Games are motivating, aren´t they? Disputing the arguments for digital game-based learning

The growing popularity of game-based learning reflects the burning desire for exploiting the involving and motivating characteristics of games for serious purposes. A wide range of arguments for using games for teaching and learning can be encountered in scientific papers, policy reports, game reviews and advertisements. With contagious enthusiasm, the proponents of game-based learning make their claims for using games to improve education. However, standing up for a good cause is easily replaced with the unconcerned promotion and spread of the word, which tends to make gaming an article of faith. This paper critically examines and re-establishes the argumentation used for game-based learning and identifies misconceptions that confuse the discussions. It reviews the following claims about game-based learning: 1) games foster motivation, 2) play is a natural mode of learning, 3) games induce cognitive flow, which is productive for learning, 4) games support learning-by-doing, 5) games allow for performance monitoring, 6) games offer freedom of movement and the associated problem ownership, 7) games support social learning, 8) games allow for safe experimentation, 9) games accommodate new generations of learners, who have grown up immersed in digital media, and 10) there are many successful games for learning. Assessing the validity of argumentation is considered essential for the credibility of game-based learning as a discipline

Recognizing Affiliation: Using Behavioural Traces to Predict the Quality of Social Interactions in Online Games

Online social interactions in multiplayer games can be supportive and positive or toxic and harmful; however, few methods can easily assess interpersonal interaction quality in games. We use behavioural traces to predict affiliation between dyadic strangers, facilitated through their social interactions in an online gaming setting. We collected audio, video, in-game, and self-report data from 23 dyads, extracted 75 features, trained Random Forest and Support Vector Machine models, and evaluated their performance predicting binary (high/low) as well as continuous affiliation toward a partner. The models can predict both binary and continuous affiliation with up to 79.1% accuracy (F1) and 20.1% explained variance (R2) on unseen data, with features based on verbal communication demonstrating the highest potential. Our findings can inform the design of multiplayer games and game communities, and guide the development of systems for matchmaking and mitigating toxic behaviour in online games.Comment: CHI '2

Enhancing Deeper Learning Using Empathy and Creativity In Role-Playing Serious Games

Although educational technology has been widely used in education and remarkably supported instruction and assessment in face-to-face instruction, remote teaching and e-learning, teaching approaches have little deviated from the conventional approaches. Since the last decade, there is a shift in education to redesign teaching strategies. Education set priorities in promoting and supporting deeper learning to empower learners in thinking critically and creatively and gain skills and expertise in transferring their knowledge and applying it in other contexts to solve new problems. Concurrently, there is a remarkable interest by educators in harnessing the power of digital games and transferring it in education by designing Serious games. Serious Games are digital games designed to support learning, training, skill acquisition, and social and behavioural change. Serious Games integrate game design elements and gamification elements such as story, characters, score, visual objects, and rewards to create a positive mood while learning, increasing excitement, interest, motivation and engagement. Bridging the necessity for guiding learners in reaching deeper learning with Serious Games, this research thesis proposes the DeLEC pedagogical framework. DeLEC provides a pedagogic model which includes an iterative learning process of instruction, assessment and feedback integrating the elements of empathy and creativity. Aiming to investigate whether the proposed DeLEC framework is valid and indeed supports learners in reaching deeper learning, a Serious Game is designed to apply the phases of the DeLEC framework. The Serious Game is called Stronger and has the form of role-playing designed with a story and characters on a fictitious scenario around domestic violence and abuse (DVA). Stronger was tested with participants in a comparative study with an e-learning course on the same learning material. The results emerged from the data analysis demonstrated higher results in learning and deeper learning compared to the e-learning course leading to conclusions that confirm that the proposed DeLEC framework indeed assists learners in reaching Deeper Learning with Serious Games

Actas del congreso virtual: Avances en tecnologías, innovación y desafío de la educación superior ATIDES 2016.

ls entorns virtuals (educació a distància, e-Learning, blended Learning, laboratoris virtuals...), la globalització universitària (mobilitat virtual, educació global i multicultural, convenis interuniversitaris), cursos a distància massius i oberts (Massive Open Online Courses, MOOC), noves tecnologies en educació, l'espai europeu d'educació superior i els programes de mobilitat a partir de la Declaració de Bolonya, les experiències innovadores en educació, l'evaluació de competències i planificació de ECTS, l'acreditació de la qualitat, els aspectes legals i econòmics de l'educació, la regulació jurídica del dret a l'educació, l'educació i gènere... són alguns dels desafiaments que tracta la publicació

