HNRS 3000 - Haynes

How can we better learn about and teach moral thinking and skills? How can we solve moral problems? One possible way is to create and use moral learning games, or games that enable players to work on moral scenarios, make moral choices, and gain relevant skills. One possible subcategory of these games is moral knowledge games, or games that aim to solve real-world moral problems and create new knowledge about morality. This article systematically analyzes relevant literature and related games and media to uncover a preliminary set of design principles for creating moral learning games and moral knowledge games. Frameworks such as the Elemental Tetrad, Mechanics, Dynamics, and Aesthetics (MDA), and Ethics Practice and Implementation Categorization Framework (EPIC) were used to analyze individual games and media. Ten different categories of principles emerged, along with 95 possible subprinciples. Implications, next steps, and limitations of this analysis were also discussed.

While older people tend to be regarded as actual, or potential, players of digital games within literature on game studies, human–computer interaction, and gerontechnology, they are also often considered nonavid users of digital technologies. This contradiction prompted us to conduct a literature review, which revealed (a) insufficient involvement of older people within the design of games targeted toward this group and (b) insufficient understanding of their everyday digital gameplay. In this article, we present the conceptualization, design, and evaluation of digital games that active older people found to be sufficiently appealing, playable, and meaningful. A 6-month ethnography of the play experiences of 170 older people helped us to conceptualize these games, which were codesigned through playful everyday activities. To facilitate the development of these games, we designed and evaluated an online game creation platform, which enabled 99 older people with different cultural backgrounds to create, play, and contribute to games.

Augmented Reality video games such as Pokémon GO have a structure that encourages face-to-face social interactions between players, leading to potentially unique benefits for positivity (positive affect). This study investigated how participants’ social interactions while playing Pokémon GO relate to their positivity after gameplay, crucially, after accounting for other non-social factors typically associated with positivity (participants’ satisfaction with their game accomplishments). Participants were 108 Pokémon GO players, consisting of 54 dyads who signed up for the study together. Dyads were asked to play Pokémon GO together for eight sessions over 2 weeks, and to report on their gameplay experiences and positivity after each session. Multilevel modelling analyses revealed that more positive social interactions with their gameplay partner incrementally predicted participants’ greater positivity postgameplay. The association between positive social interactions and greater positivity was accentuated for participants who reported more frequent noxious mood states (depressive symptoms) at the start of the study. Findings suggest that above and beyond typical contributions such as achieving game accomplishments, there may be affective benefits for Pokémon GO players from the social interactions they have within the game, especially for those with noxious mood states.

Massively Multiplayer Online First-Person Shooter (MMOFPS) games are among the most high-risk games related to the development problem video gaming. These games are often designed to promote direct competition between players, and research has identified competition as a key motivator for participation in online games. However, it is not clear whether competitiveness measured as a personality trait is associated with problematic video gaming engagement. The primary aim of the current study was to examine the relationship between three facets of trait competitiveness and problem online video gaming among players of MMOFPS games who reported playing these video games at least 1–4 times a week. A multiple regression analysis revealed that dominant competitiveness was the only facet of trait competitiveness to predict problem gaming score. The results of the current study expand upon previous indications that competitiveness motivates online gaming, suggesting that inherent dominant competitive tendencies may increase the risk of problematic participation in competition-centered online video games.

5G technology will greatly improve quality of human life by enabling new use cases that will fully leverage on the improved throughput, connections, and latency of the 5G networks. Enhanced Mobile Broadband (eMBB), which supports ultra-high throughput, is one of the most important features in 5G networks. This service is expected to improve users' quality of experience (QoE) when using resource-intensive and far more interactive applications such as playing online games. It is widely known that 5G networks can be used for gathering network monitoring data and application metrics; however, the correlation between the data and the users' QoE is not well understood. Since large amount of data can be collected, machine learning approach is well suited for predicting users' QoE when playing online games in 5G networks. In this paper, an artificial neural network (ANN) model is proposed to predict the users' QoE based on the network monitoring data of a 5G network during an online gaming session and the model's performance is evaluated. The ANN model consists of four layers which include one input layer, two hidden layers, and one output layer. The Unified Management Expert (UME) system is used to collect the network monitoring data from a 5G NSA indoor private campus network. The proposed ANN model achieves prediction accuracy of close to 80% using 30 most relevant features derived from the radio access network monitoring data.