Abstract. Monitoring a learner’s performance during practice plays an important role in scaffolding. It helps with scheduling suitable practice exercises, and by doing so sustain learner motivation and a steady learning progress while they move through the curriculum. In this paper we present our approach for monitoring the learning progress of students learning to play piano with Hidden Markov Models. First, we present and implement the so-called practice modes, practice units that are derived from the original task by reducing its complexity and focusing on one or several relevant task dimensions. Second, for each practice mode a Hidden Markov Model is trained to predict whether the player is in the Mastered or NonMastered latent state regarding the current task and practice mode

Abstract. American local newspapers have been experiencing a large loss of reader retention and business within the past 15 years due to the proliferation of online news sources. Local media companies are starting to shift from an advertising-supported business model to one based on subscriptions to mitigate this problem. With this subscription model, there is a need to increase user engagement and personalization, and recommender systems are one way for these news companies to accomplish this goal. However, using standard modeling approaches that focus on users’ global preferences is not appropriate in this context because the local preferences of users exhibit some specific characteristics which do not necessarily match their long-term or global preferences in the news. Our research explores a localized session-based recommendation approach, using recommendations based on local news articles and articles pertaining to the different local news categories. Experiments performed on a news dataset from a local newspaper show that these local models, particularly certain categories of items, do indeed provide more accuracy and effectiveness for personalization which, in turn, may lead to more user engagement with local news content.

Abstract. Persuasive technologies are interactive systems that are designed to influence people to change their attitudes or behaviours. Persuasive technologies have been used successfully in several domains including health to make people exercise more, shopping to make people buy specific products, and social media to make people contribute better content. In the area of sustainability, its use is not well documented. To contribute to the use of persuasive technologies in sustainability, this paper carries out a literature review of published articles in the area in the past five years and summarizes the main findings based on three main themes: the design and development of the technology to make it adaptive to users, the evaluation of the technology, and the findings from the evaluation. Our results suggest that most persuasive technologies are developed as mobile applications, IoT devices or serious games and the most common behaviour change targeted by the persuasive technologies in this domain are energy conservation and sustainable food management. The most common persuasive strategies that are used are rewards, suggestions and self-monitoring. In terms of evaluation, a self-reported evaluation method was applied by most authors. While the range of evaluation of the developed persuasive technologies was between one hour and one year, the number of recruited participants ranged from two to over nine hundred. The findings from the evaluation were mostly mixed with several authors reporting positive results (behaviour change) for some participants. Based on these results, we suggest guidelines for the development of future persuasive technologies for sustainability.

Abstract. Physical activity is important to improve an individual’s overall well-being. Digital interventions as they use Virtual Reality (VR) and Augmented Reality (AR), have shown success in promoting physical activity (PA) in people of all ages. This work discusses the design of an AR gamified mobile application prototype for promoting physical activity in young adults. The application (app), “The Journey” aims to promote PA in young adults users while they explore various touristic sites and also acquire virtual assets. This is achievable at a low cost to users by using smartphones-based AR app to tour any location of interest from the comfort of their home or outdoor. Each user’s step count tracked via mobile device is used to help them navigate the location of interest. The findings from our evaluation of 29 people show that The Journey has the potential to motivate people to improve their PA both indoors and outdoors.

Abstract. Many people with dementia residing in long-term care may face barriers in accessing experiences beyond their physical premises; this may be due to location, mobility constraints, legal acts and/or mental health restrictions. Previous research has suggested that institutionalization increases the co-existing symptoms of dementia, such as aggression, depression, apathy, lack of motivation and loss of interest in oneself and others. Despite the importance of supporting the mental well-being of people with dementia, in many cases, it remains undertreated. In recent years, there has been a growing research interest towards designing non-pharmacological interventions aiming to improve the Health-Related Quality of Life for people with dementia within long-term care. With computer technology and especially Virtual Reality offering endless opportunities for mental support, we must consider how Virtual Reality for people with dementia can be sensitively designed to provide comfortable, enriching out-world experiences. Working closely with 24 dementia patients and 51 medical and paramedical personnel, we co-designed an intelligent and personalized Virtual Reality system to enhance symptom management of dementia patients residing in long-term care. Through this paper, we thoroughly explain the screening process and analysis we run to identify which environments patients would like to receive as a Virtual Reality intervention to minimize the aforementioned co-existing symptoms of dementia, and the development of an intelligent system using the selected environments, that adapts the content of the Virtual Reality experience based on physiological and eye-tracking data from the patients and their personal preferences.