Description: With the increasing availability of powerful mobile and ubiquitous computing technologies, motivational and behavior change technologies, traditionally applied in the health science domain, have become commonplace and have expanded to cover several other domains. In particular, game-based motivational systems (i.e., serious games, games with a purpose, gamification) are emerging as an effective tool to induce a positive change in human behaviors in relation to environmental challenges, social engagement, safety, productivity and learning. Games introduce goals, interaction, feedback, problem solving, competition, narrative, and fun learning environments, motivational affordances that can increase end-user engagement and induce a voluntary behavior change. Although several research studies proved the validity of game-based motivational systems, their effectiveness has often been context specific and varied among individuals. A promising and ever-growing research field concerns the investigation of user-centered, personalized and adaptive gamified dynamics, tailored to specific users and contexts. In the context of games, adaptivity describes the automatic adaptation of game elements, i.e., of content, user interfaces, game mechanics, game difficulty, etc., to customize or personalize the interactive experience. Personalization and adaptivity can promote motivated usage, increased user acceptance, and user identification in serious games.
The aim of the PhD project is to investigate key features of adaptive personalized motivational game-based systems addressing one or more of the following research challenges: analyse the relationship between the mechanics and their effects on different individuals to react accordingly; investigate adaptive game dynamics in multi-player settings, finding the right balance between individual (micro) level and community (macro) level personalization; design of meaningful adaptive gamified reinforcement strategy to sustain players’ long-term motivation (e.g., churn prediction and generation of dynamic personalized re-engagement incentives).

Skills: The ideal candidate has a background in Computer Science or Cognitive Science. User-centered design, game design, motivation theories, knowledge on designing and conducting experimental studies, experience with quantitative and qualitative data analysis techniques are a plus for the application and should be acquired during the Phd training.

Responsible of the Project: Annapaola Marconi - marconi [at] fbk.eu
 

Description: The PhD project focuses on the cognitive basis of computational thinking for the design of digital technologies in the field of Internet-Of-Things aimed at improving learning and education. In particular, the research explores digital tools that can be manipulated and adapted by teachers and children themselves (the so-called "End-User Programming").

Skills: The ideal candidate has a background in Computer Science or Cognitive Science with strong interest in the Human-Computer Interaction. Skills in programming (HML5, Python or similar) and knowledge on designing and conducting experimental studies are a plus for the application and they should be acquired during the Phd training.

Responsibles of the Project: Massimo Zancanaro - massimo.zancanaro [at] unitn.it | zancana [at] fbk.eu
 

Description: The Phd project can evolve along either one of the two research lines described below.
 

Research line 1: Personal agents for mindfulness-based interventions in healthcare. In the last decade there has been a growing interest for mindfulness interventions delivered by means of mobile applications and personal assistants to support self-care of patients, including those coping with chronic conditions. Despite the fact that the validity of mindful practices has been proved repeatedly by previous research, the design of effective behavioral intervention technologies for mindfulness coaching and practice remains a challenge. The aim of the PhD project is to investigate key features of smart coaching solutions for mindful-based interventions that are engaging to use by patients and produce effective outcomes from a clinical perspective. The ideal candidate will be strongly motivated in developing design skills in the field of behavioral intervention technologies and conversational agents for applications in healthcare.
Skills for research line 1: Familiarity with user-centered design methodology, experience with quantitative and qualitative data analysis techniques, knowledge of clinical psychology.

Research line 2: Computational creativity is a sub-field of artificial intelligence concerned with the development of programs that can produce creative output; in particular, many of these programs deal with linguistic creativity. Recent years have witnessed a growing interest in computational linguistic creativity, a research field at the boundary between many disciplines including natural language processing, linguistics, psychology, and of course cognitive sciences. Even though the state-of-the-art in this field is advancing a bit in the last years, real-world applications of computational linguistic creativity are still uncommon. Particular focus of the PhD will be put in computational treatment of figurative, emotional, witty language considering also in multimodal (e.g. visual) context.
Skills for research line 2: Familiarity with the main techniques of computational linguistics. Good programming skills and being comfortable with linguistic and visual creativity.

Responsibles of the Project: Silvia Gabrielli - sgabrielli [at] fbk.eu (for research line 1)
                                              Carlo Strapparava - strappa [at] fbk.eu (for research line 2)