What Video Games Have to Teach Us about Learning and Literacy

The Transmission Control Protocol.

Gamification, the application of game elements to non-game settings, continues to grow in popularity as a method to increase student engagement in the classroom. We tested students across two courses, measuring their motivation, social comparison, effort, satisfaction, learner empowerment, and academic performance at four points during a 16-week semester. One course received a gamified curriculum, featuring a leaderboard and badges, whereas the other course received the same curriculum without the gamified elements. Our results found that students in the gamified course showed less motivation, satisfaction, and empowerment over time than those in the non-gamified class. The effect of course type on students' final exam scores was mediated by students' levels of intrinsic motivation, with students in the gamified course showing less motivation and lower final exam scores than the non-gamified class. This suggests that some care should be taken when applying certain gamification mechanics to educational settings. Longitudinal study on effects of gamification in the classroom.71 students surveyed at four time points in gamified or non-gamified course.Over time, gamified students were less motivated, empowered, and satisfied.Gamified course negatively affected final exam grades through intrinsic motivation.Gamified systems strongly featuring rewards may have negative effects.

Assessing the effects of gamification in the classroom

https://romisatriawahono.net/lecture/rm/survey/machine%20learning/Wozniak%20-%20Multiple%20Classifier%20Systems%20-%202014.pdf

A survey of multiple classifier systems as hybrid systems

In this meta-analysis, we systematically reviewed research on digital games and learning for K-16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust variance estimates to summarize overall effects and explore potential moderator effects. Results from media comparisons indicated that digital games significantly enhanced student learning relative to nongame conditions ([Formula: see text] = 0.33, 95% confidence interval [0.19, 0.48], k = 57, n = 209). Results from value-added comparisons indicated significant learning benefits associated with augmented game designs ([Formula: see text] = 0.34, 95% confidence interval [0.17, 0.51], k = 20, n = 40). Moderator analyses demonstrated that effects varied across various game mechanics characteristics, visual and narrative characteristics, and research quality characteristics. Taken together, the results highlight the affordances of games for learning as well as the key role of design beyond medium.

Digital Games, Design, and Learning A Systematic Review and Meta-Analysis

In the domain of computer games, research into the interaction between player and game has centred on 'enjoyment', often drawing in particular on optimal experience research and Csikszentmihalyi's 'Flow theory'. Flow is a well-established construct for examining experience in any setting and its application to game-play is intuitive. Nevertheless, it's not immediately obvious how to translate between the flow construct and an operative description of game-play. Previous research has attempted this translation through analogy. In this article we propose a practical, integrated approach for analysis of the mechanics and aesthetics of game-play, which helps develop deeper insights into the capacity for flow within games. The relationship between player and game, characterized by learning and enjoyment, is central to our analysis. We begin by framing that relationship within Cowley's user-system-experience (USE) model, and expand this into an information systems framework, which enables a practical mapping of flow onto game-play. We believe this approach enhances our understanding of a player's interaction with a game and provides useful insights for games' researchers seeking to devise mechanisms to adapt game-play to individual players.

/pdf/toward-an-understanding-of-flow-in-video-games-2bzvemnjeu.pdf

Toward an understanding of flow in video games

We describe an approach to player-centred game design through adaptive game technologies [9]. The work presented is the result of on-going collaborative research between Media and Computing groups at the University of Ulster, and so we begin with a review of related literature from both areas before presenting our new ideas. In particular we focus on three areas of related research: understanding players, modelling players, and adaptive game technology. We argue that player modelling and adaptive technologies may be used alongside existing approaches to facilitate improved player-centred game design in order to provide a more appropriate level of challenge, smooth the learning curve, and enhance the gameplay experience for individual players regardless of gender, age and experience. However, adaptive game behaviour is a controversial topic within game research and development and so while we outline the potential of such technologies, we also address the most significant concerns.

Player-Centred Game Design: Player Modelling and Adaptive Digital Games

It is generally accepted that informative and timely feedback is important to a student's learning experience within higher education. In the study of commercial digital games it has also become increasingly understood that games are particularly good at providing effective feedback of this form to gameplayers. We discuss recent game based learning research that attempts to harness the motivating qualities of digital games to inform the design of educational technology. Results from this research demonstrate student participation and performance can be improved by providing Game-Based Feedback (GBF) to students. The GBF approach awards points to students for the successful completion of tasks throughout a course of study. Points and achievements accumulated over time builds a profile that provides a student with a potentially powerful representation of their educational identity. In this paper, we argue that virtual worlds are particularly suitable for this form of GBF and can further enhance a student's understanding of their educational standing. We outline a Virtual Learning Landscape (VLL) design that is embedded within a multi-user virtual environment, where educational feedback is supplied to students via their avatar and a virtual world's landscape. The core structural principles of the proposed VLL are explained and several examples of the use of the VLL are provided to illustrate the system.

Game-based feedback for educational multi-user virtual environments

In this paper we outline a framework for creating playercentred digital games. At the core of our proposal is the requirement for games to be more responsive to different player types and their individual needs; for games to have the capability to adapt so as to provide an appropriate level of challenge for each player, to smooth the learning curve, and enhance the gameplay experience for each player individually. This is not an easy objective to achieve and adaptive game technology, although a popular ideal in some quarters, is still fraught with difficulties and some controversy. We address some of the most well known issues and outline a proposal for dealing with two of the more recent issues: that of monitoring the effectiveness of game adaptation on the basis of player intention and/or frustration, and dealing with dynamic player profiles – because players learn in different ways and at a different speed.

Dynamic Player Modelling: A Framework for Player-Centered Digital Games

Artificial intelligence for digital games constitutes the implementation of a set of algorithms and techniques from both traditional and modern artificial intelligence in order to provide solutions to a range of game dependent problems. However, the majority of current approaches lead to predefined, static and predictable game agent responses, with no ability to adjust during game-play to the behaviour or playing style of the player. Machine learning techniques provide a way to improve the behavioural dynamics of computer controlled game agents by facilitating the automated generation and selection of behaviours, thus enhancing the capabilities of digital game artificial intelligence and providing the opportunity to create more engaging and entertaining game-play experiences. This paper provides a survey of the current state of academic machine learning research for digital game environments, with respect to the use of techniques from neural networks, evolutionary computation and reinforcement learning for game agent control.

Michaela Black

Papers

Toward an understanding of flow in video games

Player-Centred Game Design: Player Modelling and Adaptive Digital Games

Game-based feedback for educational multi-user virtual environments

Dynamic Player Modelling: A Framework for Player-Centered Digital Games

Machine learning in digital games: a survey