Analyse visuelle et cérébrale de l’état cognitif d’un apprenant

Un état cognitif peut se définir comme étant l’ensemble des processus cognitifs inférieurs (par exemple : perception et attention) et supérieurs (par exemple : prise de décision et raisonnement), nécessitant de la part de l’être humain toutes ses capacités mentales en vue d’utiliser des connaissances existantes pour résoudre un problème donné ou bien d’établir de nouvelles connaissances. Dans ce contexte, une attention particulière est portée par les environnements d’apprentissage informatisés sur le suivi et l’analyse des réactions émotionnelles de l’apprenant lors de l’activité d’apprentissage. En effet, les émotions conditionnent l’état mental de l’apprenant qui a un impact direct sur ses capacités cognitives tel que le raisonnement, la prise de décision, la mémorisation, etc. Dans ce contexte, l’objectif est d’améliorer les capacités cognitives de l’apprenant en identifiant et corrigeant les états mentaux défavorables à l’apprentissage en vue d’optimiser les performances des apprenants. Dans cette thèse, nous visons en particulier à examiner le raisonnement en tant que processus cognitif complexe de haut niveau. Notre objectif est double : en premier lieu, nous cherchons à évaluer le processus de raisonnement des étudiants novices en médecine à travers leur comportement visuel et en deuxième lieu, nous cherchons à analyser leur état mental quand ils raisonnent afin de détecter des indicateurs visuels et cérébraux permettant d’améliorer l’expérience d’apprentissage. Plus précisément, notre premier objectif a été d’utiliser les mouvements des yeux de l’apprenant pour évaluer son processus de raisonnement lors d’interactions avec des jeux sérieux éducatifs. Pour ce faire, nous avons analysé deux types de mesures oculaires à savoir : des mesures statiques et des mesures dynamiques. Dans un premier temps, nous avons étudié la possibilité d’identifier automatiquement deux classes d’apprenants à partir des différentes mesures statiques, à travers l’entrainement d’algorithmes d’apprentissage machine. Ensuite, en utilisant les mesures dynamiques avec un algorithme d’alignement de séquences issu de la bio-informatique, nous avons évalué la séquence logique visuelle suivie par l’apprenant en cours de raisonnement pour vérifier s’il est en train de suivre le bon processus de raisonnement ou non. Notre deuxième objectif a été de suivre l’évolution de l’état mental d’engagement d’un apprenant à partir de son activité cérébrale et aussi d’évaluer la relation entre l’engagement et les performances d’apprentissage. Pour cela, une étude a été réalisée où nous avons analysé la distribution de l’indice d’engagement de l’apprenant à travers tout d’abord les différentes phases de résolution du problème donné et deuxièmement, à travers les différentes régions qui composent l’interface de l’environnement. L’activité cérébrale de chaque participant a été mesurée tout au long de l’interaction avec l’environnement. Ensuite, à partir des signaux obtenus, un indice d’engagement a été calculé en se basant sur les trois bandes de fréquences α, β et θ. Enfin, notre troisième objectif a été de proposer une approche multimodale à base de deux senseurs physiologiques pour permettre une analyse conjointe du comportement visuel et cérébral de l’apprenant. Nous avons à cette fin enregistré les mouvements des yeux et l’activité cérébrale de l’apprenant afin d’évaluer son processus de raisonnement durant la résolution de différents exercices cognitifs. Plus précisément, nous visons à déterminer quels sont les indicateurs clés de performances à travers un raisonnement clinique en vue de les utiliser pour améliorer en particulier, les capacités cognitives des apprenants novices et en général, l’expérience d’apprentissage.A cognitive state can be defined as a set of inferior (e.g. perception and attention) and superior (e.g. perception and attention) cognitive processes, requiring the human being to have all of his mental abilities in an effort to use existing knowledge to solve a given problem or to establish new knowledge. In this context, a particular attention is paid by computer-based learning environments to monitor and assess learner’s emotional reactions during a learning activity. In fact, emotions govern the learner’s mental state that has in turn a direct impact on his cognitive abilities such as reasoning, decision-making, memory, etc. In this context, the objective is to improve the cognitive abilities of the learner by identifying and redressing the mental states that are unfavorable to learning in order to optimize the learners’ performances. In this thesis, we aim in particular to examine the reasoning as a high-level cognitive process. Our goal is two-fold: first, we seek to evaluate the reasoning process of novice medical students through their visual behavior and second, we seek to analyze learners’ mental states when reasoning to detect visual and cerebral indicators that can improve learning outcomes. More specifically, our first objective was to use the learner’s eye movements to assess his reasoning process while interacting with educational serious games. For this purpose, we have analyzed two types of ocular metrics namely, static metrics and dynamic metrics. First of all, we have studied the feasibility of using static metrics to automatically identify two groups of learners through the training of machine learning algorithms. Then, we have assessed the logical visual sequence followed by the learner when reasoning using dynamic metrics and a sequence alignment method from bio-informatics to see if he/she performed the correct reasoning process or not. Our second objective was to analyze the evolution of the learner’s engagement mental state from his brain activity and to assess the relationship between engagement and learning performance. An experimental study was conducted where we analyzed the distribution of the learner engagement index through first, the different phases of the problem-solving task and second, through the different regions of the environment interface. The cerebral activity of each participant was recorded during the whole game interaction. Then, from the obtained signals, an engagement index was computed based on the three frequency bands α, β et θ. Finally, our third objective was to propose a multimodal approach based on two physiological sensors to provide a joint analysis of the learner’s visual and cerebral behaviors. To this end, we recorded eye movements and brain activity of the learner to assess his reasoning process during the resolution of different cognitive tasks. More precisely, we aimed to identify key indicators of reasoning performance in order to use them to improve the cognitive abilities of novice learners in particular, and the learning experience in general

Performance assessment in serious games

Göbel, S., Hugo, O., Kickmeier-Rust, M. D., & Egenfeldt-Nielsen, S.(2016). Serious game: Economic and legal issues. In R. Dörner, S. Göbel, W. Effelsberg, & J. Wiemeyer (Eds.), Serious games: Foundations, concepts and practice (pp. 273-302). Berlin: Springer

Performance assessment in serious games

Göbel, S., Hugo, O., Kickmeier-Rust, M. D., & Egenfeldt-Nielsen, S.(2016). Serious game: Economic and legal issues. In R. Dörner, S. Göbel, W. Effelsberg, & J. Wiemeyer (Eds.), Serious games: Foundations, concepts and practice (pp. 273-302). Berlin: Springer

Performance assessment in serious games: Compensating for the effects of randomness

17 Halama