A trace-based approach to identifying users’ engagement and qualifying their engaged-behaviours in interactive systems: application to a social game

Abstract

International audienceAnalysing and monitoring users' engaged-behaviours continuously and under ecologically valid conditions can reveal valuable information for designers and practitioners, allowing them to analyse, design and monitor the interactive mediated activity, and then to adapt and personalise it. An interactive mediated activity is a human activity supported by digital interactive technologies. While classical metric methods fall within quantitative approaches, this paper proposes a qualitative approach to identifying users' engagement and qualifying their engaged-behaviours from their traces of interaction. Traces of interaction represent the users' activities with an interactive environment. The basis of our approach is to transform low-level traces of interaction into meaningful information represented in higher-level traces. For this, our approach combines three theoretical frameworks : the Self-Determination Theory, the Activity Theory and the Trace Theory. Our approach has been implemented and tested in the context of the QUEJANT Projet. QUEJANT targets the development of a system allowing the actors of Social Gaming to analyse players' engagement from an analysis of their activity traces. In order to demonstrate the feasibility of our approach, we implemented the whole process in a prototype and applied it to 12 players' interaction data collected over four months. Based on these interaction data, we were able to identify engaged and non-engaged users and to qualify their types of engaged-behaviours. We also conducted a user study based on a validation of our results by experts. The high prediction rate obtained confirms the performance of our approach. We finally discuss the limitations of our approach, the potential fields of application and the implications for digital behavioural interventions

Adaptive user modelling in car racing games using behavioural and physiological data

“…As in Bouvier et al (2014), primitives were set to be mouse and keyboard entries whereas a collection of them on specific timestamps and specific places in their user interface were generating the primary traces. However, a primary trace is still low level and not meaningful enough.…”

Preface to the special issue on personalization and behavior change

“…It presents analyses and empirical research that focus on how adaptive and personalized systems can motivate people, for instance to improve health (op den Akker et al 2014;Dijkstra 2014;Orji et al 2014) and learning (Bouvier et at. 2014).…”

Identificação E Adaptação Do Nível De Habilidade Em Jogos Educacionais

“…Para isso, é necessário deixá-lo interessado e motivado a jogar. Estudos já mostram que jogos podem ser usados como ferramentas efetivas para ensinar [Ke e Grabowski 2007], mas é necessário que o jogo consiga manter o aluno interessado e motivado para que possa cumprir seu objetivo [Bouvier et al 2014]. Chun et al (2015) desenvolveram um método para fazer o ajuste de dificuldade em jogos educacionais móveis.…”

“…Mesmo com a intenção de entreter alunos enquanto aprendem, vários serious games não cumprem sua missão, na medida em que sacrificam a jogabilidade e focam apenas no conteúdo a ser ensinado, tornando o jogo tedioso [Pogačnik 2009] e sacrificando o interesse do aluno em aprender sobre o assunto abordado. Considerando isso, várias pesquisas já foram realizadas sobre o nível de interesse dos alunos ao jogar serious games e sua influência no aprendizado [Bouvier et al 2014;Baker et al 2010;Jovanovic et al 2011]. Segundo Bouvier e colegas, a falta de interesse ao jogar esses jogos é inversamente proporcional ao aprendizado do aluno e é um problema que deve ser solucionado.…”