresses the third aim. In order to consolidate literature on gamification for mental health and wellbeing, this systematic review identified 70 papers that collectively reported on 50 apps and technologies for improving mental health and wellbeing. These papers were coded for gamification element, mental health and wellbeing domain, and researchers’ justification for applying gamification to improving mental health and wellbeing. This study resulted in two major findings: first, that the current application of gamification for mental health and wellbeing does not resemble the heavily critiqued mainstream application that relies on extrinsic motivators; and second, that many authors of the reviewed papers provided little or no justification for why they applied gamification to their mental health and wellbeing interventions. While the former finding is encouraging, the latter suggests that the gamification of mental health and wellbeing is not theory-driven, and is a cause for concern. Finally, to address the final aim of this thesis, all study learnings were synthesised into practical guidelines for implementing gamification for mental health and wellbeing. First, it is important to assess the suitability of implementing gamification into the intervention. Second, this implementation should ideally be integrated at a deeper, systemic level, with the explicitly qualified intention to support users, evidence-based processes, and user engagement with these processes. Third, it is important to assess the acceptability of this gamified intervention throughout its development, involving all relevant stakeholders (particularly representative end user populations). Fourth, it is important to evaluate the impact of this gamified intervention. Fifth, and finally, comprehensive and detailed documentation of this process should be provided at all stages of this process. This thesis contributes to a growing literature on the increasing importance and relevance of Internet-based resources and apps and technologies for mental health and wellbeing, particularly for young people. Given the dominance of games in society and culture across history, and the increasing contemporary prominence of digital games (also known as video games) in particular, gamification is uniquely positioned to have the potential to make large contributions to mental health and wellbeing research. In this context, this thesis contributes a systematically derived operationalisation of gamification, an evaluation of a gamified app for mental health and wellbeing, and best practice guidelines for implementing gamification for mental health and wellbeing, thereby providing frameworks that future implementations of gamified mental health and wellbeing interventions and initiatives may find useful

CrowdCO-OP : sharing risks and rewards in crowdsourcing

Paid micro-task crowdsourcing has gained in popularity partly due to the increasing need for large-scale manually labelled datasets which are often used to train and evaluate Artificial Intelligence systems. Modern paid crowdsourcing platforms use a piecework approach to rewards, meaning that workers are paid for each task they complete, given that their work quality is considered sufficient by the requester or the platform. Such an approach creates risks for workers; their work may be rejected without being rewarded, and they may be working on poorly rewarded tasks, in light of the disproportionate time required to complete them. As a result, recent research has shown that crowd workers may tend to choose specific, simple, and familiar tasks and avoid new requesters to manage these risks. In this paper, we propose a novel crowdsourcing reward mechanism that allows workers to share these risks and achieve a standardized hourly wage equal for all participating workers. Reward-focused workers can thereby take up challenging and complex HITs without bearing the financial risk of not being rewarded for completed work. We experimentally compare different crowd reward schemes and observe their impact on worker performance and satisfaction. Our results show that 1) workers clearly perceive the benefits of the proposed reward scheme, 2) work effectiveness and efficiency are not impacted as compared to those of the piecework scheme, and 3) the presence of slow workers is limited and does not disrupt the proposed cooperation-based approaches

Machine Learning and Integrative Analysis of Biomedical Big Data.

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues