Although gamification in the workplace is burgeoning, organizations frequently have difficulty sustaining user engagement with a gamified information system (IS). The focus of this study is how a gamified IS in the workplace engages users and encourages them to continue system use. By proposing the concepts of flow experience (FE) and aesthetic experience (AE) as different ways to provide deep and meaningful user engagement, this study develops a model that explores the antecedents of FE and AE and their roles in explaining an individual’s continuance intention to use of a gamified IS. The model is tested using data collected from 178 users of a gamified IS in a global consulting company. The results demonstrate that although FE and AE are complementary forces, AE is more salient than FE for explaining continuance intention. The research proposes AE as a parsimonious yet powerful construct that extends the research on user engagement. The findings contribute to research on gamification by shifting...

Gamification in the Workplace: The Central Role of the Aesthetic Experience

Engaging users is a priority for designers of products and services of every kind. The need to understand users’ experiences has motivated a focus on user engagement across computer science. However, to date, there has been limited review of how Human--Computer Interaction and computer science research interprets and employs the concept. Questions persist concerning its conception, abstraction, and measurement. This article presents a systematic review of engagement spanning a corpus of 351 articles and 102 definitions. We map the current state of engagement research, including the diverse interpretation, theory, and measurement of the concept. We describe the ecology of engagement and strategies for the design of engaging experiences, discuss the value of the concept and its relationship to other terms, and present a set of guidelines and opportunities for future research.

https://dl.acm.org/doi/pdf/10.1145/3234149

Engagement in HCI: Conception, Theory and Measurement

Slowly computers are being dressed and becoming huggable and tangible. They are being personalized and are expected to understand more of their users' feelings, emotions, and moods: This we refer to as affective computing. The work and experiences from 50+ publications on affective computing is collected and reported in one concise monograph. A brief introduction on emotion theory and affective computing is given and its relevance for computer science (i.e., Human-Computer Interaction, Artificial Intelligence (AI), and Health Informatics) is denoted. Next, a closed model for affective computing is introduced and reviews of both biosignals and affective computing are presented. The conclusion of all of this is that affective computing lacks standards. Affective computing's key dimensions need to be identified and studied to bring the field the progress it needs. A series of studies is presented that explore baseline-free affective computing, the influence of a range of distinct triggers for emotions, the influence of time windows, several combinations of biosignals with and without speech, the impact of the context, the personality traits neuroticism and extroversion, and demographics. Moreover, a complete signal processing + classification processing pipeline for affective computing is developed and executed on the data gathered. This pipeline is also applied on two clinical case studies, which proves that affective computing is already feasible in clinical practice; that is, Computer Aided Diagnosis (CAD) for patients suffering from a Post-Traumatic Stress Disorder (PTSD). A set of key dimensions for affective computing and, subsequently, prerequisites and guidelines are defined, based on the author's work and experiences. Moreover, historical, emotion theoretical, and computer science perspectives are taken to reflect upon the work and five applications (i.e., next-generation TV, knowledge representations, CAD, robot nannies, and digital human models) are presented to illustrate the field's future impact. If anything, this monograph shows that affective computing will become unstoppable, will determine our relation with ICT and, as such, will reshape our lives.

/pdf/affective-signal-processing-asp-unraveling-the-mystery-of-36xjmlsbyr.pdf

Affective Signal Processing (ASP): Unraveling the mystery of emotions

http://home.fsw.vu.nl/ea.konijn/files/Realism_Published_2007.pdf

Realism is not all! User engagement with task-related interface characters

Despite the popularity of the technology acceptance and adoption studies, adoption of persuasive systems has not been investigated from a theoretical perspective. In the present study, we put forward a novel approach for investigating behavior change support systems (BCSS) through a theoretical model. We constructed and tested (two measurement points; 172 subjects) a model predicting perceived persuasiveness and actual usage of a behavior change support system. Results from a rigorous PLS-SEM analysis support most of our hypotheses about factors affecting persuasiveness and actual usage. The proffered model can be considered as a meta-model, i.e. it may be utilized in a multitude of domains, such as health behaviors (as in the present study), safety and education. The present study extends the extant (rather limited) body of knowledge regarding the factors contributing to engagement with behavior change support systems.

Factors Affecting Perceived Persuasiveness of a Behavior Change Support System

The nature of humans interacting with interface characters (e.g. embodied agents) is not well understood. The I-PEFiC model provides an integrative perspective on human-character interaction, assuming that the processes of engagement and user interaction exchange information in explaining user responses with interface characters. An experiment using the Sims2 game was conducted to test the effects of aesthetics (beautiful versus ugly, as engagement factor) and affordances (help versus obstacle, as interaction factor) of interface characters on use intentions, user engagement, and user satisfaction. Results of the experiment showed that (1) people tended to use helpful characters more than obstructing characters, (2) user engagement was enhanced by beauty and perceived affordance of the character whereas (3) intentions to use the character were not affected by good looks, and (4) the most satisfied users were those that were engaged with the character as well as willing to use it. This stresses the importance of enhancing affordances so to increase user engagement with interface characters. The I-PEFiC model provided a valuable framework to study the (interdependent) effects of relevant factors in human-character interaction.

/pdf/affective-affordances-improving-interface-character-2lk0vanik2.pdf

Athina de Bie Dimitriadou

Papers

Affective affordances: Improving interface character engagement through interaction